diff --git a/.github/workflows/auto_pr_review.yaml b/.github/workflows/auto_pr_review.yaml
index eaaca56060..c6a1cb9821 100644
--- a/.github/workflows/auto_pr_review.yaml
+++ b/.github/workflows/auto_pr_review.yaml
@@ -1,7 +1,7 @@
name: "PR review"
on:
pull_request_target:
- types: [opened, reopened, synchronize, edited, edited]
+ types: [opened, reopened, synchronize, edited]
jobs:
labeler:
@@ -50,4 +50,3 @@ jobs:
* all the tests are passing
* the change is [something we merge](https://github.com/commaai/openpilot/blob/master/docs/CONTRIBUTING.md#what-gets-merged)
* include a route or your device' dongle ID if relevant
-
diff --git a/.github/workflows/selfdrive_tests.yaml b/.github/workflows/selfdrive_tests.yaml
index 67a76a4232..25fc258634 100644
--- a/.github/workflows/selfdrive_tests.yaml
+++ b/.github/workflows/selfdrive_tests.yaml
@@ -85,26 +85,34 @@ jobs:
build_mac:
name: build macOS
- runs-on: ${{ github.repository == 'commaai/openpilot' && 'namespace-profile-macos-8x14' || 'macos-latest' }}
+ runs-on: ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-macos-8x14' || 'macos-latest' }}
steps:
- uses: actions/checkout@v4
with:
submodules: true
+ - run: echo "CACHE_COMMIT_DATE=$(git log -1 --pretty='format:%cd' --date=format:'%Y-%m-%d-%H:%M')" >> $GITHUB_ENV
- name: Homebrew cache
uses: ./.github/workflows/auto-cache
with:
path: ~/Library/Caches/Homebrew
+ key: brew-macos-${{ env.CACHE_COMMIT_DATE }}-${{ github.sha }}
+ restore-keys: |
+ brew-macos-${{ env.CACHE_COMMIT_DATE }}
+ brew-macos
- name: Install dependencies
run: ./tools/mac_setup.sh
env:
# package install has DeprecationWarnings
PYTHONWARNINGS: default
- run: git lfs pull
- - run: echo "CACHE_COMMIT_DATE=$(git log -1 --pretty='format:%cd' --date=format:'%Y-%m-%d-%H:%M')" >> $GITHUB_ENV
- name: Getting scons cache
uses: ./.github/workflows/auto-cache
with:
path: /tmp/scons_cache
+ key: scons-${{ runner.arch }}-macos-${{ env.CACHE_COMMIT_DATE }}-${{ github.sha }}
+ restore-keys: |
+ scons-${{ runner.arch }}-macos-${{ env.CACHE_COMMIT_DATE }}
+ scons-${{ runner.arch }}-macos
- name: Building openpilot
run: . .venv/bin/activate && scons -j$(nproc)
@@ -323,6 +331,7 @@ jobs:
runs-on:
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-profile-amd64-8x16' || 'ubuntu-24.04' }}
- ${{ ((github.repository == 'commaai/openpilot') && ((github.event_name != 'pull_request') || (github.event.pull_request.head.repo.full_name == 'commaai/openpilot'))) && 'namespace-experiments:docker.builds.local-cache=separate' || 'ubuntu-24.04' }}
+ if: false # FIXME: FrameReader is broken on CI runners
steps:
- uses: actions/checkout@v4
with:
diff --git a/.github/workflows/ui_preview.yaml b/.github/workflows/ui_preview.yaml
index 75e6249b76..9ec7a59223 100644
--- a/.github/workflows/ui_preview.yaml
+++ b/.github/workflows/ui_preview.yaml
@@ -19,7 +19,8 @@ env:
jobs:
preview:
- if: github.repository == 'commaai/openpilot'
+ #if: github.repository == 'commaai/openpilot'
+ if: false # FIXME: FrameReader is broken on CI runners
name: preview
runs-on: ubuntu-latest
timeout-minutes: 20
@@ -82,7 +83,7 @@ jobs:
if: github.event_name == 'pull_request_target'
id: find_diff
run: >-
- sudo apt-get install -y imagemagick
+ sudo apt-get update && sudo apt-get install -y imagemagick
scenes=$(find ${{ github.workspace }}/pr_ui/*.png -type f -printf "%f\n" | cut -d '.' -f 1 | grep -v 'pair_device')
A=($scenes)
@@ -93,8 +94,20 @@ jobs:
for ((i=0; i<${#A[*]}; i=i+1));
do
+ # Check if the master file exists
+ if [ ! -f "${{ github.workspace }}/master_ui/${A[$i]}.png" ]; then
+ # This is a new file in PR UI that doesn't exist in master
+ DIFF="${DIFF}"
+ DIFF="${DIFF}${A[$i]} : \$\${\\color{cyan}\\text{NEW}}\$\$
"
+ DIFF="${DIFF}"
- if ! compare -fuzz 2% -highlight-color DeepSkyBlue1 -lowlight-color Black -compose Src ${{ github.workspace }}/master_ui/${A[$i]}.png ${{ github.workspace }}/pr_ui/${A[$i]}.png ${{ github.workspace }}/pr_ui/${A[$i]}_diff.png; then
+ DIFF="${DIFF}"
+ DIFF="${DIFF} ![](\"https://raw.githubusercontent.com/commaai/ci-artifacts/${{) | "
+ DIFF="${DIFF}
"
+
+ DIFF="${DIFF}
"
+ DIFF="${DIFF} "
+ elif ! compare -fuzz 2% -highlight-color DeepSkyBlue1 -lowlight-color Black -compose Src ${{ github.workspace }}/master_ui/${A[$i]}.png ${{ github.workspace }}/pr_ui/${A[$i]}.png ${{ github.workspace }}/pr_ui/${A[$i]}_diff.png; then
convert ${{ github.workspace }}/pr_ui/${A[$i]}_diff.png -transparent black mask.png
composite mask.png ${{ github.workspace }}/master_ui/${A[$i]}.png composite_diff.png
convert -delay 100 ${{ github.workspace }}/master_ui/${A[$i]}.png composite_diff.png -loop 0 ${{ github.workspace }}/pr_ui/${A[$i]}_diff.gif
diff --git a/RELEASES.md b/RELEASES.md
index 071622f89a..ced7e3d4fc 100644
--- a/RELEASES.md
+++ b/RELEASES.md
@@ -1,6 +1,10 @@
-Version 0.9.9 (2025-04-XX)
+Version 0.9.9 (2025-04-30)
========================
+* New driving model
* Tesla Model 3 and Y support thanks to lukasloetkolben!
+* Coming soon
+ * New driving model supervised by MLSIM
+ * An online learner for steering actuator delay
Version 0.9.8 (2025-02-28)
========================
diff --git a/cereal/log.capnp b/cereal/log.capnp
index 7b6076311f..a5828d61cb 100644
--- a/cereal/log.capnp
+++ b/cereal/log.capnp
@@ -1174,6 +1174,8 @@ struct ModelDataV2 {
struct Action {
desiredCurvature @0 :Float32;
+ desiredAcceleration @1 :Float32;
+ shouldStop @2 :Bool;
}
}
@@ -1586,6 +1588,10 @@ struct UbloxGnss {
svId @0 :UInt8;
gnssId @1 :UInt8;
flagsBitfield @2 :UInt32;
+ cno @3 :UInt8;
+ elevationDeg @4 :Int8;
+ azimuthDeg @5 :Int16;
+ pseudorangeResidual @6 :Float32;
}
}
@@ -2274,6 +2280,22 @@ struct LiveTorqueParametersData {
useParams @12 :Bool;
}
+struct LiveDelayData {
+ lateralDelay @0 :Float32;
+ validBlocks @1 :Int32;
+ status @2 :Status;
+
+ lateralDelayEstimate @3 :Float32;
+ lateralDelayEstimateStd @5 :Float32;
+ points @4 :List(Float32);
+
+ enum Status {
+ unestimated @0;
+ estimated @1;
+ invalid @2;
+ }
+}
+
struct LiveMapDataDEPRECATED {
speedLimitValid @0 :Bool;
speedLimit @1 :Float32;
@@ -2504,6 +2526,7 @@ struct Event {
gnssMeasurements @91 :GnssMeasurements;
liveParameters @61 :LiveParametersData;
liveTorqueParameters @94 :LiveTorqueParametersData;
+ liveDelay @146 : LiveDelayData;
cameraOdometry @63 :CameraOdometry;
thumbnail @66: Thumbnail;
onroadEvents @134: List(OnroadEvent);
diff --git a/cereal/services.py b/cereal/services.py
index aad83177bb..82fc04bd00 100755
--- a/cereal/services.py
+++ b/cereal/services.py
@@ -36,6 +36,7 @@ _services: dict[str, tuple] = {
"errorLogMessage": (True, 0., 1),
"liveCalibration": (True, 4., 4),
"liveTorqueParameters": (True, 4., 1),
+ "liveDelay": (True, 4., 1),
"androidLog": (True, 0.),
"carState": (True, 100., 10),
"carControl": (True, 100., 10),
diff --git a/common/params_keys.h b/common/params_keys.h
index 2b540b744c..ca779a5b5c 100644
--- a/common/params_keys.h
+++ b/common/params_keys.h
@@ -34,7 +34,7 @@ inline static std::unordered_map keys = {
{"DoReboot", CLEAR_ON_MANAGER_START},
{"DoShutdown", CLEAR_ON_MANAGER_START},
{"DoUninstall", CLEAR_ON_MANAGER_START},
- {"ExperimentalLongitudinalEnabled", PERSISTENT | DEVELOPMENT_ONLY},
+ {"AlphaLongitudinalEnabled", PERSISTENT | DEVELOPMENT_ONLY},
{"ExperimentalMode", PERSISTENT},
{"ExperimentalModeConfirmed", PERSISTENT},
{"FirmwareQueryDone", CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION},
@@ -71,7 +71,9 @@ inline static std::unordered_map keys = {
{"LastPowerDropDetected", CLEAR_ON_MANAGER_START},
{"LastUpdateException", CLEAR_ON_MANAGER_START},
{"LastUpdateTime", PERSISTENT},
+ {"LiveDelay", PERSISTENT},
{"LiveParameters", PERSISTENT},
+ {"LiveParametersV2", PERSISTENT},
{"LiveTorqueParameters", PERSISTENT | DONT_LOG},
{"LocationFilterInitialState", PERSISTENT},
{"LongitudinalManeuverMode", CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION},
diff --git a/docs/CARS.md b/docs/CARS.md
index a3b1fe6351..a1b027c51b 100644
--- a/docs/CARS.md
+++ b/docs/CARS.md
@@ -4,328 +4,332 @@
A supported vehicle is one that just works when you install a comma device. All supported cars provide a better experience than any stock system. Supported vehicles reference the US market unless otherwise specified.
-# 302 Supported Cars
+# 304 Supported Cars
|Make|Model|Supported Package|ACC|No ACC accel below|No ALC below|Steering Torque|Resume from stop|![]()
Hardware Needed
|Video|
|---|---|---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
-|Acura|ILX 2016-19|AcuraWatch Plus|openpilot|26 mph|25 mph|[](##)|[](##)|Parts
- 1 Honda Nidec connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 Honda Nidec connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Honda Bosch A connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 USB-C coupler
- 1 VW J533 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 long OBD-C cable
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 USB-C coupler
- 1 VW J533 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 long OBD-C cable
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 USB-C coupler
- 1 VW J533 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 long OBD-C cable
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 USB-C coupler
- 1 VW J533 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 long OBD-C cable
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 USB-C coupler
- 1 VW J533 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 long OBD-C cable
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 USB-C coupler
- 1 VW J533 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 long OBD-C cable
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 Honda Nidec connector
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Honda Nidec connector
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Honda Bosch A connector
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 USB-C coupler
- 1 VW J533 connector
- 1 comma 3X
- 1 harness box
- 1 long OBD-C cable (9.5 ft)
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 USB-C coupler
- 1 VW J533 connector
- 1 comma 3X
- 1 harness box
- 1 long OBD-C cable (9.5 ft)
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 USB-C coupler
- 1 VW J533 connector
- 1 comma 3X
- 1 harness box
- 1 long OBD-C cable (9.5 ft)
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 USB-C coupler
- 1 VW J533 connector
- 1 comma 3X
- 1 harness box
- 1 long OBD-C cable (9.5 ft)
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 USB-C coupler
- 1 VW J533 connector
- 1 comma 3X
- 1 harness box
- 1 long OBD-C cable (9.5 ft)
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 USB-C coupler
- 1 VW J533 connector
- 1 comma 3X
- 1 harness box
- 1 long OBD-C cable (9.5 ft)
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 GM connector
- 1 comma 3X
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy Here
|
|Chevrolet|Bolt EV 2022-23|2LT Trim with Adaptive Cruise Control Package|openpilot available[1](#footnotes)|3 mph|6 mph|[](##)|[](##)|Parts
- 1 GM connector
- 1 comma 3X
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 GM connector
- 1 comma 3X
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 GM connector
- 1 comma 3X
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 GM connector
- 1 comma 3X
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 FCA connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 FCA connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 FCA connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 FCA connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 FCA connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 FCA connector
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 FCA connector
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 FCA connector
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 FCA connector
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 FCA connector
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 USB-C coupler
- 1 VW J533 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 long OBD-C cable
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 FCA connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 angled mount (8 degrees)
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q4 connector
- 1 USB-C coupler
- 1 angled mount (8 degrees)
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 long OBD-C cable
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 Ford Q4 connector
- 1 USB-C coupler
- 1 angled mount (8 degrees)
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 long OBD-C cable
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 angled mount (8 degrees)
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 angled mount (8 degrees)
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 angled mount (8 degrees)
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 angled mount (8 degrees)
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q4 connector
- 1 USB-C coupler
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 long OBD-C cable
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 Ford Q4 connector
- 1 USB-C coupler
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 long OBD-C cable
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Hyundai F connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Hyundai F connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Hyundai L connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Hyundai J connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Hyundai H connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Hyundai P connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Hyundai C connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Hyundai A connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Hyundai K connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Hyundai L connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Hyundai M connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Hyundai Q connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Hyundai Q connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Hyundai M connector
- 1 comma 3X
- 1 comma power v2
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 USB-C coupler
- 1 VW J533 connector
- 1 comma 3X
- 1 harness box
- 1 long OBD-C cable (9.5 ft)
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 FCA connector
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 Ford Q3 connector
- 1 angled mount (8 degrees)
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 right angle OBD-C cable (1.5 ft)
Buy HereParts
- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q3 connector
- 1 comma 3X
- 1 comma power v3
- 1 harness box
- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q4 connector
- 1 USB-C coupler
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- 1 comma 3X
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- 1 Ford Q4 connector
- 1 USB-C coupler
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 comma 3X
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- 1 angled mount (8 degrees)
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- 1 angled mount (8 degrees)
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- 1 angled mount (8 degrees)
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- 1 Ford Q3 connector
- 1 angled mount (8 degrees)
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- 1 Ford Q4 connector
- 1 USB-C coupler
- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 Ford Q4 connector
- 1 USB-C coupler
- 1 comma 3X
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- 1 harness box
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 mount
- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
- 1 comma power v2
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- 1 right angle OBD-C cable (1.5 ft)
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- 1 comma 3X
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- 1 comma 3X
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- 1 USB-C coupler
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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- 1 comma 3X
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2By default, this car will use the stock Adaptive Cruise Control (ACC) for longitudinal control. If the Driver Support Unit (DSU) is disconnected, openpilot ACC will replace stock ACC. NOTE: disconnecting the DSU disables Automatic Emergency Braking (AEB).
3Refers only to the Focus Mk4 (C519) available in Europe/China/Taiwan/Australasia, not the Focus Mk3 (C346) in North and South America/Southeast Asia.
-42019 Honda Civic 1.6L Diesel Sedan does not have ALC below 12mph.
-5Requires a CAN FD panda kit if not using comma 3X for this CAN FD car.
-6In the non-US market, openpilot requires the car to come equipped with EyeSight with Lane Keep Assistance.
-7Enabling longitudinal control (alpha) will disable all EyeSight functionality, including AEB, LDW, and RAB.
-8Some 2023 model years have HW4. To check which hardware type your vehicle has, look for Autopilot computer under Software -> Additional Vehicle Information on your vehicle's touchscreen. See this page for more information.
-9openpilot operates above 28mph for Camry 4CYL L, 4CYL LE and 4CYL SE which don't have Full-Speed Range Dynamic Radar Cruise Control.
-10Not including the China market Kamiq, which is based on the (currently) unsupported PQ34 platform.
-11Refers only to the MQB-based European B8 Passat, not the NMS Passat in the USA/China/Mideast markets.
-12Some Škoda vehicles are equipped with heated windshields, which are known to block GPS signal needed for some comma 3X functionality.
-13Only available for vehicles using a gateway (J533) harness. At this time, vehicles using a camera harness are limited to using stock ACC.
-14Model-years 2022 and beyond may have a combined CAN gateway and BCM, which is supported by openpilot in software, but doesn't yet have a harness available from the comma store.
+4See more setup details for GM.
+52019 Honda Civic 1.6L Diesel Sedan does not have ALC below 12mph.
+6Requires a CAN FD panda kit if not using comma 3X for this CAN FD car.
+7See more setup details for Nissan.
+8In the non-US market, openpilot requires the car to come equipped with EyeSight with Lane Keep Assistance.
+9Enabling longitudinal control (alpha) will disable all EyeSight functionality, including AEB, LDW, and RAB.
+10Some 2023 model years have HW4. To check which hardware type your vehicle has, look for Autopilot computer under Software -> Additional Vehicle Information on your vehicle's touchscreen. See this page for more information.
+11openpilot operates above 28mph for Camry 4CYL L, 4CYL LE and 4CYL SE which don't have Full-Speed Range Dynamic Radar Cruise Control.
+12Not including the China market Kamiq, which is based on the (currently) unsupported PQ34 platform.
+13Refers only to the MQB-based European B8 Passat, not the NMS Passat in the USA/China/Mideast markets.
+14Some Škoda vehicles are equipped with heated windshields, which are known to block GPS signal needed for some comma 3X functionality.
+15Only available for vehicles using a gateway (J533) harness. At this time, vehicles using a camera harness are limited to using stock ACC.
+16Model-years 2022 and beyond may have a combined CAN gateway and BCM, which is supported by openpilot in software, but doesn't yet have a harness available from the comma store.
## Community Maintained Cars
Although they're not upstream, the community has openpilot running on other makes and models. See the 'Community Supported Models' section of each make [on our wiki](https://wiki.comma.ai/).
diff --git a/docs/WORKFLOW.md b/docs/WORKFLOW.md
index 477c7511ca..1c5bbe9a63 100644
--- a/docs/WORKFLOW.md
+++ b/docs/WORKFLOW.md
@@ -31,13 +31,3 @@ cd system/loggerd && pytest .
# run the linter
op lint
```
-
-## Testing
-
-### Automated Testing
-
-All PRs and commits are automatically checked by GitHub Actions. Check out `.github/workflows/` for what GitHub Actions runs. Any new tests should be added to GitHub Actions.
-
-### Code Style and Linting
-
-Code is automatically checked for style by GitHub Actions as part of the automated tests. You can also run these tests yourself by running `pre-commit run --all`.
diff --git a/launch_env.sh b/launch_env.sh
index 9bee47837a..aff451e541 100755
--- a/launch_env.sh
+++ b/launch_env.sh
@@ -7,7 +7,7 @@ export OPENBLAS_NUM_THREADS=1
export VECLIB_MAXIMUM_THREADS=1
if [ -z "$AGNOS_VERSION" ]; then
- export AGNOS_VERSION="11.11"
+ export AGNOS_VERSION="11.13"
fi
export STAGING_ROOT="/data/safe_staging"
diff --git a/msgq_repo b/msgq_repo
index ad9020c430..94e738992c 160000
--- a/msgq_repo
+++ b/msgq_repo
@@ -1 +1 @@
-Subproject commit ad9020c430362d17c0edf97747d344389234be4d
+Subproject commit 94e738992ca8a12c2d9bb7bdeeaab4713543773e
diff --git a/opendbc_repo b/opendbc_repo
index b46e6340c1..3b33a71a2b 160000
--- a/opendbc_repo
+++ b/opendbc_repo
@@ -1 +1 @@
-Subproject commit b46e6340c15428ef72435b163ce03ffe66ffe563
+Subproject commit 3b33a71a2bf08b57dd5b2bf77e26cc376dcd7cc9
diff --git a/panda b/panda
index 1d5b89956b..d319ea2bba 160000
--- a/panda
+++ b/panda
@@ -1 +1 @@
-Subproject commit 1d5b89956b32bbda2940724ce70c5166e44668c5
+Subproject commit d319ea2bbae4ee0f5dea12d7ca5456cd34288d55
diff --git a/pyproject.toml b/pyproject.toml
index 1fb751e2d5..344bf2cfcc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -26,7 +26,7 @@ dependencies = [
"pycapnp",
"Cython",
"setuptools",
- "numpy < 2.0.0",
+ "numpy >=2.0, <2.2", # Linting issues with mypy in 2.2
# body / webrtcd
"aiohttp",
diff --git a/rednose_repo b/rednose_repo
index 05fd60278a..8b86052919 160000
--- a/rednose_repo
+++ b/rednose_repo
@@ -1 +1 @@
-Subproject commit 05fd60278a95190cc5a61f40730c82eaa1d986e1
+Subproject commit 8b860529199569401d5d8e105bc1be600fca49a8
diff --git a/scripts/jenkins_loop_test.sh b/scripts/jenkins_loop_test.sh
index 0b242e98dc..8073f4668c 100755
--- a/scripts/jenkins_loop_test.sh
+++ b/scripts/jenkins_loop_test.sh
@@ -16,7 +16,7 @@ CRUMB=$(curl -s --cookie-jar $COOKIE_JAR 'https://jenkins.comma.life/crumbIssuer
FIRST_LOOP=1
function loop() {
- JENKINS_BRANCH="__jenkins_loop_${BRANCH}"
+ JENKINS_BRANCH="__jenkins_loop_${BRANCH}_$(date +%s)"
API_ROUTE="https://jenkins.comma.life/job/openpilot/job/$JENKINS_BRANCH"
for run in $(seq 1 $((RUNS / 2))); do
diff --git a/selfdrive/car/card.py b/selfdrive/car/card.py
index 607f5590c4..378543164c 100755
--- a/selfdrive/car/card.py
+++ b/selfdrive/car/card.py
@@ -89,7 +89,7 @@ class Car:
if len(can.can) > 0:
break
- experimental_long_allowed = self.params.get_bool("ExperimentalLongitudinalEnabled")
+ alpha_long_allowed = self.params.get_bool("AlphaLongitudinalEnabled")
num_pandas = len(messaging.recv_one_retry(self.sm.sock['pandaStates']).pandaStates)
cached_params = None
@@ -98,7 +98,7 @@ class Car:
with car.CarParams.from_bytes(cached_params_raw) as _cached_params:
cached_params = _cached_params
- self.CI = get_car(*self.can_callbacks, obd_callback(self.params), experimental_long_allowed, num_pandas, cached_params)
+ self.CI = get_car(*self.can_callbacks, obd_callback(self.params), alpha_long_allowed, num_pandas, cached_params)
self.RI = interfaces[self.CI.CP.carFingerprint].RadarInterface(self.CI.CP)
self.CP = self.CI.CP
diff --git a/selfdrive/car/tests/test_car_interfaces.py b/selfdrive/car/tests/test_car_interfaces.py
index e0cd5a1e91..92c7ff8f1c 100644
--- a/selfdrive/car/tests/test_car_interfaces.py
+++ b/selfdrive/car/tests/test_car_interfaces.py
@@ -39,7 +39,7 @@ class TestCarInterfaces:
args = get_fuzzy_car_interface_args(data.draw)
car_params = CarInterface.get_params(car_name, args['fingerprints'], args['car_fw'],
- experimental_long=args['experimental_long'], docs=False)
+ alpha_long=args['alpha_long'], docs=False)
car_params = car_params.as_reader()
car_interface = CarInterface(car_params)
assert car_params
diff --git a/selfdrive/car/tests/test_models.py b/selfdrive/car/tests/test_models.py
index 906fa99320..53f2bb586d 100644
--- a/selfdrive/car/tests/test_models.py
+++ b/selfdrive/car/tests/test_models.py
@@ -78,7 +78,7 @@ class TestCarModelBase(unittest.TestCase):
cls.elm_frame = None
cls.car_safety_mode_frame = None
cls.fingerprint = gen_empty_fingerprint()
- experimental_long = False
+ alpha_long = False
for msg in lr:
if msg.which() == "can":
can = can_capnp_to_list((msg.as_builder().to_bytes(),))[0]
@@ -91,7 +91,7 @@ class TestCarModelBase(unittest.TestCase):
elif msg.which() == "carParams":
car_fw = msg.carParams.carFw
if msg.carParams.openpilotLongitudinalControl:
- experimental_long = True
+ alpha_long = True
if cls.platform is None:
live_fingerprint = msg.carParams.carFingerprint
cls.platform = MIGRATION.get(live_fingerprint, live_fingerprint)
@@ -113,7 +113,7 @@ class TestCarModelBase(unittest.TestCase):
cls.car_safety_mode_frame = len(can_msgs)
assert len(can_msgs) > int(50 / DT_CTRL), "no can data found"
- return car_fw, can_msgs, experimental_long
+ return car_fw, can_msgs, alpha_long
@classmethod
def get_testing_data(cls):
@@ -146,13 +146,13 @@ class TestCarModelBase(unittest.TestCase):
raise unittest.SkipTest
raise Exception(f"missing test route for {cls.platform}")
- car_fw, cls.can_msgs, experimental_long = cls.get_testing_data()
+ car_fw, cls.can_msgs, alpha_long = cls.get_testing_data()
# if relay is expected to be open in the route
cls.openpilot_enabled = cls.car_safety_mode_frame is not None
cls.CarInterface = interfaces[cls.platform]
- cls.CP = cls.CarInterface.get_params(cls.platform, cls.fingerprint, car_fw, experimental_long, docs=False)
+ cls.CP = cls.CarInterface.get_params(cls.platform, cls.fingerprint, car_fw, alpha_long, docs=False)
assert cls.CP
assert cls.CP.carFingerprint == cls.platform
diff --git a/selfdrive/controls/controlsd.py b/selfdrive/controls/controlsd.py
index f6fabfc421..dfff26d9db 100755
--- a/selfdrive/controls/controlsd.py
+++ b/selfdrive/controls/controlsd.py
@@ -12,7 +12,7 @@ from openpilot.common.swaglog import cloudlog
from opendbc.car.car_helpers import interfaces
from opendbc.car.vehicle_model import VehicleModel
from openpilot.selfdrive.controls.lib.drive_helpers import clip_curvature
-from openpilot.selfdrive.controls.lib.latcontrol import LatControl, MIN_LATERAL_CONTROL_SPEED
+from openpilot.selfdrive.controls.lib.latcontrol import LatControl
from openpilot.selfdrive.controls.lib.latcontrol_pid import LatControlPID
from openpilot.selfdrive.controls.lib.latcontrol_angle import LatControlAngle, STEER_ANGLE_SATURATION_THRESHOLD
from openpilot.selfdrive.controls.lib.latcontrol_torque import LatControlTorque
@@ -41,6 +41,7 @@ class Controls:
self.pm = messaging.PubMaster(['carControl', 'controlsState'])
self.steer_limited_by_controls = False
+ self.curvature = 0.0
self.desired_curvature = 0.0
self.pose_calibrator = PoseCalibrator()
@@ -73,6 +74,9 @@ class Controls:
sr = max(lp.steerRatio, 0.1)
self.VM.update_params(x, sr)
+ steer_angle_without_offset = math.radians(CS.steeringAngleDeg - lp.angleOffsetDeg)
+ self.curvature = -self.VM.calc_curvature(steer_angle_without_offset, CS.vEgo, lp.roll)
+
# Update Torque Params
if self.CP.lateralTuning.which() == 'torque':
torque_params = self.sm['liveTorqueParameters']
@@ -87,8 +91,9 @@ class Controls:
CC.enabled = self.sm['selfdriveState'].enabled
# Check which actuators can be enabled
- standstill = abs(CS.vEgo) <= max(self.CP.minSteerSpeed, MIN_LATERAL_CONTROL_SPEED) or CS.standstill
- CC.latActive = self.sm['selfdriveState'].active and not CS.steerFaultTemporary and not CS.steerFaultPermanent and not standstill
+ standstill = abs(CS.vEgo) <= max(self.CP.minSteerSpeed, 0.3) or CS.standstill
+ CC.latActive = self.sm['selfdriveState'].active and not CS.steerFaultTemporary and not CS.steerFaultPermanent and \
+ (not standstill or self.CP.steerAtStandstill)
CC.longActive = CC.enabled and not any(e.overrideLongitudinal for e in self.sm['onroadEvents']) and self.CP.openpilotLongitudinalControl
actuators = CC.actuators
@@ -109,7 +114,10 @@ class Controls:
actuators.accel = float(self.LoC.update(CC.longActive, CS, long_plan.aTarget, long_plan.shouldStop, pid_accel_limits))
# Steering PID loop and lateral MPC
- self.desired_curvature, curvature_limited = clip_curvature(CS.vEgo, self.desired_curvature, model_v2.action.desiredCurvature, lp.roll)
+ # Reset desired curvature to current to avoid violating the limits on engage
+ new_desired_curvature = model_v2.action.desiredCurvature if CC.latActive else self.curvature
+ self.desired_curvature, curvature_limited = clip_curvature(CS.vEgo, self.desired_curvature, new_desired_curvature, lp.roll)
+
actuators.curvature = self.desired_curvature
steer, steeringAngleDeg, lac_log = self.LaC.update(CC.latActive, CS, self.VM, lp,
self.steer_limited_by_controls, self.desired_curvature,
@@ -174,10 +182,7 @@ class Controls:
dat.valid = CS.canValid
cs = dat.controlsState
- lp = self.sm['liveParameters']
- steer_angle_without_offset = math.radians(CS.steeringAngleDeg - lp.angleOffsetDeg)
- cs.curvature = -self.VM.calc_curvature(steer_angle_without_offset, CS.vEgo, lp.roll)
-
+ cs.curvature = self.curvature
cs.longitudinalPlanMonoTime = self.sm.logMonoTime['longitudinalPlan']
cs.lateralPlanMonoTime = self.sm.logMonoTime['modelV2']
cs.desiredCurvature = self.desired_curvature
diff --git a/selfdrive/controls/lib/drive_helpers.py b/selfdrive/controls/lib/drive_helpers.py
index 41384abae8..3f99f1bbbb 100644
--- a/selfdrive/controls/lib/drive_helpers.py
+++ b/selfdrive/controls/lib/drive_helpers.py
@@ -1,7 +1,7 @@
import numpy as np
from cereal import log
from opendbc.car.vehicle_model import ACCELERATION_DUE_TO_GRAVITY
-from openpilot.common.realtime import DT_CTRL
+from openpilot.common.realtime import DT_CTRL, DT_MDL
MIN_SPEED = 1.0
CONTROL_N = 17
@@ -19,6 +19,9 @@ def clamp(val, min_val, max_val):
clamped_val = float(np.clip(val, min_val, max_val))
return clamped_val, clamped_val != val
+def smooth_value(val, prev_val, tau, dt=DT_MDL):
+ alpha = 1 - np.exp(-dt/tau) if tau > 0 else 1
+ return alpha * val + (1 - alpha) * prev_val
def clip_curvature(v_ego, prev_curvature, new_curvature, roll):
# This function respects ISO lateral jerk and acceleration limits + a max curvature
@@ -43,3 +46,19 @@ def get_speed_error(modelV2: log.ModelDataV2, v_ego: float) -> float:
vel_err = np.clip(modelV2.temporalPose.trans[0] - v_ego, -MAX_VEL_ERR, MAX_VEL_ERR)
return float(vel_err)
return 0.0
+
+
+def get_accel_from_plan(speeds, accels, t_idxs, action_t=DT_MDL, vEgoStopping=0.05):
+ if len(speeds) == len(t_idxs):
+ v_now = speeds[0]
+ a_now = accels[0]
+ v_target = np.interp(action_t, t_idxs, speeds)
+ a_target = 2 * (v_target - v_now) / (action_t) - a_now
+ v_target_1sec = np.interp(action_t + 1.0, t_idxs, speeds)
+ else:
+ v_target = 0.0
+ v_target_1sec = 0.0
+ a_target = 0.0
+ should_stop = (v_target < vEgoStopping and
+ v_target_1sec < vEgoStopping)
+ return a_target, should_stop
diff --git a/selfdrive/controls/lib/latcontrol.py b/selfdrive/controls/lib/latcontrol.py
index dcf0003430..d67a4aa959 100644
--- a/selfdrive/controls/lib/latcontrol.py
+++ b/selfdrive/controls/lib/latcontrol.py
@@ -3,8 +3,6 @@ from abc import abstractmethod, ABC
from openpilot.common.realtime import DT_CTRL
-MIN_LATERAL_CONTROL_SPEED = 0.3 # m/s
-
class LatControl(ABC):
def __init__(self, CP, CI):
diff --git a/selfdrive/controls/lib/longitudinal_planner.py b/selfdrive/controls/lib/longitudinal_planner.py
index c7a2295a5f..4219e80f33 100755
--- a/selfdrive/controls/lib/longitudinal_planner.py
+++ b/selfdrive/controls/lib/longitudinal_planner.py
@@ -11,7 +11,7 @@ from openpilot.selfdrive.modeld.constants import ModelConstants
from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState
from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import LongitudinalMpc
from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import T_IDXS as T_IDXS_MPC
-from openpilot.selfdrive.controls.lib.drive_helpers import CONTROL_N, get_speed_error
+from openpilot.selfdrive.controls.lib.drive_helpers import CONTROL_N, get_speed_error, get_accel_from_plan
from openpilot.selfdrive.car.cruise import V_CRUISE_MAX, V_CRUISE_UNSET
from openpilot.common.swaglog import cloudlog
@@ -48,27 +48,11 @@ def limit_accel_in_turns(v_ego, angle_steers, a_target, CP):
return [a_target[0], min(a_target[1], a_x_allowed)]
-def get_accel_from_plan(speeds, accels, action_t=DT_MDL, vEgoStopping=0.05):
- if len(speeds) == CONTROL_N:
- v_now = speeds[0]
- a_now = accels[0]
-
- v_target = np.interp(action_t, CONTROL_N_T_IDX, speeds)
- a_target = 2 * (v_target - v_now) / (action_t) - a_now
- v_target_1sec = np.interp(action_t + 1.0, CONTROL_N_T_IDX, speeds)
- else:
- v_target = 0.0
- v_target_1sec = 0.0
- a_target = 0.0
- should_stop = (v_target < vEgoStopping and
- v_target_1sec < vEgoStopping)
- return a_target, should_stop
-
-
class LongitudinalPlanner:
def __init__(self, CP, init_v=0.0, init_a=0.0, dt=DT_MDL):
self.CP = CP
self.mpc = LongitudinalMpc(dt=dt)
+ self.mpc.mode = 'acc'
self.fcw = False
self.dt = dt
self.allow_throttle = True
@@ -106,7 +90,7 @@ class LongitudinalPlanner:
return x, v, a, j, throttle_prob
def update(self, sm):
- self.mpc.mode = 'blended' if sm['selfdriveState'].experimentalMode else 'acc'
+ self.mode = 'blended' if sm['selfdriveState'].experimentalMode else 'acc'
if len(sm['carControl'].orientationNED) == 3:
accel_coast = get_coast_accel(sm['carControl'].orientationNED[1])
@@ -129,7 +113,7 @@ class LongitudinalPlanner:
# No change cost when user is controlling the speed, or when standstill
prev_accel_constraint = not (reset_state or sm['carState'].standstill)
- if self.mpc.mode == 'acc':
+ if self.mode == 'acc':
accel_clip = [ACCEL_MIN, get_max_accel(v_ego)]
steer_angle_without_offset = sm['carState'].steeringAngleDeg - sm['liveParameters'].angleOffsetDeg
accel_clip = limit_accel_in_turns(v_ego, steer_angle_without_offset, accel_clip, self.CP)
@@ -176,8 +160,17 @@ class LongitudinalPlanner:
self.v_desired_filter.x = self.v_desired_filter.x + self.dt * (self.a_desired + a_prev) / 2.0
action_t = self.CP.longitudinalActuatorDelay + DT_MDL
- output_a_target, self.output_should_stop = get_accel_from_plan(self.v_desired_trajectory, self.a_desired_trajectory,
+ output_a_target_mpc, output_should_stop_mpc = get_accel_from_plan(self.v_desired_trajectory, self.a_desired_trajectory, CONTROL_N_T_IDX,
action_t=action_t, vEgoStopping=self.CP.vEgoStopping)
+ output_a_target_e2e = sm['modelV2'].action.desiredAcceleration
+ output_should_stop_e2e = sm['modelV2'].action.shouldStop
+
+ if self.mode == 'acc':
+ output_a_target = output_a_target_mpc
+ self.output_should_stop = output_should_stop_mpc
+ else:
+ output_a_target = min(output_a_target_mpc, output_a_target_e2e)
+ self.output_should_stop = output_should_stop_e2e or output_should_stop_mpc
for idx in range(2):
accel_clip[idx] = np.clip(accel_clip[idx], self.prev_accel_clip[idx] - 0.05, self.prev_accel_clip[idx] + 0.05)
diff --git a/selfdrive/debug/max_lat_accel.py b/selfdrive/debug/max_lat_accel.py
index 2369d99d86..dc44e8ac40 100755
--- a/selfdrive/debug/max_lat_accel.py
+++ b/selfdrive/debug/max_lat_accel.py
@@ -2,6 +2,8 @@
import argparse
import numpy as np
import matplotlib.pyplot as plt
+from functools import partial
+from tqdm import tqdm
from typing import NamedTuple
from openpilot.tools.lib.logreader import LogReader
from openpilot.selfdrive.locationd.models.pose_kf import EARTH_G
@@ -20,14 +22,15 @@ class Event(NamedTuple):
timestamp: float # relative to start of route (s)
-def find_events(lr: LogReader, qlog: bool = False) -> list[Event]:
+def find_events(lr: LogReader, extrapolate: bool = False, qlog: bool = False) -> list[Event]:
min_lat_active = RLOG_MIN_LAT_ACTIVE // QLOG_DECIMATION if qlog else RLOG_MIN_LAT_ACTIVE
min_steering_unpressed = RLOG_MIN_STEERING_UNPRESSED // QLOG_DECIMATION if qlog else RLOG_MIN_STEERING_UNPRESSED
min_requesting_max = RLOG_MIN_REQUESTING_MAX // QLOG_DECIMATION if qlog else RLOG_MIN_REQUESTING_MAX
- events = []
+ # if we test with driver torque safety, max torque can be slightly noisy
+ steer_threshold = 0.7 if extrapolate else 0.95
- start_ts = 0
+ events = []
# state tracking
steering_unpressed = 0 # frames
@@ -38,7 +41,9 @@ def find_events(lr: LogReader, qlog: bool = False) -> list[Event]:
curvature = 0
v_ego = 0
roll = 0
+ out_torque = 0
+ start_ts = 0
for msg in lr:
if msg.which() == 'carControl':
if start_ts == 0:
@@ -47,8 +52,8 @@ def find_events(lr: LogReader, qlog: bool = False) -> list[Event]:
lat_active = lat_active + 1 if msg.carControl.latActive else 0
elif msg.which() == 'carOutput':
- # if we test with driver torque safety, max torque can be slightly noisy
- requesting_max = requesting_max + 1 if abs(msg.carOutput.actuatorsOutput.torque) > 0.95 else 0
+ out_torque = msg.carOutput.actuatorsOutput.torque
+ requesting_max = requesting_max + 1 if abs(out_torque) > steer_threshold else 0
elif msg.which() == 'carState':
steering_unpressed = steering_unpressed + 1 if not msg.carState.steeringPressed else 0
@@ -64,7 +69,8 @@ def find_events(lr: LogReader, qlog: bool = False) -> list[Event]:
# TODO: record max lat accel at the end of the event, need to use the past lat accel as overriding can happen before we detect it
requesting_max = 0
- current_lateral_accel = curvature * v_ego ** 2 - roll * EARTH_G
+ factor = 1 / abs(out_torque)
+ current_lateral_accel = (curvature * v_ego ** 2 * factor) - roll * EARTH_G
events.append(Event(current_lateral_accel, v_ego, roll, round((msg.logMonoTime - start_ts) * 1e-9, 2)))
print(events[-1])
@@ -75,29 +81,38 @@ if __name__ == '__main__':
parser = argparse.ArgumentParser(description="Find max lateral acceleration events",
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
- parser.add_argument("route")
+ parser.add_argument("route", nargs='+')
+ parser.add_argument("-e", "--extrapolate", action="store_true", help="Extrapolates max lateral acceleration events linearly. " +
+ "This option can be far less accurate.")
args = parser.parse_args()
- lr = LogReader(args.route, sort_by_time=True)
- qlog = args.route.endswith('/q')
- if qlog:
- print('WARNING: Treating route as qlog!')
+ events = []
+ for route in tqdm(args.route):
+ try:
+ lr = LogReader(route, sort_by_time=True)
+ except Exception:
+ print(f'Skipping {route}')
+ continue
+
+ qlog = route.endswith('/q')
+ if qlog:
+ print('WARNING: Treating route as qlog!')
- print('Finding events...')
- events = find_events(lr, qlog=qlog)
+ print('Finding events...')
+ events += lr.run_across_segments(8, partial(find_events, extrapolate=args.extrapolate, qlog=qlog), disable_tqdm=True)
print()
print(f'Found {len(events)} events')
- perc_left_accel = -np.percentile([-ev.lateral_accel for ev in events if ev.lateral_accel < 0], 90)
- perc_right_accel = np.percentile([ev.lateral_accel for ev in events if ev.lateral_accel > 0], 90)
+ perc_left_accel = -np.percentile([-ev.lateral_accel for ev in events if ev.lateral_accel < 0] or [0], 90)
+ perc_right_accel = np.percentile([ev.lateral_accel for ev in events if ev.lateral_accel > 0] or [0], 90)
CP = lr.first('carParams')
plt.ion()
plt.clf()
plt.suptitle(f'{CP.carFingerprint} - Max lateral acceleration events')
- plt.title(args.route)
+ plt.title(', '.join(args.route))
plt.scatter([ev.speed for ev in events], [ev.lateral_accel for ev in events], label='max lateral accel events')
plt.plot([0, 35], [3, 3], c='r', label='ISO 11270 - 3 m/s^2')
diff --git a/selfdrive/debug/set_car_params.py b/selfdrive/debug/set_car_params.py
index 6060dfbc36..aec30b4d74 100755
--- a/selfdrive/debug/set_car_params.py
+++ b/selfdrive/debug/set_car_params.py
@@ -15,7 +15,7 @@ if __name__ == "__main__":
else:
CP = car.CarParams.new_message()
CP.openpilotLongitudinalControl = True
- CP.experimentalLongitudinalAvailable = False
+ CP.alphaLongitudinalAvailable = False
cp_bytes = CP.to_bytes()
for p in ("CarParams", "CarParamsCache", "CarParamsPersistent"):
diff --git a/selfdrive/locationd/calibrationd.py b/selfdrive/locationd/calibrationd.py
index 8ce884ae4f..e265b70f1a 100755
--- a/selfdrive/locationd/calibrationd.py
+++ b/selfdrive/locationd/calibrationd.py
@@ -11,7 +11,7 @@ import capnp
import numpy as np
from typing import NoReturn
-from cereal import log
+from cereal import log, car
import cereal.messaging as messaging
from openpilot.common.conversions import Conversions as CV
from openpilot.common.params import Params
@@ -258,16 +258,18 @@ def main() -> NoReturn:
config_realtime_process([0, 1, 2, 3], 5)
pm = messaging.PubMaster(['liveCalibration'])
- sm = messaging.SubMaster(['cameraOdometry', 'carState', 'carParams'], poll='cameraOdometry')
+ sm = messaging.SubMaster(['cameraOdometry', 'carState'], poll='cameraOdometry')
+
+ params_reader = Params()
+ CP = messaging.log_from_bytes(params_reader.get("CarParams", block=True), car.CarParams)
calibrator = Calibrator(param_put=True)
+ calibrator.not_car = CP.notCar
while 1:
timeout = 0 if sm.frame == -1 else 100
sm.update(timeout)
- calibrator.not_car = sm['carParams'].notCar
-
if sm.updated['cameraOdometry']:
calibrator.handle_v_ego(sm['carState'].vEgo)
new_rpy = calibrator.handle_cam_odom(sm['cameraOdometry'].trans,
diff --git a/selfdrive/locationd/helpers.py b/selfdrive/locationd/helpers.py
index af307b0336..a3e3ae4a8c 100644
--- a/selfdrive/locationd/helpers.py
+++ b/selfdrive/locationd/helpers.py
@@ -1,10 +1,48 @@
import numpy as np
from typing import Any
+from functools import cache
from cereal import log
from openpilot.common.transformations.orientation import rot_from_euler, euler_from_rot
+@cache
+def fft_next_good_size(n: int) -> int:
+ """
+ smallest composite of 2, 3, 5, 7, 11 that is >= n
+ inspired by pocketfft
+ """
+ if n <= 6:
+ return n
+ best, f2 = 2 * n, 1
+ while f2 < best:
+ f23 = f2
+ while f23 < best:
+ f235 = f23
+ while f235 < best:
+ f2357 = f235
+ while f2357 < best:
+ f235711 = f2357
+ while f235711 < best:
+ best = f235711 if f235711 >= n else best
+ f235711 *= 11
+ f2357 *= 7
+ f235 *= 5
+ f23 *= 3
+ f2 *= 2
+ return best
+
+
+def parabolic_peak_interp(R, max_index):
+ if max_index == 0 or max_index == len(R) - 1:
+ return max_index
+
+ y_m1, y_0, y_p1 = R[max_index - 1], R[max_index], R[max_index + 1]
+ offset = 0.5 * (y_p1 - y_m1) / (2 * y_0 - y_p1 - y_m1)
+
+ return max_index + offset
+
+
def rotate_cov(rot_matrix, cov_in):
return rot_matrix @ cov_in @ rot_matrix.T
diff --git a/selfdrive/locationd/lagd.py b/selfdrive/locationd/lagd.py
new file mode 100755
index 0000000000..f4f46b7469
--- /dev/null
+++ b/selfdrive/locationd/lagd.py
@@ -0,0 +1,373 @@
+#!/usr/bin/env python3
+import os
+import numpy as np
+import capnp
+from collections import deque
+from functools import partial
+
+import cereal.messaging as messaging
+from cereal import car, log
+from cereal.services import SERVICE_LIST
+from openpilot.common.params import Params
+from openpilot.common.realtime import config_realtime_process
+from openpilot.common.swaglog import cloudlog
+from openpilot.selfdrive.locationd.helpers import PoseCalibrator, Pose, fft_next_good_size, parabolic_peak_interp
+
+BLOCK_SIZE = 100
+BLOCK_NUM = 50
+BLOCK_NUM_NEEDED = 5
+MOVING_WINDOW_SEC = 300.0
+MIN_OKAY_WINDOW_SEC = 25.0
+MIN_RECOVERY_BUFFER_SEC = 2.0
+MIN_VEGO = 15.0
+MIN_ABS_YAW_RATE = np.radians(1.0)
+MAX_YAW_RATE_SANITY_CHECK = 1.0
+MIN_NCC = 0.95
+MAX_LAG = 1.0
+MAX_LAG_STD = 0.1
+MAX_LAT_ACCEL = 2.0
+MAX_LAT_ACCEL_DIFF = 0.6
+
+
+def masked_normalized_cross_correlation(expected_sig: np.ndarray, actual_sig: np.ndarray, mask: np.ndarray, n: int):
+ """
+ References:
+ D. Padfield. "Masked FFT registration". In Proc. Computer Vision and
+ Pattern Recognition, pp. 2918-2925 (2010).
+ :DOI:`10.1109/CVPR.2010.5540032`
+ """
+
+ eps = np.finfo(np.float64).eps
+ expected_sig = np.asarray(expected_sig, dtype=np.float64)
+ actual_sig = np.asarray(actual_sig, dtype=np.float64)
+
+ expected_sig[~mask] = 0.0
+ actual_sig[~mask] = 0.0
+
+ rotated_expected_sig = expected_sig[::-1]
+ rotated_mask = mask[::-1]
+
+ fft = partial(np.fft.fft, n=n)
+
+ actual_sig_fft = fft(actual_sig)
+ rotated_expected_sig_fft = fft(rotated_expected_sig)
+ actual_mask_fft = fft(mask.astype(np.float64))
+ rotated_mask_fft = fft(rotated_mask.astype(np.float64))
+
+ number_overlap_masked_samples = np.fft.ifft(rotated_mask_fft * actual_mask_fft).real
+ number_overlap_masked_samples[:] = np.round(number_overlap_masked_samples)
+ number_overlap_masked_samples[:] = np.fmax(number_overlap_masked_samples, eps)
+ masked_correlated_actual_fft = np.fft.ifft(rotated_mask_fft * actual_sig_fft).real
+ masked_correlated_expected_fft = np.fft.ifft(actual_mask_fft * rotated_expected_sig_fft).real
+
+ numerator = np.fft.ifft(rotated_expected_sig_fft * actual_sig_fft).real
+ numerator -= masked_correlated_actual_fft * masked_correlated_expected_fft / number_overlap_masked_samples
+
+ actual_squared_fft = fft(actual_sig ** 2)
+ actual_sig_denom = np.fft.ifft(rotated_mask_fft * actual_squared_fft).real
+ actual_sig_denom -= masked_correlated_actual_fft ** 2 / number_overlap_masked_samples
+ actual_sig_denom[:] = np.fmax(actual_sig_denom, 0.0)
+
+ rotated_expected_squared_fft = fft(rotated_expected_sig ** 2)
+ expected_sig_denom = np.fft.ifft(actual_mask_fft * rotated_expected_squared_fft).real
+ expected_sig_denom -= masked_correlated_expected_fft ** 2 / number_overlap_masked_samples
+ expected_sig_denom[:] = np.fmax(expected_sig_denom, 0.0)
+
+ denom = np.sqrt(actual_sig_denom * expected_sig_denom)
+
+ # zero-out samples with very small denominators
+ tol = 1e3 * eps * np.max(np.abs(denom), keepdims=True)
+ nonzero_indices = denom > tol
+
+ ncc = np.zeros_like(denom, dtype=np.float64)
+ ncc[nonzero_indices] = numerator[nonzero_indices] / denom[nonzero_indices]
+ np.clip(ncc, -1, 1, out=ncc)
+
+ return ncc
+
+
+class Points:
+ def __init__(self, num_points: int):
+ self.times = deque[float]([0.0] * num_points, maxlen=num_points)
+ self.okay = deque[bool]([False] * num_points, maxlen=num_points)
+ self.desired = deque[float]([0.0] * num_points, maxlen=num_points)
+ self.actual = deque[float]([0.0] * num_points, maxlen=num_points)
+
+ @property
+ def num_points(self):
+ return len(self.desired)
+
+ @property
+ def num_okay(self):
+ return np.count_nonzero(self.okay)
+
+ def update(self, t: float, desired: float, actual: float, okay: bool):
+ self.times.append(t)
+ self.okay.append(okay)
+ self.desired.append(desired)
+ self.actual.append(actual)
+
+ def get(self) -> tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
+ return np.array(self.times), np.array(self.desired), np.array(self.actual), np.array(self.okay)
+
+
+class BlockAverage:
+ def __init__(self, num_blocks: int, block_size: int, valid_blocks: int, initial_value: float):
+ self.num_blocks = num_blocks
+ self.block_size = block_size
+ self.block_idx = valid_blocks % num_blocks
+ self.idx = 0
+
+ self.values = np.tile(initial_value, (num_blocks, 1))
+ self.valid_blocks = valid_blocks
+
+ def update(self, value: float):
+ self.values[self.block_idx] = (self.idx * self.values[self.block_idx] + value) / (self.idx + 1)
+ self.idx = (self.idx + 1) % self.block_size
+ if self.idx == 0:
+ self.block_idx = (self.block_idx + 1) % self.num_blocks
+ self.valid_blocks = min(self.valid_blocks + 1, self.num_blocks)
+
+ def get(self) -> tuple[float, float, float, float]:
+ valid_block_idx = [i for i in range(self.valid_blocks) if i != self.block_idx]
+ valid_and_current_idx = valid_block_idx + ([self.block_idx] if self.idx > 0 else [])
+
+ if len(valid_block_idx) > 0:
+ valid_mean = float(np.mean(self.values[valid_block_idx], axis=0).item())
+ valid_std = float(np.std(self.values[valid_block_idx], axis=0).item())
+ else:
+ valid_mean, valid_std = float('nan'), float('nan')
+
+ if len(valid_and_current_idx) > 0:
+ current_mean = float(np.mean(self.values[valid_and_current_idx], axis=0).item())
+ current_std = float(np.std(self.values[valid_and_current_idx], axis=0).item())
+ else:
+ current_mean, current_std = float('nan'), float('nan')
+
+ return valid_mean, valid_std, current_mean, current_std
+
+
+class LateralLagEstimator:
+ inputs = {"carControl", "carState", "controlsState", "liveCalibration", "livePose"}
+
+ def __init__(self, CP: car.CarParams, dt: float,
+ block_count: int = BLOCK_NUM, min_valid_block_count: int = BLOCK_NUM_NEEDED, block_size: int = BLOCK_SIZE,
+ window_sec: float = MOVING_WINDOW_SEC, okay_window_sec: float = MIN_OKAY_WINDOW_SEC, min_recovery_buffer_sec: float = MIN_RECOVERY_BUFFER_SEC,
+ min_vego: float = MIN_VEGO, min_yr: float = MIN_ABS_YAW_RATE, min_ncc: float = MIN_NCC,
+ max_lat_accel: float = MAX_LAT_ACCEL, max_lat_accel_diff: float = MAX_LAT_ACCEL_DIFF):
+ self.dt = dt
+ self.window_sec = window_sec
+ self.okay_window_sec = okay_window_sec
+ self.min_recovery_buffer_sec = min_recovery_buffer_sec
+ self.initial_lag = CP.steerActuatorDelay + 0.2
+ self.block_size = block_size
+ self.block_count = block_count
+ self.min_valid_block_count = min_valid_block_count
+ self.min_vego = min_vego
+ self.min_yr = min_yr
+ self.min_ncc = min_ncc
+ self.max_lat_accel = max_lat_accel
+ self.max_lat_accel_diff = max_lat_accel_diff
+
+ self.t = 0.0
+ self.lat_active = False
+ self.steering_pressed = False
+ self.steering_saturated = False
+ self.desired_curvature = 0.0
+ self.v_ego = 0.0
+ self.yaw_rate = 0.0
+ self.yaw_rate_std = 0.0
+ self.pose_valid = False
+
+ self.last_lat_inactive_t = 0.0
+ self.last_steering_pressed_t = 0.0
+ self.last_steering_saturated_t = 0.0
+ self.last_pose_invalid_t = 0.0
+ self.last_estimate_t = 0.0
+
+ self.calibrator = PoseCalibrator()
+
+ self.reset(self.initial_lag, 0)
+
+ def reset(self, initial_lag: float, valid_blocks: int):
+ window_len = int(self.window_sec / self.dt)
+ self.points = Points(window_len)
+ self.block_avg = BlockAverage(self.block_count, self.block_size, valid_blocks, initial_lag)
+
+ def get_msg(self, valid: bool, debug: bool = False) -> capnp._DynamicStructBuilder:
+ msg = messaging.new_message('liveDelay')
+
+ msg.valid = valid
+
+ liveDelay = msg.liveDelay
+
+ valid_mean_lag, valid_std, current_mean_lag, current_std = self.block_avg.get()
+ if self.block_avg.valid_blocks >= self.min_valid_block_count and not np.isnan(valid_mean_lag) and not np.isnan(valid_std):
+ if valid_std > MAX_LAG_STD:
+ liveDelay.status = log.LiveDelayData.Status.invalid
+ else:
+ liveDelay.status = log.LiveDelayData.Status.estimated
+ else:
+ liveDelay.status = log.LiveDelayData.Status.unestimated
+
+ if liveDelay.status == log.LiveDelayData.Status.estimated:
+ liveDelay.lateralDelay = valid_mean_lag
+ else:
+ liveDelay.lateralDelay = self.initial_lag
+
+ if not np.isnan(current_mean_lag) and not np.isnan(current_std):
+ liveDelay.lateralDelayEstimate = current_mean_lag
+ liveDelay.lateralDelayEstimateStd = current_std
+ else:
+ liveDelay.lateralDelayEstimate = self.initial_lag
+ liveDelay.lateralDelayEstimateStd = 0.0
+
+ liveDelay.validBlocks = self.block_avg.valid_blocks
+ if debug:
+ liveDelay.points = self.block_avg.values.flatten().tolist()
+
+ return msg
+
+ def handle_log(self, t: float, which: str, msg: capnp._DynamicStructReader):
+ if which == "carControl":
+ self.lat_active = msg.latActive
+ elif which == "carState":
+ self.steering_pressed = msg.steeringPressed
+ self.v_ego = msg.vEgo
+ elif which == "controlsState":
+ self.steering_saturated = getattr(msg.lateralControlState, msg.lateralControlState.which()).saturated
+ self.desired_curvature = msg.desiredCurvature
+ elif which == "liveCalibration":
+ self.calibrator.feed_live_calib(msg)
+ elif which == "livePose":
+ device_pose = Pose.from_live_pose(msg)
+ calibrated_pose = self.calibrator.build_calibrated_pose(device_pose)
+ self.yaw_rate = calibrated_pose.angular_velocity.yaw
+ self.yaw_rate_std = calibrated_pose.angular_velocity.yaw_std
+ self.pose_valid = msg.angularVelocityDevice.valid and msg.posenetOK and msg.inputsOK
+ self.t = t
+
+ def points_enough(self):
+ return self.points.num_points >= int(self.okay_window_sec / self.dt)
+
+ def points_valid(self):
+ return self.points.num_okay >= int(self.okay_window_sec / self.dt)
+
+ def update_points(self):
+ la_desired = self.desired_curvature * self.v_ego * self.v_ego
+ la_actual_pose = self.yaw_rate * self.v_ego
+
+ fast = self.v_ego > self.min_vego
+ turning = np.abs(self.yaw_rate) >= self.min_yr
+ sensors_valid = self.pose_valid and np.abs(self.yaw_rate) < MAX_YAW_RATE_SANITY_CHECK and self.yaw_rate_std < MAX_YAW_RATE_SANITY_CHECK
+ la_valid = np.abs(la_actual_pose) <= self.max_lat_accel and np.abs(la_desired - la_actual_pose) <= self.max_lat_accel_diff
+ calib_valid = self.calibrator.calib_valid
+
+ if not self.lat_active:
+ self.last_lat_inactive_t = self.t
+ if self.steering_pressed:
+ self.last_steering_pressed_t = self.t
+ if self.steering_saturated:
+ self.last_steering_saturated_t = self.t
+ if not sensors_valid or not la_valid:
+ self.last_pose_invalid_t = self.t
+
+ has_recovered = all( # wait for recovery after !lat_active, steering_pressed, steering_saturated, !sensors/la_valid
+ self.t - last_t >= self.min_recovery_buffer_sec
+ for last_t in [self.last_lat_inactive_t, self.last_steering_pressed_t, self.last_steering_saturated_t, self.last_pose_invalid_t]
+ )
+ okay = self.lat_active and not self.steering_pressed and not self.steering_saturated and \
+ fast and turning and has_recovered and calib_valid and sensors_valid and la_valid
+
+ self.points.update(self.t, la_desired, la_actual_pose, okay)
+
+ def update_estimate(self):
+ if not self.points_enough():
+ return
+
+ times, desired, actual, okay = self.points.get()
+ # check if there are any new valid data points since the last update
+ is_valid = self.points_valid()
+ if self.last_estimate_t != 0 and times[0] <= self.last_estimate_t:
+ new_values_start_idx = next(-i for i, t in enumerate(reversed(times)) if t <= self.last_estimate_t)
+ is_valid = is_valid and not (new_values_start_idx == 0 or not np.any(okay[new_values_start_idx:]))
+
+ delay, corr = self.actuator_delay(desired, actual, okay, self.dt, MAX_LAG)
+ if corr < self.min_ncc or not is_valid:
+ return
+
+ self.block_avg.update(delay)
+ self.last_estimate_t = self.t
+
+ def actuator_delay(self, expected_sig: np.ndarray, actual_sig: np.ndarray, mask: np.ndarray, dt: float, max_lag: float) -> tuple[float, float]:
+ assert len(expected_sig) == len(actual_sig)
+ max_lag_samples = int(max_lag / dt)
+ padded_size = fft_next_good_size(len(expected_sig) + max_lag_samples)
+
+ ncc = masked_normalized_cross_correlation(expected_sig, actual_sig, mask, padded_size)
+
+ # only consider lags from 0 to max_lag
+ roi_ncc = ncc[len(expected_sig) - 1: len(expected_sig) - 1 + max_lag_samples]
+
+ max_corr_index = np.argmax(roi_ncc)
+ corr = roi_ncc[max_corr_index]
+ lag = parabolic_peak_interp(roi_ncc, max_corr_index) * dt
+
+ return lag, corr
+
+
+def retrieve_initial_lag(params_reader: Params, CP: car.CarParams):
+ last_lag_data = params_reader.get("LiveDelay")
+ last_carparams_data = params_reader.get("CarParamsPrevRoute")
+
+ if last_lag_data is not None:
+ try:
+ with log.Event.from_bytes(last_lag_data) as last_lag_msg, car.CarParams.from_bytes(last_carparams_data) as last_CP:
+ ld = last_lag_msg.liveDelay
+ if last_CP.carFingerprint != CP.carFingerprint:
+ raise Exception("Car model mismatch")
+
+ lag, valid_blocks, status = ld.lateralDelayEstimate, ld.validBlocks, ld.status
+ assert valid_blocks <= BLOCK_NUM, "Invalid number of valid blocks"
+ assert status != log.LiveDelayData.Status.invalid, "Lag estimate is invalid"
+ return lag, valid_blocks
+ except Exception as e:
+ cloudlog.error(f"Failed to retrieve initial lag: {e}")
+
+ return None
+
+
+def main():
+ config_realtime_process([0, 1, 2, 3], 5)
+
+ DEBUG = bool(int(os.getenv("DEBUG", "0")))
+
+ pm = messaging.PubMaster(['liveDelay'])
+ sm = messaging.SubMaster(['livePose', 'liveCalibration', 'carState', 'controlsState', 'carControl'], poll='livePose')
+
+ params_reader = Params()
+ CP = messaging.log_from_bytes(params_reader.get("CarParams", block=True), car.CarParams)
+
+ lag_learner = LateralLagEstimator(CP, 1. / SERVICE_LIST['livePose'].frequency)
+ if (initial_lag_params := retrieve_initial_lag(params_reader, CP)) is not None:
+ lag, valid_blocks = initial_lag_params
+ lag_learner.reset(lag, valid_blocks)
+
+ while True:
+ sm.update()
+ if sm.all_checks():
+ for which in sorted(sm.updated.keys(), key=lambda x: sm.logMonoTime[x]):
+ if sm.updated[which]:
+ t = sm.logMonoTime[which] * 1e-9
+ lag_learner.handle_log(t, which, sm[which])
+ lag_learner.update_points()
+
+ # 4Hz driven by livePose
+ if sm.frame % 5 == 0:
+ lag_learner.update_estimate()
+ lag_msg = lag_learner.get_msg(sm.all_checks(), DEBUG)
+ lag_msg_dat = lag_msg.to_bytes()
+ pm.send('liveDelay', lag_msg_dat)
+
+ if sm.frame % 1200 == 0: # cache every 60 seconds
+ params_reader.put_nonblocking("LiveDelay", lag_msg_dat)
diff --git a/selfdrive/locationd/locationd.py b/selfdrive/locationd/locationd.py
index 80789b8886..f6a0935ed9 100755
--- a/selfdrive/locationd/locationd.py
+++ b/selfdrive/locationd/locationd.py
@@ -1,6 +1,5 @@
#!/usr/bin/env python3
import os
-import json
import time
import capnp
import numpy as np
@@ -65,7 +64,7 @@ class LocationEstimator:
self.observation_errors = {kind: np.zeros(3, dtype=np.float32) for kind in obs_kinds}
def reset(self, t: float, x_initial: np.ndarray = PoseKalman.initial_x, P_initial: np.ndarray = PoseKalman.initial_P):
- self.kf.reset(t, x_initial, P_initial)
+ self.kf.init_state(x_initial, covs=P_initial, filter_time=t)
def _validate_sensor_source(self, source: log.SensorEventData.SensorSource):
# some segments have two IMUs, ignore the second one
@@ -186,8 +185,8 @@ class LocationEstimator:
rot_device_noise = rot_device_std ** 2
trans_device_noise = trans_device_std ** 2
- cam_odo_rot_res = self.kf.predict_and_observe(t, ObservationKind.CAMERA_ODO_ROTATION, rot_device, rot_device_noise)
- cam_odo_trans_res = self.kf.predict_and_observe(t, ObservationKind.CAMERA_ODO_TRANSLATION, trans_device, trans_device_noise)
+ cam_odo_rot_res = self.kf.predict_and_observe(t, ObservationKind.CAMERA_ODO_ROTATION, rot_device, np.array([np.diag(rot_device_noise)]))
+ cam_odo_trans_res = self.kf.predict_and_observe(t, ObservationKind.CAMERA_ODO_TRANSLATION, trans_device, np.array([np.diag(trans_device_noise)]))
self.camodo_yawrate_distribution = np.array([rot_device[2], rot_device_std[2]])
if cam_odo_rot_res is not None:
_, new_x, _, new_P, _, _, (cam_odo_rot_err,), _, _ = cam_odo_rot_res
@@ -278,12 +277,13 @@ def main():
input_invalid_threshold = {s: input_invalid_limit[s] - 0.5 for s in critcal_services}
input_invalid_decay = {s: calculate_invalid_input_decay(input_invalid_limit[s], INPUT_INVALID_RECOVERY, SERVICE_LIST[s].frequency) for s in critcal_services}
- initial_pose = params.get("LocationFilterInitialState")
- if initial_pose is not None:
- initial_pose = json.loads(initial_pose)
- x_initial = np.array(initial_pose["x"], dtype=np.float64)
- P_initial = np.diag(np.array(initial_pose["P"], dtype=np.float64))
- estimator.reset(None, x_initial, P_initial)
+ initial_pose_data = params.get("LocationFilterInitialState")
+ if initial_pose_data is not None:
+ with log.Event.from_bytes(initial_pose_data) as lp_msg:
+ filter_state = lp_msg.livePose.debugFilterState
+ x_initial = np.array(filter_state.value, dtype=np.float64) if len(filter_state.value) != 0 else PoseKalman.initial_x
+ P_initial = np.diag(np.array(filter_state.std, dtype=np.float64)) if len(filter_state.std) != 0 else PoseKalman.initial_P
+ estimator.reset(None, x_initial, P_initial)
while True:
sm.update()
diff --git a/selfdrive/locationd/models/car_kf.py b/selfdrive/locationd/models/car_kf.py
index 5f40f19e46..349897f371 100755
--- a/selfdrive/locationd/models/car_kf.py
+++ b/selfdrive/locationd/models/car_kf.py
@@ -160,19 +160,18 @@ class CarKalman(KalmanFilter):
gen_code(generated_dir, name, f_sym, dt, state_sym, obs_eqs, dim_state, dim_state, global_vars=global_vars)
- def __init__(self, generated_dir, steer_ratio=15, stiffness_factor=1, angle_offset=0, P_initial=None):
- dim_state = self.initial_x.shape[0]
- dim_state_err = self.P_initial.shape[0]
- x_init = self.initial_x
- x_init[States.STEER_RATIO] = steer_ratio
- x_init[States.STIFFNESS] = stiffness_factor
- x_init[States.ANGLE_OFFSET] = angle_offset
-
- if P_initial is not None:
- self.P_initial = P_initial
- # init filter
- self.filter = EKF_sym_pyx(generated_dir, self.name, self.Q, self.initial_x, self.P_initial,
- dim_state, dim_state_err, global_vars=self.global_vars, logger=cloudlog)
+ def __init__(self, generated_dir):
+ dim_state, dim_state_err = CarKalman.initial_x.shape[0], CarKalman.P_initial.shape[0]
+ self.filter = EKF_sym_pyx(generated_dir, CarKalman.name, CarKalman.Q, CarKalman.initial_x, CarKalman.P_initial,
+ dim_state, dim_state_err, global_vars=CarKalman.global_vars, logger=cloudlog)
+
+ def set_globals(self, mass, rotational_inertia, center_to_front, center_to_rear, stiffness_front, stiffness_rear):
+ self.filter.set_global("mass", mass)
+ self.filter.set_global("rotational_inertia", rotational_inertia)
+ self.filter.set_global("center_to_front", center_to_front)
+ self.filter.set_global("center_to_rear", center_to_rear)
+ self.filter.set_global("stiffness_front", stiffness_front)
+ self.filter.set_global("stiffness_rear", stiffness_rear)
if __name__ == "__main__":
diff --git a/selfdrive/locationd/models/pose_kf.py b/selfdrive/locationd/models/pose_kf.py
index df63518441..020e51ad6e 100755
--- a/selfdrive/locationd/models/pose_kf.py
+++ b/selfdrive/locationd/models/pose_kf.py
@@ -5,6 +5,8 @@ import numpy as np
from openpilot.selfdrive.locationd.models.constants import ObservationKind
+from rednose.helpers.kalmanfilter import KalmanFilter
+
if __name__=="__main__":
import sympy as sp
from rednose.helpers.ekf_sym import gen_code
@@ -24,7 +26,7 @@ class States:
ACCEL_BIAS = slice(15, 18) # Acceletometer bias in m/s**2
-class PoseKalman:
+class PoseKalman(KalmanFilter):
name = "pose"
# state
@@ -50,10 +52,10 @@ class PoseKalman:
3**2, 3**2, 3**2,
0.005**2, 0.005**2, 0.005**2])
- obs_noise = {ObservationKind.PHONE_GYRO: np.array([0.025**2, 0.025**2, 0.025**2]),
- ObservationKind.PHONE_ACCEL: np.array([.5**2, .5**2, .5**2]),
- ObservationKind.CAMERA_ODO_TRANSLATION: np.array([0.5**2, 0.5**2, 0.5**2]),
- ObservationKind.CAMERA_ODO_ROTATION: np.array([0.05**2, 0.05**2, 0.05**2])}
+ obs_noise = {ObservationKind.PHONE_GYRO: np.diag([0.025**2, 0.025**2, 0.025**2]),
+ ObservationKind.PHONE_ACCEL: np.diag([.5**2, .5**2, .5**2]),
+ ObservationKind.CAMERA_ODO_TRANSLATION: np.diag([0.5**2, 0.5**2, 0.5**2]),
+ ObservationKind.CAMERA_ODO_ROTATION: np.diag([0.05**2, 0.05**2, 0.05**2])}
@staticmethod
def generate_code(generated_dir):
@@ -103,35 +105,6 @@ class PoseKalman:
self.filter = EKF_sym_pyx(generated_dir, self.name, PoseKalman.Q, PoseKalman.initial_x, PoseKalman.initial_P,
dim_state, dim_state_err, max_rewind_age=max_rewind_age)
- @property
- def x(self):
- return self.filter.state()
-
- @property
- def P(self):
- return self.filter.covs()
-
- @property
- def t(self):
- return self.filter.get_filter_time()
-
- def predict_and_observe(self, t, kind, data, obs_noise=None):
- data = np.atleast_2d(data)
- if obs_noise is None:
- obs_noise = self.obs_noise[kind]
- R = self._get_R(len(data), obs_noise)
- return self.filter.predict_and_update_batch(t, kind, data, R)
-
- def reset(self, t, x_init, P_init):
- self.filter.init_state(x_init, P_init, t)
-
- def _get_R(self, n, obs_noise):
- dim = obs_noise.shape[0]
- R = np.zeros((n, dim, dim))
- for i in range(n):
- R[i, :, :] = np.diag(obs_noise)
- return R
-
if __name__ == "__main__":
generated_dir = sys.argv[2]
diff --git a/selfdrive/locationd/paramsd.py b/selfdrive/locationd/paramsd.py
index 3819fba080..a7712ba1d9 100755
--- a/selfdrive/locationd/paramsd.py
+++ b/selfdrive/locationd/paramsd.py
@@ -1,8 +1,8 @@
#!/usr/bin/env python3
import os
-import math
import json
import numpy as np
+import capnp
import cereal.messaging as messaging
from cereal import car, log
@@ -13,12 +13,11 @@ from openpilot.selfdrive.locationd.models.constants import GENERATED_DIR
from openpilot.selfdrive.locationd.helpers import PoseCalibrator, Pose
from openpilot.common.swaglog import cloudlog
-
MAX_ANGLE_OFFSET_DELTA = 20 * DT_MDL # Max 20 deg/s
-ROLL_MAX_DELTA = math.radians(20.0) * DT_MDL # 20deg in 1 second is well within curvature limits
-ROLL_MIN, ROLL_MAX = math.radians(-10), math.radians(10)
-ROLL_LOWERED_MAX = math.radians(8)
-ROLL_STD_MAX = math.radians(1.5)
+ROLL_MAX_DELTA = np.radians(20.0) * DT_MDL # 20deg in 1 second is well within curvature limits
+ROLL_MIN, ROLL_MAX = np.radians(-10), np.radians(10)
+ROLL_LOWERED_MAX = np.radians(8)
+ROLL_STD_MAX = np.radians(1.5)
LATERAL_ACC_SENSOR_THRESHOLD = 4.0
OFFSET_MAX = 10.0
OFFSET_LOWERED_MAX = 8.0
@@ -26,40 +25,58 @@ MIN_ACTIVE_SPEED = 1.0
LOW_ACTIVE_SPEED = 10.0
-class ParamsLearner:
- def __init__(self, CP, steer_ratio, stiffness_factor, angle_offset, P_initial=None):
- self.kf = CarKalman(GENERATED_DIR, steer_ratio, stiffness_factor, angle_offset, P_initial)
+class VehicleParamsLearner:
+ def __init__(self, CP: car.CarParams, steer_ratio: float, stiffness_factor: float, angle_offset: float, P_initial: np.ndarray | None = None):
+ self.kf = CarKalman(GENERATED_DIR)
+
+ self.x_initial = CarKalman.initial_x.copy()
+ self.x_initial[States.STEER_RATIO] = steer_ratio
+ self.x_initial[States.STIFFNESS] = stiffness_factor
+ self.x_initial[States.ANGLE_OFFSET] = angle_offset
+ self.P_initial = P_initial if P_initial is not None else CarKalman.P_initial
- self.kf.filter.set_global("mass", CP.mass)
- self.kf.filter.set_global("rotational_inertia", CP.rotationalInertia)
- self.kf.filter.set_global("center_to_front", CP.centerToFront)
- self.kf.filter.set_global("center_to_rear", CP.wheelbase - CP.centerToFront)
- self.kf.filter.set_global("stiffness_front", CP.tireStiffnessFront)
- self.kf.filter.set_global("stiffness_rear", CP.tireStiffnessRear)
+ self.kf.set_globals(
+ mass=CP.mass,
+ rotational_inertia=CP.rotationalInertia,
+ center_to_front=CP.centerToFront,
+ center_to_rear=CP.wheelbase - CP.centerToFront,
+ stiffness_front=CP.tireStiffnessFront,
+ stiffness_rear=CP.tireStiffnessRear
+ )
- self.active = False
+ self.min_sr, self.max_sr = 0.5 * CP.steerRatio, 2.0 * CP.steerRatio
self.calibrator = PoseCalibrator()
- self.speed = 0.0
- self.yaw_rate = 0.0
- self.yaw_rate_std = 0.0
- self.roll = 0.0
- self.steering_angle = 0.0
+ self.observed_speed = 0.0
+ self.observed_yaw_rate = 0.0
+ self.observed_roll = 0.0
+
+ self.avg_offset_valid = True
+ self.total_offset_valid = True
+ self.roll_valid = True
+
+ self.reset(None)
- def handle_log(self, t, which, msg):
+ def reset(self, t: float | None):
+ self.kf.init_state(self.x_initial, covs=self.P_initial, filter_time=t)
+
+ self.angle_offset, self.roll, self.active = np.degrees(self.x_initial[States.ANGLE_OFFSET].item()), 0.0, False
+ self.avg_angle_offset = self.angle_offset
+
+ def handle_log(self, t: float, which: str, msg: capnp._DynamicStructReader):
if which == 'livePose':
device_pose = Pose.from_live_pose(msg)
calibrated_pose = self.calibrator.build_calibrated_pose(device_pose)
+ yaw_rate, yaw_rate_std = calibrated_pose.angular_velocity.z, calibrated_pose.angular_velocity.z_std
yaw_rate_valid = msg.angularVelocityDevice.valid
- yaw_rate_valid = yaw_rate_valid and 0 < self.yaw_rate_std < 10 # rad/s
- yaw_rate_valid = yaw_rate_valid and abs(self.yaw_rate) < 1 # rad/s
- if yaw_rate_valid:
- self.yaw_rate, self.yaw_rate_std = calibrated_pose.angular_velocity.z, calibrated_pose.angular_velocity.z_std
- else:
+ yaw_rate_valid = yaw_rate_valid and 0 < yaw_rate_std < 10 # rad/s
+ yaw_rate_valid = yaw_rate_valid and abs(yaw_rate) < 1 # rad/s
+ if not yaw_rate_valid:
# This is done to bound the yaw rate estimate when localizer values are invalid or calibrating
- self.yaw_rate, self.yaw_rate_std = 0.0, np.radians(10.0)
+ yaw_rate, yaw_rate_std = 0.0, np.radians(10.0)
+ self.observed_yaw_rate = yaw_rate
localizer_roll, localizer_roll_std = device_pose.orientation.x, device_pose.orientation.x_std
localizer_roll_std = np.radians(1) if np.isnan(localizer_roll_std) else localizer_roll_std
@@ -72,18 +89,18 @@ class ParamsLearner:
# This is done to bound the road roll estimate when localizer values are invalid
roll = 0.0
roll_std = np.radians(10.0)
- self.roll = np.clip(roll, self.roll - ROLL_MAX_DELTA, self.roll + ROLL_MAX_DELTA)
+ self.observed_roll = np.clip(roll, self.observed_roll - ROLL_MAX_DELTA, self.observed_roll + ROLL_MAX_DELTA)
if self.active:
if msg.posenetOK:
self.kf.predict_and_observe(t,
ObservationKind.ROAD_FRAME_YAW_RATE,
- np.array([[-self.yaw_rate]]),
- np.array([np.atleast_2d(self.yaw_rate_std**2)]))
+ np.array([[-self.observed_yaw_rate]]),
+ np.array([np.atleast_2d(yaw_rate_std**2)]))
self.kf.predict_and_observe(t,
ObservationKind.ROAD_ROLL,
- np.array([[self.roll]]),
+ np.array([[self.observed_roll]]),
np.array([np.atleast_2d(roll_std**2)]))
self.kf.predict_and_observe(t, ObservationKind.ANGLE_OFFSET_FAST, np.array([[0]]))
@@ -99,20 +116,79 @@ class ParamsLearner:
self.calibrator.feed_live_calib(msg)
elif which == 'carState':
- self.steering_angle = msg.steeringAngleDeg
- self.speed = msg.vEgo
+ steering_angle = msg.steeringAngleDeg
- in_linear_region = abs(self.steering_angle) < 45
- self.active = self.speed > MIN_ACTIVE_SPEED and in_linear_region
+ in_linear_region = abs(steering_angle) < 45
+ self.observed_speed = msg.vEgo
+ self.active = self.observed_speed > MIN_ACTIVE_SPEED and in_linear_region
if self.active:
- self.kf.predict_and_observe(t, ObservationKind.STEER_ANGLE, np.array([[math.radians(msg.steeringAngleDeg)]]))
- self.kf.predict_and_observe(t, ObservationKind.ROAD_FRAME_X_SPEED, np.array([[self.speed]]))
+ self.kf.predict_and_observe(t, ObservationKind.STEER_ANGLE, np.array([[np.radians(steering_angle)]]))
+ self.kf.predict_and_observe(t, ObservationKind.ROAD_FRAME_X_SPEED, np.array([[self.observed_speed]]))
if not self.active:
# Reset time when stopped so uncertainty doesn't grow
- self.kf.filter.set_filter_time(t)
- self.kf.filter.reset_rewind()
+ self.kf.filter.set_filter_time(t) # type: ignore
+ self.kf.filter.reset_rewind() # type: ignore
+
+ def get_msg(self, valid: bool, debug: bool = False) -> capnp._DynamicStructBuilder:
+ x = self.kf.x
+ P = np.sqrt(self.kf.P.diagonal())
+ if not np.all(np.isfinite(x)):
+ cloudlog.error("NaN in liveParameters estimate. Resetting to default values")
+ self.reset(self.kf.t)
+ x = self.kf.x
+
+ self.avg_angle_offset = np.clip(np.degrees(x[States.ANGLE_OFFSET].item()),
+ self.avg_angle_offset - MAX_ANGLE_OFFSET_DELTA, self.avg_angle_offset + MAX_ANGLE_OFFSET_DELTA)
+ self.angle_offset = np.clip(np.degrees(x[States.ANGLE_OFFSET].item() + x[States.ANGLE_OFFSET_FAST].item()),
+ self.angle_offset - MAX_ANGLE_OFFSET_DELTA, self.angle_offset + MAX_ANGLE_OFFSET_DELTA)
+ self.roll = np.clip(float(x[States.ROAD_ROLL].item()), self.roll - ROLL_MAX_DELTA, self.roll + ROLL_MAX_DELTA)
+ roll_std = float(P[States.ROAD_ROLL].item())
+ if self.active and self.observed_speed > LOW_ACTIVE_SPEED:
+ # Account for the opposite signs of the yaw rates
+ # At low speeds, bumping into a curb can cause the yaw rate to be very high
+ sensors_valid = bool(abs(self.observed_speed * (x[States.YAW_RATE].item() + self.observed_yaw_rate)) < LATERAL_ACC_SENSOR_THRESHOLD)
+ else:
+ sensors_valid = True
+ self.avg_offset_valid = check_valid_with_hysteresis(self.avg_offset_valid, self.avg_angle_offset, OFFSET_MAX, OFFSET_LOWERED_MAX)
+ self.total_offset_valid = check_valid_with_hysteresis(self.total_offset_valid, self.angle_offset, OFFSET_MAX, OFFSET_LOWERED_MAX)
+ self.roll_valid = check_valid_with_hysteresis(self.roll_valid, self.roll, ROLL_MAX, ROLL_LOWERED_MAX)
+
+ msg = messaging.new_message('liveParameters')
+
+ msg.valid = valid
+
+ liveParameters = msg.liveParameters
+ liveParameters.posenetValid = True
+ liveParameters.sensorValid = sensors_valid
+ liveParameters.steerRatio = float(x[States.STEER_RATIO].item())
+ liveParameters.stiffnessFactor = float(x[States.STIFFNESS].item())
+ liveParameters.roll = float(self.roll)
+ liveParameters.angleOffsetAverageDeg = float(self.avg_angle_offset)
+ liveParameters.angleOffsetDeg = float(self.angle_offset)
+ liveParameters.steerRatioValid = self.min_sr <= liveParameters.steerRatio <= self.max_sr
+ liveParameters.stiffnessFactorValid = 0.2 <= liveParameters.stiffnessFactor <= 5.0
+ liveParameters.angleOffsetAverageValid = bool(self.avg_offset_valid)
+ liveParameters.angleOffsetValid = bool(self.total_offset_valid)
+ liveParameters.valid = all((
+ liveParameters.angleOffsetAverageValid,
+ liveParameters.angleOffsetValid ,
+ self.roll_valid,
+ roll_std < ROLL_STD_MAX,
+ liveParameters.stiffnessFactorValid,
+ liveParameters.steerRatioValid,
+ ))
+ liveParameters.steerRatioStd = float(P[States.STEER_RATIO].item())
+ liveParameters.stiffnessFactorStd = float(P[States.STIFFNESS].item())
+ liveParameters.angleOffsetAverageStd = float(P[States.ANGLE_OFFSET].item())
+ liveParameters.angleOffsetFastStd = float(P[States.ANGLE_OFFSET_FAST].item())
+ if debug:
+ liveParameters.debugFilterState = log.LiveParametersData.FilterState.new_message()
+ liveParameters.debugFilterState.value = x.tolist()
+ liveParameters.debugFilterState.std = P.tolist()
+
+ return msg
def check_valid_with_hysteresis(current_valid: bool, val: float, threshold: float, lowered_threshold: float):
@@ -123,69 +199,83 @@ def check_valid_with_hysteresis(current_valid: bool, val: float, threshold: floa
return current_valid
-def main():
- config_realtime_process([0, 1, 2, 3], 5)
-
- DEBUG = bool(int(os.getenv("DEBUG", "0")))
- REPLAY = bool(int(os.getenv("REPLAY", "0")))
-
- pm = messaging.PubMaster(['liveParameters'])
- sm = messaging.SubMaster(['livePose', 'liveCalibration', 'carState'], poll='livePose')
+# TODO: Remove this function after few releases (added in 0.9.9)
+def migrate_cached_vehicle_params_if_needed(params: Params):
+ last_parameters_data_old = params.get("LiveParameters")
+ last_parameters_data = params.get("LiveParametersV2")
+ if last_parameters_data_old is None or last_parameters_data is not None:
+ return
- params_reader = Params()
- # wait for stats about the car to come in from controls
- cloudlog.info("paramsd is waiting for CarParams")
- CP = messaging.log_from_bytes(params_reader.get("CarParams", block=True), car.CarParams)
- cloudlog.info("paramsd got CarParams")
+ try:
+ last_parameters_dict = json.loads(last_parameters_data_old)
+ last_parameters_msg = messaging.new_message('liveParameters')
+ last_parameters_msg.liveParameters.valid = True
+ last_parameters_msg.liveParameters.steerRatio = last_parameters_dict['steerRatio']
+ last_parameters_msg.liveParameters.stiffnessFactor = last_parameters_dict['stiffnessFactor']
+ last_parameters_msg.liveParameters.angleOffsetAverageDeg = last_parameters_dict['angleOffsetAverageDeg']
+ params.put("LiveParametersV2", last_parameters_msg.to_bytes())
+ except Exception as e:
+ cloudlog.error(f"Failed to perform parameter migration: {e}")
+ params.remove("LiveParameters")
- min_sr, max_sr = 0.5 * CP.steerRatio, 2.0 * CP.steerRatio
- params = params_reader.get("LiveParameters")
+def retrieve_initial_vehicle_params(params: Params, CP: car.CarParams, replay: bool, debug: bool):
+ last_parameters_data = params.get("LiveParametersV2")
+ last_carparams_data = params.get("CarParamsPrevRoute")
- # Check if car model matches
- if params is not None:
- params = json.loads(params)
- if params.get('carFingerprint', None) != CP.carFingerprint:
- cloudlog.info("Parameter learner found parameters for wrong car.")
- params = None
+ steer_ratio, stiffness_factor, angle_offset_deg, p_initial = CP.steerRatio, 1.0, 0.0, None
- # Check if starting values are sane
- if params is not None:
+ retrieve_success = False
+ if last_parameters_data is not None and last_carparams_data is not None:
try:
- steer_ratio_sane = min_sr <= params['steerRatio'] <= max_sr
- if not steer_ratio_sane:
- cloudlog.info(f"Invalid starting values found {params}")
- params = None
+ with log.Event.from_bytes(last_parameters_data) as last_lp_msg, car.CarParams.from_bytes(last_carparams_data) as last_CP:
+ lp = last_lp_msg.liveParameters
+ # Check if car model matches
+ if last_CP.carFingerprint != CP.carFingerprint:
+ raise Exception("Car model mismatch")
+
+ # Check if starting values are sane
+ min_sr, max_sr = 0.5 * CP.steerRatio, 2.0 * CP.steerRatio
+ steer_ratio_sane = min_sr <= lp.steerRatio <= max_sr
+ if not steer_ratio_sane:
+ raise Exception(f"Invalid starting values found {lp}")
+
+ initial_filter_std = np.array(lp.debugFilterState.std)
+ if debug and len(initial_filter_std) != 0:
+ p_initial = np.diag(initial_filter_std)
+
+ steer_ratio, stiffness_factor, angle_offset_deg = lp.steerRatio, lp.stiffnessFactor, lp.angleOffsetAverageDeg
+ retrieve_success = True
except Exception as e:
- cloudlog.info(f"Error reading params {params}: {str(e)}")
- params = None
-
- # TODO: cache the params with the capnp struct
- if params is None:
- params = {
- 'carFingerprint': CP.carFingerprint,
- 'steerRatio': CP.steerRatio,
- 'stiffnessFactor': 1.0,
- 'angleOffsetAverageDeg': 0.0,
- }
- cloudlog.info("Parameter learner resetting to default values")
+ cloudlog.error(f"Failed to retrieve initial values: {e}")
- if not REPLAY:
+ if not replay:
# When driving in wet conditions the stiffness can go down, and then be too low on the next drive
# Without a way to detect this we have to reset the stiffness every drive
- params['stiffnessFactor'] = 1.0
+ stiffness_factor = 1.0
- pInitial = None
- if DEBUG:
- pInitial = np.array(params['debugFilterState']['std']) if 'debugFilterState' in params else None
+ if not retrieve_success:
+ cloudlog.info("Parameter learner resetting to default values")
+
+ return steer_ratio, stiffness_factor, angle_offset_deg, p_initial
+
+
+def main():
+ config_realtime_process([0, 1, 2, 3], 5)
+
+ DEBUG = bool(int(os.getenv("DEBUG", "0")))
+ REPLAY = bool(int(os.getenv("REPLAY", "0")))
+
+ pm = messaging.PubMaster(['liveParameters'])
+ sm = messaging.SubMaster(['livePose', 'liveCalibration', 'carState'], poll='livePose')
- learner = ParamsLearner(CP, params['steerRatio'], params['stiffnessFactor'], math.radians(params['angleOffsetAverageDeg']), pInitial)
- angle_offset_average = params['angleOffsetAverageDeg']
- angle_offset = angle_offset_average
- roll = 0.0
- avg_offset_valid = True
- total_offset_valid = True
- roll_valid = True
+ params = Params()
+ CP = messaging.log_from_bytes(params.get("CarParams", block=True), car.CarParams)
+
+ migrate_cached_vehicle_params_if_needed(params)
+
+ steer_ratio, stiffness_factor, angle_offset_deg, pInitial = retrieve_initial_vehicle_params(params, CP, REPLAY, DEBUG)
+ learner = VehicleParamsLearner(CP, steer_ratio, stiffness_factor, np.radians(angle_offset_deg), pInitial)
while True:
sm.update()
@@ -196,72 +286,13 @@ def main():
learner.handle_log(t, which, sm[which])
if sm.updated['livePose']:
- x = learner.kf.x
- P = np.sqrt(learner.kf.P.diagonal())
- if not all(map(math.isfinite, x)):
- cloudlog.error("NaN in liveParameters estimate. Resetting to default values")
- learner = ParamsLearner(CP, CP.steerRatio, 1.0, 0.0)
- x = learner.kf.x
-
- angle_offset_average = np.clip(math.degrees(x[States.ANGLE_OFFSET].item()),
- angle_offset_average - MAX_ANGLE_OFFSET_DELTA, angle_offset_average + MAX_ANGLE_OFFSET_DELTA)
- angle_offset = np.clip(math.degrees(x[States.ANGLE_OFFSET].item() + x[States.ANGLE_OFFSET_FAST].item()),
- angle_offset - MAX_ANGLE_OFFSET_DELTA, angle_offset + MAX_ANGLE_OFFSET_DELTA)
- roll = np.clip(float(x[States.ROAD_ROLL].item()), roll - ROLL_MAX_DELTA, roll + ROLL_MAX_DELTA)
- roll_std = float(P[States.ROAD_ROLL].item())
- if learner.active and learner.speed > LOW_ACTIVE_SPEED:
- # Account for the opposite signs of the yaw rates
- # At low speeds, bumping into a curb can cause the yaw rate to be very high
- sensors_valid = bool(abs(learner.speed * (x[States.YAW_RATE].item() + learner.yaw_rate)) < LATERAL_ACC_SENSOR_THRESHOLD)
- else:
- sensors_valid = True
- avg_offset_valid = check_valid_with_hysteresis(avg_offset_valid, angle_offset_average, OFFSET_MAX, OFFSET_LOWERED_MAX)
- total_offset_valid = check_valid_with_hysteresis(total_offset_valid, angle_offset, OFFSET_MAX, OFFSET_LOWERED_MAX)
- roll_valid = check_valid_with_hysteresis(roll_valid, roll, ROLL_MAX, ROLL_LOWERED_MAX)
-
- msg = messaging.new_message('liveParameters')
-
- liveParameters = msg.liveParameters
- liveParameters.posenetValid = True
- liveParameters.sensorValid = sensors_valid
- liveParameters.steerRatio = float(x[States.STEER_RATIO].item())
- liveParameters.stiffnessFactor = float(x[States.STIFFNESS].item())
- liveParameters.roll = float(roll)
- liveParameters.angleOffsetAverageDeg = float(angle_offset_average)
- liveParameters.angleOffsetDeg = float(angle_offset)
- liveParameters.steerRatioValid = min_sr <= liveParameters.steerRatio <= max_sr
- liveParameters.stiffnessFactorValid = 0.2 <= liveParameters.stiffnessFactor <= 5.0
- liveParameters.angleOffsetAverageValid = bool(avg_offset_valid)
- liveParameters.angleOffsetValid = bool(total_offset_valid)
- liveParameters.valid = all((
- liveParameters.angleOffsetAverageValid,
- liveParameters.angleOffsetValid ,
- roll_valid,
- roll_std < ROLL_STD_MAX,
- liveParameters.stiffnessFactorValid,
- liveParameters.steerRatioValid,
- ))
- liveParameters.steerRatioStd = float(P[States.STEER_RATIO].item())
- liveParameters.stiffnessFactorStd = float(P[States.STIFFNESS].item())
- liveParameters.angleOffsetAverageStd = float(P[States.ANGLE_OFFSET].item())
- liveParameters.angleOffsetFastStd = float(P[States.ANGLE_OFFSET_FAST].item())
- if DEBUG:
- liveParameters.debugFilterState = log.LiveParametersData.FilterState.new_message()
- liveParameters.debugFilterState.value = x.tolist()
- liveParameters.debugFilterState.std = P.tolist()
-
- msg.valid = sm.all_checks()
+ msg = learner.get_msg(sm.all_checks(), debug=DEBUG)
+ msg_dat = msg.to_bytes()
if sm.frame % 1200 == 0: # once a minute
- params = {
- 'carFingerprint': CP.carFingerprint,
- 'steerRatio': liveParameters.steerRatio,
- 'stiffnessFactor': liveParameters.stiffnessFactor,
- 'angleOffsetAverageDeg': liveParameters.angleOffsetAverageDeg,
- }
- params_reader.put_nonblocking("LiveParameters", json.dumps(params))
-
- pm.send('liveParameters', msg)
+ params.put_nonblocking("LiveParametersV2", msg_dat)
+
+ pm.send('liveParameters', msg_dat)
if __name__ == "__main__":
diff --git a/selfdrive/locationd/test/test_lagd.py b/selfdrive/locationd/test/test_lagd.py
new file mode 100644
index 0000000000..13aea60a26
--- /dev/null
+++ b/selfdrive/locationd/test/test_lagd.py
@@ -0,0 +1,141 @@
+import random
+import numpy as np
+import time
+import pytest
+
+from cereal import messaging, log
+from openpilot.selfdrive.locationd.lagd import LateralLagEstimator, retrieve_initial_lag, masked_normalized_cross_correlation, \
+ BLOCK_NUM_NEEDED, BLOCK_SIZE, MIN_OKAY_WINDOW_SEC
+from openpilot.selfdrive.test.process_replay.migration import migrate, migrate_carParams
+from openpilot.selfdrive.locationd.test.test_locationd_scenarios import TEST_ROUTE
+from openpilot.common.params import Params
+from openpilot.tools.lib.logreader import LogReader
+from openpilot.system.hardware import PC
+
+MAX_ERR_FRAMES = 1
+DT = 0.05
+
+
+def process_messages(mocker, estimator, lag_frames, n_frames, vego=20.0, rejection_threshold=0.0):
+ class ZeroMock(mocker.Mock):
+ def __getattr__(self, *args):
+ return 0
+
+ for i in range(n_frames):
+ t = i * estimator.dt
+ desired_la = np.cos(t) * 0.1
+ actual_la = np.cos(t - lag_frames * estimator.dt) * 0.1
+
+ # if sample is masked out, set it to desired value (no lag)
+ rejected = random.uniform(0, 1) < rejection_threshold
+ if rejected:
+ actual_la = desired_la
+
+ desired_cuvature = desired_la / (vego ** 2)
+ actual_yr = actual_la / vego
+ msgs = [
+ (t, "carControl", mocker.Mock(latActive=not rejected)),
+ (t, "carState", mocker.Mock(vEgo=vego, steeringPressed=False)),
+ (t, "controlsState", mocker.Mock(desiredCurvature=desired_cuvature,
+ lateralControlState=mocker.Mock(which=mocker.Mock(return_value='debugControlState'), debugControlState=ZeroMock()))),
+ (t, "livePose", mocker.Mock(orientationNED=ZeroMock(),
+ velocityDevice=ZeroMock(),
+ accelerationDevice=ZeroMock(),
+ angularVelocityDevice=ZeroMock(z=actual_yr, valid=True),
+ posenetOK=True, inputsOK=True)),
+ (t, "liveCalibration", mocker.Mock(rpyCalib=[0, 0, 0], calStatus=log.LiveCalibrationData.Status.calibrated)),
+ ]
+ for t, w, m in msgs:
+ estimator.handle_log(t, w, m)
+ estimator.update_points()
+ estimator.update_estimate()
+
+
+class TestLagd:
+ def test_read_saved_params(self):
+ params = Params()
+
+ lr = migrate(LogReader(TEST_ROUTE), [migrate_carParams])
+ CP = next(m for m in lr if m.which() == "carParams").carParams
+
+ msg = messaging.new_message('liveDelay')
+ msg.liveDelay.lateralDelayEstimate = random.random()
+ msg.liveDelay.validBlocks = random.randint(1, 10)
+ params.put("LiveDelay", msg.to_bytes())
+ params.put("CarParamsPrevRoute", CP.as_builder().to_bytes())
+
+ saved_lag_params = retrieve_initial_lag(params, CP)
+ assert saved_lag_params is not None
+
+ lag, valid_blocks = saved_lag_params
+ assert lag == msg.liveDelay.lateralDelayEstimate
+ assert valid_blocks == msg.liveDelay.validBlocks
+
+ def test_ncc(self):
+ lag_frames = random.randint(1, 19)
+
+ desired_sig = np.sin(np.arange(0.0, 10.0, 0.1))
+ actual_sig = np.sin(np.arange(0.0, 10.0, 0.1) - lag_frames * 0.1)
+ mask = np.ones(len(desired_sig), dtype=bool)
+
+ corr = masked_normalized_cross_correlation(desired_sig, actual_sig, mask, 200)[len(desired_sig) - 1:len(desired_sig) + 20]
+ assert np.argmax(corr) == lag_frames
+
+ # add some noise
+ desired_sig += np.random.normal(0, 0.05, len(desired_sig))
+ actual_sig += np.random.normal(0, 0.05, len(actual_sig))
+ corr = masked_normalized_cross_correlation(desired_sig, actual_sig, mask, 200)[len(desired_sig) - 1:len(desired_sig) + 20]
+ assert np.argmax(corr) in range(lag_frames - MAX_ERR_FRAMES, lag_frames + MAX_ERR_FRAMES + 1)
+
+ # mask out 40% of the values, and make them noise
+ mask = np.random.choice([True, False], size=len(desired_sig), p=[0.6, 0.4])
+ desired_sig[~mask] = np.random.normal(0, 1, size=np.sum(~mask))
+ actual_sig[~mask] = np.random.normal(0, 1, size=np.sum(~mask))
+ corr = masked_normalized_cross_correlation(desired_sig, actual_sig, mask, 200)[len(desired_sig) - 1:len(desired_sig) + 20]
+ assert np.argmax(corr) in range(lag_frames - MAX_ERR_FRAMES, lag_frames + MAX_ERR_FRAMES + 1)
+
+ def test_empty_estimator(self, mocker):
+ mocked_CP = mocker.Mock(steerActuatorDelay=0.8)
+ estimator = LateralLagEstimator(mocked_CP, DT)
+ msg = estimator.get_msg(True)
+ assert msg.liveDelay.status == 'unestimated'
+ assert np.allclose(msg.liveDelay.lateralDelay, estimator.initial_lag)
+ assert np.allclose(msg.liveDelay.lateralDelayEstimate, estimator.initial_lag)
+ assert msg.liveDelay.validBlocks == 0
+
+ def test_estimator_basics(self, mocker, subtests):
+ for lag_frames in range(5):
+ with subtests.test(msg=f"lag_frames={lag_frames}"):
+ mocked_CP = mocker.Mock(steerActuatorDelay=0.8)
+ estimator = LateralLagEstimator(mocked_CP, DT, min_recovery_buffer_sec=0.0, min_yr=0.0)
+ process_messages(mocker, estimator, lag_frames, int(MIN_OKAY_WINDOW_SEC / DT) + BLOCK_NUM_NEEDED * BLOCK_SIZE)
+ msg = estimator.get_msg(True)
+ assert msg.liveDelay.status == 'estimated'
+ assert np.allclose(msg.liveDelay.lateralDelay, lag_frames * DT, atol=0.01)
+ assert np.allclose(msg.liveDelay.lateralDelayEstimate, lag_frames * DT, atol=0.01)
+ assert np.allclose(msg.liveDelay.lateralDelayEstimateStd, 0.0, atol=0.01)
+ assert msg.liveDelay.validBlocks == BLOCK_NUM_NEEDED
+
+ def test_estimator_masking(self, mocker):
+ mocked_CP, lag_frames = mocker.Mock(steerActuatorDelay=0.8), random.randint(1, 19)
+ estimator = LateralLagEstimator(mocked_CP, DT, min_recovery_buffer_sec=0.0, min_yr=0.0, min_valid_block_count=1)
+ process_messages(mocker, estimator, lag_frames, (int(MIN_OKAY_WINDOW_SEC / DT) + BLOCK_SIZE) * 2, rejection_threshold=0.4)
+ msg = estimator.get_msg(True)
+ assert np.allclose(msg.liveDelay.lateralDelayEstimate, lag_frames * DT, atol=0.01)
+ assert np.allclose(msg.liveDelay.lateralDelayEstimateStd, 0.0, atol=0.01)
+
+ @pytest.mark.skipif(PC, reason="only on device")
+ @pytest.mark.timeout(60)
+ def test_estimator_performance(self, mocker):
+ mocked_CP = mocker.Mock(steerActuatorDelay=0.8)
+ estimator = LateralLagEstimator(mocked_CP, DT)
+
+ ds = []
+ for _ in range(1000):
+ st = time.perf_counter()
+ estimator.update_points()
+ estimator.update_estimate()
+ d = time.perf_counter() - st
+ ds.append(d)
+
+ assert np.mean(ds) < DT
diff --git a/selfdrive/locationd/test/test_paramsd.py b/selfdrive/locationd/test/test_paramsd.py
new file mode 100644
index 0000000000..2129bf4386
--- /dev/null
+++ b/selfdrive/locationd/test/test_paramsd.py
@@ -0,0 +1,68 @@
+import random
+import numpy as np
+import json
+
+from cereal import messaging
+from openpilot.selfdrive.locationd.paramsd import retrieve_initial_vehicle_params, migrate_cached_vehicle_params_if_needed
+from openpilot.selfdrive.locationd.models.car_kf import CarKalman
+from openpilot.selfdrive.locationd.test.test_locationd_scenarios import TEST_ROUTE
+from openpilot.selfdrive.test.process_replay.migration import migrate, migrate_carParams
+from openpilot.common.params import Params
+from openpilot.tools.lib.logreader import LogReader
+
+
+def get_random_live_parameters(CP):
+ msg = messaging.new_message("liveParameters")
+ msg.liveParameters.steerRatio = (random.random() + 0.5) * CP.steerRatio
+ msg.liveParameters.stiffnessFactor = random.random()
+ msg.liveParameters.angleOffsetAverageDeg = random.random()
+ msg.liveParameters.debugFilterState.std = [random.random() for _ in range(CarKalman.P_initial.shape[0])]
+ return msg
+
+
+class TestParamsd:
+ def test_read_saved_params(self):
+ params = Params()
+
+ lr = migrate(LogReader(TEST_ROUTE), [migrate_carParams])
+ CP = next(m for m in lr if m.which() == "carParams").carParams
+
+ msg = get_random_live_parameters(CP)
+ params.put("LiveParametersV2", msg.to_bytes())
+ params.put("CarParamsPrevRoute", CP.as_builder().to_bytes())
+
+ migrate_cached_vehicle_params_if_needed(params) # this is not tested here but should not mess anything up or throw an error
+ sr, sf, offset, p_init = retrieve_initial_vehicle_params(params, CP, replay=True, debug=True)
+ np.testing.assert_allclose(sr, msg.liveParameters.steerRatio)
+ np.testing.assert_allclose(sf, msg.liveParameters.stiffnessFactor)
+ np.testing.assert_allclose(offset, msg.liveParameters.angleOffsetAverageDeg)
+ np.testing.assert_equal(p_init.shape, CarKalman.P_initial.shape)
+ np.testing.assert_allclose(np.diagonal(p_init), msg.liveParameters.debugFilterState.std)
+
+ # TODO Remove this test after the support for old format is removed
+ def test_read_saved_params_old_format(self):
+ params = Params()
+
+ lr = migrate(LogReader(TEST_ROUTE), [migrate_carParams])
+ CP = next(m for m in lr if m.which() == "carParams").carParams
+
+ msg = get_random_live_parameters(CP)
+ params.put("LiveParameters", json.dumps(msg.liveParameters.to_dict()))
+ params.put("CarParamsPrevRoute", CP.as_builder().to_bytes())
+ params.remove("LiveParametersV2")
+
+ migrate_cached_vehicle_params_if_needed(params)
+ sr, sf, offset, _ = retrieve_initial_vehicle_params(params, CP, replay=True, debug=True)
+ np.testing.assert_allclose(sr, msg.liveParameters.steerRatio)
+ np.testing.assert_allclose(sf, msg.liveParameters.stiffnessFactor)
+ np.testing.assert_allclose(offset, msg.liveParameters.angleOffsetAverageDeg)
+ assert params.get("LiveParametersV2") is not None
+
+ def test_read_saved_params_corrupted_old_format(self):
+ params = Params()
+ params.put("LiveParameters", b'\x00\x00\x02\x00\x01\x00:F\xde\xed\xae;')
+ params.remove("LiveParametersV2")
+
+ migrate_cached_vehicle_params_if_needed(params)
+ assert params.get("LiveParameters") is None
+ assert params.get("LiveParametersV2") is None
diff --git a/selfdrive/locationd/torqued.py b/selfdrive/locationd/torqued.py
index 590b6cc6f7..fcaa19df73 100755
--- a/selfdrive/locationd/torqued.py
+++ b/selfdrive/locationd/torqued.py
@@ -32,7 +32,7 @@ MIN_BUCKET_POINTS = np.array([100, 300, 500, 500, 500, 500, 300, 100])
MIN_ENGAGE_BUFFER = 2 # secs
VERSION = 1 # bump this to invalidate old parameter caches
-ALLOWED_CARS = ['toyota', 'hyundai']
+ALLOWED_CARS = ['toyota', 'hyundai', 'rivian']
def slope2rot(slope):
diff --git a/selfdrive/modeld/dmonitoringmodeld.py b/selfdrive/modeld/dmonitoringmodeld.py
index 9ebdea4c75..94e117bc6a 100755
--- a/selfdrive/modeld/dmonitoringmodeld.py
+++ b/selfdrive/modeld/dmonitoringmodeld.py
@@ -134,7 +134,7 @@ def get_driverstate_packet(model_output: np.ndarray, frame_id: int, location_ts:
def main():
setproctitle(PROCESS_NAME)
- config_realtime_process([0, 1, 2, 3], 5)
+ config_realtime_process(7, 5)
sentry.set_tag("daemon", PROCESS_NAME)
cloudlog.bind(daemon=PROCESS_NAME)
@@ -173,6 +173,9 @@ def main():
model_output, gpu_execution_time = model.run(buf, calib, model_transform)
t2 = time.perf_counter()
+ # run one more time, just for the load
+ model.run(buf, calib, model_transform)
+
pm.send("driverStateV2", get_driverstate_packet(model_output, vipc_client.frame_id, vipc_client.timestamp_sof, t2 - t1, gpu_execution_time))
diff --git a/selfdrive/modeld/fill_model_msg.py b/selfdrive/modeld/fill_model_msg.py
index 0ea88f9bc1..36bd724d01 100644
--- a/selfdrive/modeld/fill_model_msg.py
+++ b/selfdrive/modeld/fill_model_msg.py
@@ -56,7 +56,7 @@ def fill_lane_line_meta(builder, lane_lines, lane_line_probs):
builder.rightProb = lane_line_probs[2]
def fill_model_msg(base_msg: capnp._DynamicStructBuilder, extended_msg: capnp._DynamicStructBuilder,
- net_output_data: dict[str, np.ndarray], v_ego: float, delay: float,
+ net_output_data: dict[str, np.ndarray], action: log.ModelDataV2.Action,
publish_state: PublishState, vipc_frame_id: int, vipc_frame_id_extra: int,
frame_id: int, frame_drop: float, timestamp_eof: int, model_execution_time: float,
valid: bool) -> None:
@@ -71,7 +71,8 @@ def fill_model_msg(base_msg: capnp._DynamicStructBuilder, extended_msg: capnp._D
driving_model_data.frameIdExtra = vipc_frame_id_extra
driving_model_data.frameDropPerc = frame_drop_perc
driving_model_data.modelExecutionTime = model_execution_time
- driving_model_data.action.desiredCurvature = float(net_output_data['desired_curvature'][0,0])
+
+ driving_model_data.action = action
modelV2 = extended_msg.modelV2
modelV2.frameId = vipc_frame_id
@@ -89,42 +90,26 @@ def fill_model_msg(base_msg: capnp._DynamicStructBuilder, extended_msg: capnp._D
fill_xyzt(modelV2.orientationRate, ModelConstants.T_IDXS, *net_output_data['plan'][0,:,Plan.ORIENTATION_RATE].T)
# temporal pose
- temporal_pose = modelV2.temporalPose
- temporal_pose.trans = net_output_data['sim_pose'][0,:ModelConstants.POSE_WIDTH//2].tolist()
- temporal_pose.transStd = net_output_data['sim_pose_stds'][0,:ModelConstants.POSE_WIDTH//2].tolist()
- temporal_pose.rot = net_output_data['sim_pose'][0,ModelConstants.POSE_WIDTH//2:].tolist()
- temporal_pose.rotStd = net_output_data['sim_pose_stds'][0,ModelConstants.POSE_WIDTH//2:].tolist()
+ #temporal_pose = modelV2.temporalPose
+ #temporal_pose.trans = net_output_data['sim_pose'][0,:ModelConstants.POSE_WIDTH//2].tolist()
+ #temporal_pose.transStd = net_output_data['sim_pose_stds'][0,:ModelConstants.POSE_WIDTH//2].tolist()
+ #temporal_pose.rot = net_output_data['sim_pose'][0,ModelConstants.POSE_WIDTH//2:].tolist()
+ #temporal_pose.rotStd = net_output_data['sim_pose_stds'][0,ModelConstants.POSE_WIDTH//2:].tolist()
# poly path
fill_xyz_poly(driving_model_data.path, ModelConstants.POLY_PATH_DEGREE, *net_output_data['plan'][0,:,Plan.POSITION].T)
- # lateral planning
- modelV2.action.desiredCurvature = float(net_output_data['desired_curvature'][0,0])
-
- # times at X_IDXS according to model plan
- PLAN_T_IDXS = [np.nan] * ModelConstants.IDX_N
- PLAN_T_IDXS[0] = 0.0
- plan_x = net_output_data['plan'][0,:,Plan.POSITION][:,0].tolist()
- for xidx in range(1, ModelConstants.IDX_N):
- tidx = 0
- # increment tidx until we find an element that's further away than the current xidx
- while tidx < ModelConstants.IDX_N - 1 and plan_x[tidx+1] < ModelConstants.X_IDXS[xidx]:
- tidx += 1
- if tidx == ModelConstants.IDX_N - 1:
- # if the Plan doesn't extend far enough, set plan_t to the max value (10s), then break
- PLAN_T_IDXS[xidx] = ModelConstants.T_IDXS[ModelConstants.IDX_N - 1]
- break
- # interpolate to find `t` for the current xidx
- current_x_val = plan_x[tidx]
- next_x_val = plan_x[tidx+1]
- p = (ModelConstants.X_IDXS[xidx] - current_x_val) / (next_x_val - current_x_val) if abs(next_x_val - current_x_val) > 1e-9 else float('nan')
- PLAN_T_IDXS[xidx] = p * ModelConstants.T_IDXS[tidx+1] + (1 - p) * ModelConstants.T_IDXS[tidx]
+ # action
+ modelV2.action = action
+
+ # times at X_IDXS of edges and lines aren't used
+ LINE_T_IDXS: list[float] = []
# lane lines
modelV2.init('laneLines', 4)
for i in range(4):
lane_line = modelV2.laneLines[i]
- fill_xyzt(lane_line, PLAN_T_IDXS, np.array(ModelConstants.X_IDXS), net_output_data['lane_lines'][0,i,:,0], net_output_data['lane_lines'][0,i,:,1])
+ fill_xyzt(lane_line, LINE_T_IDXS, np.array(ModelConstants.X_IDXS), net_output_data['lane_lines'][0,i,:,0], net_output_data['lane_lines'][0,i,:,1])
modelV2.laneLineStds = net_output_data['lane_lines_stds'][0,:,0,0].tolist()
modelV2.laneLineProbs = net_output_data['lane_lines_prob'][0,1::2].tolist()
@@ -134,7 +119,7 @@ def fill_model_msg(base_msg: capnp._DynamicStructBuilder, extended_msg: capnp._D
modelV2.init('roadEdges', 2)
for i in range(2):
road_edge = modelV2.roadEdges[i]
- fill_xyzt(road_edge, PLAN_T_IDXS, np.array(ModelConstants.X_IDXS), net_output_data['road_edges'][0,i,:,0], net_output_data['road_edges'][0,i,:,1])
+ fill_xyzt(road_edge, LINE_T_IDXS, np.array(ModelConstants.X_IDXS), net_output_data['road_edges'][0,i,:,0], net_output_data['road_edges'][0,i,:,1])
modelV2.roadEdgeStds = net_output_data['road_edges_stds'][0,:,0,0].tolist()
# leads
diff --git a/selfdrive/modeld/modeld.py b/selfdrive/modeld/modeld.py
index 1e557942fe..1d0facd133 100755
--- a/selfdrive/modeld/modeld.py
+++ b/selfdrive/modeld/modeld.py
@@ -21,14 +21,15 @@ from opendbc.car.car_helpers import get_demo_car_params
from openpilot.common.swaglog import cloudlog
from openpilot.common.params import Params
from openpilot.common.filter_simple import FirstOrderFilter
-from openpilot.common.realtime import config_realtime_process
+from openpilot.common.realtime import config_realtime_process, DT_MDL
from openpilot.common.transformations.camera import DEVICE_CAMERAS
from openpilot.common.transformations.model import get_warp_matrix
from openpilot.system import sentry
from openpilot.selfdrive.controls.lib.desire_helper import DesireHelper
+from openpilot.selfdrive.controls.lib.drive_helpers import get_accel_from_plan, smooth_value
from openpilot.selfdrive.modeld.parse_model_outputs import Parser
from openpilot.selfdrive.modeld.fill_model_msg import fill_model_msg, fill_pose_msg, PublishState
-from openpilot.selfdrive.modeld.constants import ModelConstants
+from openpilot.selfdrive.modeld.constants import ModelConstants, Plan
from openpilot.selfdrive.modeld.models.commonmodel_pyx import DrivingModelFrame, CLContext
@@ -40,6 +41,26 @@ POLICY_PKL_PATH = Path(__file__).parent / 'models/driving_policy_tinygrad.pkl'
VISION_METADATA_PATH = Path(__file__).parent / 'models/driving_vision_metadata.pkl'
POLICY_METADATA_PATH = Path(__file__).parent / 'models/driving_policy_metadata.pkl'
+LAT_SMOOTH_SECONDS = 0.1
+LONG_SMOOTH_SECONDS = 0.3
+
+
+def get_action_from_model(model_output: dict[str, np.ndarray], prev_action: log.ModelDataV2.Action,
+ lat_action_t: float, long_action_t: float,) -> log.ModelDataV2.Action:
+ plan = model_output['plan'][0]
+ desired_accel, should_stop = get_accel_from_plan(plan[:,Plan.VELOCITY][:,0],
+ plan[:,Plan.ACCELERATION][:,0],
+ ModelConstants.T_IDXS,
+ action_t=long_action_t)
+ desired_accel = smooth_value(desired_accel, prev_action.desiredAcceleration, LONG_SMOOTH_SECONDS)
+
+ desired_curvature = model_output['desired_curvature'][0, 0]
+ desired_curvature = smooth_value(desired_curvature, prev_action.desiredCurvature, LAT_SMOOTH_SECONDS)
+
+ return log.ModelDataV2.Action(desiredCurvature=float(desired_curvature),
+ desiredAcceleration=float(desired_accel),
+ shouldStop=bool(should_stop))
+
class FrameMeta:
frame_id: int = 0
timestamp_sof: int = 0
@@ -147,7 +168,7 @@ class ModelState:
# TODO model only uses last value now
self.full_prev_desired_curv[0,:-1] = self.full_prev_desired_curv[0,1:]
self.full_prev_desired_curv[0,-1,:] = policy_outputs_dict['desired_curvature'][0, :]
- self.numpy_inputs['prev_desired_curv'][:] = self.full_prev_desired_curv[0, self.temporal_idxs]
+ self.numpy_inputs['prev_desired_curv'][:] = 0*self.full_prev_desired_curv[0, self.temporal_idxs]
combined_outputs_dict = {**vision_outputs_dict, **policy_outputs_dict}
if SEND_RAW_PRED:
@@ -221,7 +242,10 @@ def main(demo=False):
cloudlog.info("modeld got CarParams: %s", CP.brand)
# TODO this needs more thought, use .2s extra for now to estimate other delays
- steer_delay = CP.steerActuatorDelay + .2
+ # TODO Move smooth seconds to action function
+ lat_delay = CP.steerActuatorDelay + .2 + LAT_SMOOTH_SECONDS
+ long_delay = CP.longitudinalActuatorDelay + LONG_SMOOTH_SECONDS
+ prev_action = log.ModelDataV2.Action()
DH = DesireHelper()
@@ -263,7 +287,7 @@ def main(demo=False):
is_rhd = sm["driverMonitoringState"].isRHD
frame_id = sm["roadCameraState"].frameId
v_ego = max(sm["carState"].vEgo, 0.)
- lateral_control_params = np.array([v_ego, steer_delay], dtype=np.float32)
+ lateral_control_params = np.array([v_ego, lat_delay], dtype=np.float32)
if sm.updated["liveCalibration"] and sm.seen['roadCameraState'] and sm.seen['deviceState']:
device_from_calib_euler = np.array(sm["liveCalibration"].rpyCalib, dtype=np.float32)
dc = DEVICE_CAMERAS[(str(sm['deviceState'].deviceType), str(sm['roadCameraState'].sensor))]
@@ -306,7 +330,10 @@ def main(demo=False):
modelv2_send = messaging.new_message('modelV2')
drivingdata_send = messaging.new_message('drivingModelData')
posenet_send = messaging.new_message('cameraOdometry')
- fill_model_msg(drivingdata_send, modelv2_send, model_output, v_ego, steer_delay,
+
+ action = get_action_from_model(model_output, prev_action, lat_delay + DT_MDL, long_delay + DT_MDL)
+ prev_action = action
+ fill_model_msg(drivingdata_send, modelv2_send, model_output, action,
publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id,
frame_drop_ratio, meta_main.timestamp_eof, model_execution_time, live_calib_seen)
diff --git a/selfdrive/modeld/models/driving_policy.onnx b/selfdrive/modeld/models/driving_policy.onnx
index 3601bbb5da..df11e590dd 100644
--- a/selfdrive/modeld/models/driving_policy.onnx
+++ b/selfdrive/modeld/models/driving_policy.onnx
@@ -1,3 +1,3 @@
version https://git-lfs.github.com/spec/v1
-oid sha256:98f0121ccb6f850077b04cc91bd33d370fc6cbdc2bd35f1ab55628a15a813f36
-size 15966721
+oid sha256:84061882148485dabfdd23ee7e0925284a4370d0ae5be804d6099ae847352891
+size 15578328
diff --git a/selfdrive/modeld/models/driving_vision.onnx b/selfdrive/modeld/models/driving_vision.onnx
index aee6d8f1bf..5e08b78472 100644
--- a/selfdrive/modeld/models/driving_vision.onnx
+++ b/selfdrive/modeld/models/driving_vision.onnx
@@ -1,3 +1,3 @@
version https://git-lfs.github.com/spec/v1
-oid sha256:897f80d0388250f99bba69b6a8434560cc0fd83157cbeb0bc134c67fe4e64624
-size 34882971
+oid sha256:f222d2c528f1763828de01bb55e8979b1e4056e1dbb41350f521d2d2bb09d177
+size 46265585
diff --git a/selfdrive/modeld/parse_model_outputs.py b/selfdrive/modeld/parse_model_outputs.py
index 810c44ccb9..783572d436 100644
--- a/selfdrive/modeld/parse_model_outputs.py
+++ b/selfdrive/modeld/parse_model_outputs.py
@@ -88,6 +88,12 @@ class Parser:
self.parse_mdn('pose', outs, in_N=0, out_N=0, out_shape=(ModelConstants.POSE_WIDTH,))
self.parse_mdn('wide_from_device_euler', outs, in_N=0, out_N=0, out_shape=(ModelConstants.WIDE_FROM_DEVICE_WIDTH,))
self.parse_mdn('road_transform', outs, in_N=0, out_N=0, out_shape=(ModelConstants.POSE_WIDTH,))
+ self.parse_mdn('lane_lines', outs, in_N=0, out_N=0, out_shape=(ModelConstants.NUM_LANE_LINES,ModelConstants.IDX_N,ModelConstants.LANE_LINES_WIDTH))
+ self.parse_mdn('road_edges', outs, in_N=0, out_N=0, out_shape=(ModelConstants.NUM_ROAD_EDGES,ModelConstants.IDX_N,ModelConstants.LANE_LINES_WIDTH))
+ self.parse_mdn('lead', outs, in_N=ModelConstants.LEAD_MHP_N, out_N=ModelConstants.LEAD_MHP_SELECTION,
+ out_shape=(ModelConstants.LEAD_TRAJ_LEN,ModelConstants.LEAD_WIDTH))
+ for k in ['lead_prob', 'lane_lines_prob']:
+ self.parse_binary_crossentropy(k, outs)
self.parse_categorical_crossentropy('desire_pred', outs, out_shape=(ModelConstants.DESIRE_PRED_LEN,ModelConstants.DESIRE_PRED_WIDTH))
self.parse_binary_crossentropy('meta', outs)
return outs
@@ -95,17 +101,10 @@ class Parser:
def parse_policy_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
self.parse_mdn('plan', outs, in_N=ModelConstants.PLAN_MHP_N, out_N=ModelConstants.PLAN_MHP_SELECTION,
out_shape=(ModelConstants.IDX_N,ModelConstants.PLAN_WIDTH))
- self.parse_mdn('lane_lines', outs, in_N=0, out_N=0, out_shape=(ModelConstants.NUM_LANE_LINES,ModelConstants.IDX_N,ModelConstants.LANE_LINES_WIDTH))
- self.parse_mdn('road_edges', outs, in_N=0, out_N=0, out_shape=(ModelConstants.NUM_ROAD_EDGES,ModelConstants.IDX_N,ModelConstants.LANE_LINES_WIDTH))
- self.parse_mdn('sim_pose', outs, in_N=0, out_N=0, out_shape=(ModelConstants.POSE_WIDTH,))
- self.parse_mdn('lead', outs, in_N=ModelConstants.LEAD_MHP_N, out_N=ModelConstants.LEAD_MHP_SELECTION,
- out_shape=(ModelConstants.LEAD_TRAJ_LEN,ModelConstants.LEAD_WIDTH))
if 'lat_planner_solution' in outs:
self.parse_mdn('lat_planner_solution', outs, in_N=0, out_N=0, out_shape=(ModelConstants.IDX_N,ModelConstants.LAT_PLANNER_SOLUTION_WIDTH))
if 'desired_curvature' in outs:
self.parse_mdn('desired_curvature', outs, in_N=0, out_N=0, out_shape=(ModelConstants.DESIRED_CURV_WIDTH,))
- for k in ['lead_prob', 'lane_lines_prob']:
- self.parse_binary_crossentropy(k, outs)
self.parse_categorical_crossentropy('desire_state', outs, out_shape=(ModelConstants.DESIRE_PRED_WIDTH,))
return outs
diff --git a/selfdrive/selfdrived/selfdrived.py b/selfdrive/selfdrived/selfdrived.py
index c7320f9350..face7dab29 100755
--- a/selfdrive/selfdrived/selfdrived.py
+++ b/selfdrive/selfdrived/selfdrived.py
@@ -19,14 +19,13 @@ from openpilot.selfdrive.car.car_specific import CarSpecificEvents
from openpilot.selfdrive.selfdrived.events import Events, ET
from openpilot.selfdrive.selfdrived.state import StateMachine
from openpilot.selfdrive.selfdrived.alertmanager import AlertManager, set_offroad_alert
-from openpilot.selfdrive.controls.lib.latcontrol import MIN_LATERAL_CONTROL_SPEED
+from openpilot.system.hardware import HARDWARE
from openpilot.system.version import get_build_metadata
REPLAY = "REPLAY" in os.environ
SIMULATION = "SIMULATION" in os.environ
TESTING_CLOSET = "TESTING_CLOSET" in os.environ
-IGNORE_PROCESSES = {"loggerd", "encoderd", "statsd"}
LONGITUDINAL_PERSONALITY_MAP = {v: k for k, v in log.LongitudinalPersonality.schema.enumerants.items()}
ThermalStatus = log.DeviceState.ThermalStatus
@@ -76,7 +75,7 @@ class SelfdriveD:
# no vipc in replay will make them ignored anyways
ignore += ['roadCameraState', 'wideRoadCameraState']
self.sm = messaging.SubMaster(['deviceState', 'pandaStates', 'peripheralState', 'modelV2', 'liveCalibration',
- 'carOutput', 'driverMonitoringState', 'longitudinalPlan', 'livePose',
+ 'carOutput', 'driverMonitoringState', 'longitudinalPlan', 'livePose', 'liveDelay',
'managerState', 'liveParameters', 'radarState', 'liveTorqueParameters',
'controlsState', 'carControl', 'driverAssistance', 'alertDebug'] + \
self.camera_packets + self.sensor_packets + self.gps_packets,
@@ -90,8 +89,8 @@ class SelfdriveD:
car_recognized = self.CP.brand != 'mock'
# cleanup old params
- if not self.CP.experimentalLongitudinalAvailable:
- self.params.remove("ExperimentalLongitudinalEnabled")
+ if not self.CP.alphaLongitudinalAvailable:
+ self.params.remove("AlphaLongitudinalEnabled")
if not self.CP.openpilotLongitudinalControl:
self.params.remove("ExperimentalMode")
@@ -116,6 +115,12 @@ class SelfdriveD:
self.state_machine = StateMachine()
self.rk = Ratekeeper(100, print_delay_threshold=None)
+ # some comma three with NVMe experience NVMe dropouts mid-drive that
+ # cause loggerd to crash on write, so ignore it only on that platform
+ self.ignored_processes = set()
+ if HARDWARE.get_device_type() == 'tici' and os.path.exists('/dev/nvme0'):
+ self.ignored_processes = {'loggerd', }
+
# Determine startup event
self.startup_event = EventName.startup if build_metadata.openpilot.comma_remote and build_metadata.tested_channel else EventName.startupMaster
if not car_recognized:
@@ -259,7 +264,7 @@ class SelfdriveD:
if not_running != self.not_running_prev:
cloudlog.event("process_not_running", not_running=not_running, error=True)
self.not_running_prev = not_running
- if self.sm.recv_frame['managerState'] and (not_running - IGNORE_PROCESSES):
+ if self.sm.recv_frame['managerState'] and (not_running - self.ignored_processes):
self.events.add(EventName.processNotRunning)
else:
if not SIMULATION and not self.rk.lagging:
@@ -276,7 +281,6 @@ class SelfdriveD:
self.events.add(EventName.radarTempUnavailable)
else:
self.events.add(EventName.radarFault)
- self.events.add(EventName.radarFault)
if not self.sm.valid['pandaStates']:
self.events.add(EventName.usbError)
if CS.canTimeout:
@@ -332,7 +336,7 @@ class SelfdriveD:
controlstate = self.sm['controlsState']
lac = getattr(controlstate.lateralControlState, controlstate.lateralControlState.which())
if lac.active and not recent_steer_pressed and not self.CP.notCar:
- clipped_speed = max(CS.vEgo, MIN_LATERAL_CONTROL_SPEED)
+ clipped_speed = max(CS.vEgo, 0.3)
actual_lateral_accel = controlstate.curvature * (clipped_speed**2)
desired_lateral_accel = self.sm['modelV2'].action.desiredCurvature * (clipped_speed**2)
undershooting = abs(desired_lateral_accel) / abs(1e-3 + actual_lateral_accel) > 1.2
diff --git a/selfdrive/test/longitudinal_maneuvers/plant.py b/selfdrive/test/longitudinal_maneuvers/plant.py
index 989b84dee3..b8c6adb436 100755
--- a/selfdrive/test/longitudinal_maneuvers/plant.py
+++ b/selfdrive/test/longitudinal_maneuvers/plant.py
@@ -107,6 +107,7 @@ class Plant:
position = log.XYZTData.new_message()
position.x = [float(x) for x in (self.speed + 0.5) * np.array(ModelConstants.T_IDXS)]
model.modelV2.position = position
+ model.modelV2.action.desiredAcceleration = float(self.acceleration + 0.1)
velocity = log.XYZTData.new_message()
velocity.x = [float(x) for x in (self.speed + 0.5) * np.ones_like(ModelConstants.T_IDXS)]
velocity.x[0] = float(self.speed) # always start at current speed
diff --git a/selfdrive/test/process_replay/migration.py b/selfdrive/test/process_replay/migration.py
index fd13c4f239..02cd9b6d71 100644
--- a/selfdrive/test/process_replay/migration.py
+++ b/selfdrive/test/process_replay/migration.py
@@ -9,10 +9,11 @@ from opendbc.car.fingerprints import MIGRATION
from opendbc.car.toyota.values import EPS_SCALE, ToyotaSafetyFlags
from opendbc.car.ford.values import CAR as FORD, FordFlags, FordSafetyFlags
from opendbc.car.hyundai.values import HyundaiSafetyFlags
+from opendbc.car.gm.values import GMSafetyFlags
from openpilot.selfdrive.modeld.constants import ModelConstants
from openpilot.selfdrive.modeld.fill_model_msg import fill_xyz_poly, fill_lane_line_meta
from openpilot.selfdrive.test.process_replay.vision_meta import meta_from_encode_index
-from openpilot.selfdrive.controls.lib.longitudinal_planner import get_accel_from_plan
+from openpilot.selfdrive.controls.lib.longitudinal_planner import get_accel_from_plan, CONTROL_N_T_IDX
from openpilot.system.manager.process_config import managed_processes
from openpilot.tools.lib.logreader import LogIterable
@@ -108,7 +109,7 @@ def migrate_longitudinalPlan(msgs):
if msg.which() != 'longitudinalPlan':
continue
new_msg = msg.as_builder()
- a_target, should_stop = get_accel_from_plan(msg.longitudinalPlan.speeds, msg.longitudinalPlan.accels)
+ a_target, should_stop = get_accel_from_plan(msg.longitudinalPlan.speeds, msg.longitudinalPlan.accels, CONTROL_N_T_IDX)
new_msg.longitudinalPlan.aTarget, new_msg.longitudinalPlan.shouldStop = float(a_target), bool(should_stop)
ops.append((index, new_msg.as_reader()))
return ops, [], []
@@ -274,9 +275,11 @@ def migrate_pandaStates(msgs):
"TOYOTA_PRIUS": EPS_SCALE["TOYOTA_PRIUS"] | ToyotaSafetyFlags.STOCK_LONGITUDINAL,
"TOYOTA_RAV4": EPS_SCALE["TOYOTA_RAV4"] | ToyotaSafetyFlags.ALT_BRAKE,
"KIA_EV6": HyundaiSafetyFlags.EV_GAS | HyundaiSafetyFlags.CANFD_LKA_STEERING,
+ "CHEVROLET_VOLT": GMSafetyFlags.EV,
+ "CHEVROLET_BOLT_EUV": GMSafetyFlags.EV | GMSafetyFlags.HW_CAM,
}
# TODO: get new Ford route
- safety_param_migration |= {car: FordSafetyFlags.LONG_CONTROL for car in (set(FORD) - FORD.with_flags(FordFlags.CANFD))}
+ safety_param_migration |= dict.fromkeys((set(FORD) - FORD.with_flags(FordFlags.CANFD)), FordSafetyFlags.LONG_CONTROL)
# Migrate safety param base on carParams
CP = next((m.carParams for _, m in msgs if m.which() == 'carParams'), None)
diff --git a/selfdrive/test/process_replay/model_replay.py b/selfdrive/test/process_replay/model_replay.py
index 36398af8ca..af626e2da9 100755
--- a/selfdrive/test/process_replay/model_replay.py
+++ b/selfdrive/test/process_replay/model_replay.py
@@ -64,6 +64,7 @@ def generate_report(proposed, master, tmp, commit):
ModelV2_Plots = zl([
(lambda x: get_idx_if_non_empty(x.velocity.x, 0), "velocity.x"),
(lambda x: get_idx_if_non_empty(x.action.desiredCurvature), "desiredCurvature"),
+ (lambda x: get_idx_if_non_empty(x.action.desiredAcceleration), "desiredAcceleration"),
(lambda x: get_idx_if_non_empty(x.leadsV3[0].x, 0), "leadsV3.x"),
(lambda x: get_idx_if_non_empty(x.laneLines[1].y, 0), "laneLines.y"),
(lambda x: get_idx_if_non_empty(x.meta.desireState, 3), "desireState.laneChangeLeft"),
diff --git a/selfdrive/test/process_replay/process_replay.py b/selfdrive/test/process_replay/process_replay.py
index 16761225d3..6139846322 100755
--- a/selfdrive/test/process_replay/process_replay.py
+++ b/selfdrive/test/process_replay/process_replay.py
@@ -2,7 +2,6 @@
import os
import time
import copy
-import json
import heapq
import signal
from collections import Counter, OrderedDict
@@ -364,7 +363,7 @@ def get_car_params_callback(rc, pm, msgs, fingerprint):
with car.CarParams.from_bytes(cached_params_raw) as _cached_params:
cached_params = _cached_params
- CP = get_car(*can_callbacks, lambda obd: None, Params().get_bool("ExperimentalLongitudinalEnabled"), cached_params=cached_params).CP
+ CP = get_car(*can_callbacks, lambda obd: None, Params().get_bool("AlphaLongitudinalEnabled"), cached_params=cached_params).CP
if not params.get_bool("DisengageOnAccelerator"):
CP.alternativeExperience |= ALTERNATIVE_EXPERIENCE.DISABLE_DISENGAGE_ON_GAS
@@ -463,7 +462,7 @@ CONFIGS = [
proc_name="selfdrived",
pubs=[
"carState", "deviceState", "pandaStates", "peripheralState", "liveCalibration", "driverMonitoringState",
- "longitudinalPlan", "livePose", "liveParameters", "radarState",
+ "longitudinalPlan", "livePose", "liveDelay", "liveParameters", "radarState",
"modelV2", "driverCameraState", "roadCameraState", "wideRoadCameraState", "managerState",
"liveTorqueParameters", "accelerometer", "gyroscope", "carOutput",
"gpsLocationExternal", "gpsLocation", "controlsState", "carControl", "driverAssistance", "alertDebug",
@@ -517,9 +516,10 @@ CONFIGS = [
),
ProcessConfig(
proc_name="calibrationd",
- pubs=["carState", "cameraOdometry", "carParams"],
+ pubs=["carState", "cameraOdometry"],
subs=["liveCalibration"],
ignore=["logMonoTime"],
+ init_callback=get_car_params_callback,
should_recv_callback=calibration_rcv_callback,
),
ProcessConfig(
@@ -551,6 +551,15 @@ CONFIGS = [
tolerance=NUMPY_TOLERANCE,
processing_time=0.004,
),
+ ProcessConfig(
+ proc_name="lagd",
+ pubs=["livePose", "liveCalibration", "carState", "carControl", "controlsState"],
+ subs=["liveDelay"],
+ ignore=["logMonoTime"],
+ init_callback=get_car_params_callback,
+ should_recv_callback=MessageBasedRcvCallback("livePose"),
+ tolerance=NUMPY_TOLERANCE,
+ ),
ProcessConfig(
proc_name="ubloxd",
pubs=["ubloxRaw"],
@@ -628,9 +637,7 @@ def get_custom_params_from_lr(lr: LogIterable, initial_state: str = "first") ->
if len(live_calibration) > 0:
custom_params["CalibrationParams"] = live_calibration[msg_index].as_builder().to_bytes()
if len(live_parameters) > 0:
- lp_dict = live_parameters[msg_index].to_dict()
- lp_dict["carFingerprint"] = CP.carFingerprint
- custom_params["LiveParameters"] = json.dumps(lp_dict)
+ custom_params["LiveParameters"] = live_parameters[msg_index].as_builder().to_bytes()
if len(live_torque_parameters) > 0:
custom_params["LiveTorqueParameters"] = live_torque_parameters[msg_index].as_builder().to_bytes()
@@ -770,7 +777,7 @@ def generate_params_config(lr=None, CP=None, fingerprint=None, custom_params=Non
params_dict["CarParamsCache"] = CP.as_builder().to_bytes()
if CP.openpilotLongitudinalControl:
- params_dict["ExperimentalLongitudinalEnabled"] = True
+ params_dict["AlphaLongitudinalEnabled"] = True
if CP.notCar:
params_dict["JoystickDebugMode"] = True
diff --git a/selfdrive/test/process_replay/ref_commit b/selfdrive/test/process_replay/ref_commit
index 353b8fa7ce..4b3ef33407 100644
--- a/selfdrive/test/process_replay/ref_commit
+++ b/selfdrive/test/process_replay/ref_commit
@@ -1 +1 @@
-e9d57157494480637a8ffb52257d2b660a48be67
\ No newline at end of file
+fcc771b9ceb487a61035885acbd84e592fb316bf
\ No newline at end of file
diff --git a/selfdrive/test/process_replay/test_processes.py b/selfdrive/test/process_replay/test_processes.py
index 927f54c0c3..d479369693 100755
--- a/selfdrive/test/process_replay/test_processes.py
+++ b/selfdrive/test/process_replay/test_processes.py
@@ -22,16 +22,16 @@ source_segments = [
("HYUNDAI2", "d545129f3ca90f28|2022-11-07--20-43-08--3"), # HYUNDAI.HYUNDAI_KIA_EV6 (+ QCOM GPS)
("TOYOTA", "0982d79ebb0de295|2021-01-04--17-13-21--13"), # TOYOTA.TOYOTA_PRIUS
("TOYOTA2", "0982d79ebb0de295|2021-01-03--20-03-36--6"), # TOYOTA.TOYOTA_RAV4
- ("TOYOTA3", "f7d7e3538cda1a2a|2021-08-16--08-55-34--6"), # TOYOTA.TOYOTA_COROLLA_TSS2
+ ("TOYOTA3", "8011d605be1cbb77|000000cc--8e8d8ec716--6"), # TOYOTA.TOYOTA_COROLLA_TSS2
("HONDA", "eb140f119469d9ab|2021-06-12--10-46-24--27"), # HONDA.HONDA_CIVIC (NIDEC)
("HONDA2", "7d2244f34d1bbcda|2021-06-25--12-25-37--26"), # HONDA.HONDA_ACCORD (BOSCH)
("CHRYSLER", "4deb27de11bee626|2021-02-20--11-28-55--8"), # CHRYSLER.CHRYSLER_PACIFICA_2018_HYBRID
("RAM", "17fc16d840fe9d21|2023-04-26--13-28-44--5"), # CHRYSLER.RAM_1500_5TH_GEN
("SUBARU", "341dccd5359e3c97|2022-09-12--10-35-33--3"), # SUBARU.SUBARU_OUTBACK
- ("GM", "0c58b6a25109da2b|2021-02-23--16-35-50--11"), # GM.CHEVROLET_VOLT
- ("GM2", "376bf99325883932|2022-10-27--13-41-22--1"), # GM.CHEVROLET_BOLT_EUV
+ ("GM", "376bf99325883932|2022-10-27--13-41-22--1"), # GM.CHEVROLET_BOLT_EUV
("NISSAN", "35336926920f3571|2021-02-12--18-38-48--46"), # NISSAN.NISSAN_XTRAIL
("VOLKSWAGEN", "de9592456ad7d144|2021-06-29--11-00-15--6"), # VOLKSWAGEN.VOLKSWAGEN_GOLF
+ # FIXME the sensor timings are bad in mazda segment, we're not fully testing it, but it should be replaced
("MAZDA", "bd6a637565e91581|2021-10-30--15-14-53--4"), # MAZDA.MAZDA_CX9_2021
("FORD", "54827bf84c38b14f|2023-01-26--21-59-07--4"), # FORD.FORD_BRONCO_SPORT_MK1
("RIVIAN", "bc095dc92e101734|000000db--ee9fe46e57--1"), # RIVIAN.RIVIAN_R1_GEN1
@@ -41,28 +41,27 @@ source_segments = [
]
segments = [
- ("BODY", "regenA67A128BCD8|2024-08-30--02-36-22--0"),
- ("HYUNDAI", "regenCCD47FEBC0C|2025-03-04--03-21-48--0"),
- ("HYUNDAI2", "regen306779F6870|2024-10-03--04-03-23--0"),
- ("TOYOTA", "regen4A5115B248D|2025-03-04--03-21-43--0"),
- ("TOYOTA2", "regen6E484EDAB96|2024-08-30--02-47-37--0"),
- ("TOYOTA3", "regen4CE950B0267|2024-08-30--02-51-30--0"),
- ("HONDA", "regenB8CABEC09CC|2025-03-04--03-32-55--0"),
- ("HONDA2", "regen4B38A7428CD|2024-08-30--02-56-31--0"),
- ("CHRYSLER", "regenF3DBBA9E8DF|2024-08-30--02-59-03--0"),
- ("RAM", "regenDB02684E00A|2024-08-30--03-02-54--0"),
- ("SUBARU", "regen5E3347D0A0F|2025-03-04--03-23-55--0"),
- ("GM", "regen720F2BA4CF6|2024-08-30--03-09-15--0"),
- ("GM2", "regen9ADBECBCD1C|2024-08-30--03-13-04--0"),
- ("NISSAN", "regen58464878D07|2024-08-30--03-15-31--0"),
- ("VOLKSWAGEN", "regenED976DEB757|2024-08-30--03-18-02--0"),
+ ("BODY", "regen2F3C7259F1B|2025-04-08--23-00-23--0"),
+ ("HYUNDAI", "regenAA0FC4ED71E|2025-04-08--22-57-50--0"),
+ ("HYUNDAI2", "regenAFB9780D823|2025-04-08--23-00-34--0"),
+ ("TOYOTA", "regen218A4DCFAA1|2025-04-08--22-57-51--0"),
+ ("TOYOTA2", "regen107352E20EB|2025-04-08--22-57-46--0"),
+ ("TOYOTA3", "regen1455E3B4BDF|2025-04-09--03-26-06--0"),
+ ("HONDA", "regenB328FF8BA0A|2025-04-08--22-57-45--0"),
+ ("HONDA2", "regen6170C8C9A35|2025-04-08--22-57-46--0"),
+ ("CHRYSLER", "regen5B28FC2A437|2025-04-08--23-04-24--0"),
+ ("RAM", "regenBF81EA96E08|2025-04-08--23-06-54--0"),
+ ("SUBARU", "regen7366F13F6A1|2025-04-08--23-07-07--0"),
+ ("GM", "regen1271097D038|2025-04-09--03-26-00--0"),
+ ("NISSAN", "regen15D60604EAB|2025-04-08--23-06-59--0"),
+ ("VOLKSWAGEN", "regen0F2F06C9539|2025-04-08--23-06-56--0"),
("MAZDA", "regenACF84CCF482|2024-08-30--03-21-55--0"),
- ("FORD", "regenA75209BD115|2025-03-04--03-23-53--0"),
- ("RIVIAN", "bc095dc92e101734|000000db--ee9fe46e57--1"),
+ ("FORD", "regen755D8CB1E1F|2025-04-08--23-13-43--0"),
+ ("RIVIAN", "regen5FCAC896BBE|2025-04-08--23-13-35--0"),
]
# dashcamOnly makes don't need to be tested until a full port is done
-excluded_interfaces = ["mock", "tesla", "rivian"]
+excluded_interfaces = ["mock", "tesla"]
BASE_URL = "https://commadataci.blob.core.windows.net/openpilotci/"
REF_COMMIT_FN = os.path.join(PROC_REPLAY_DIR, "ref_commit")
@@ -196,7 +195,7 @@ if __name__ == "__main__":
continue
# to speed things up, we only test all segments on card
- if cfg.proc_name != 'card' and car_brand not in ('HYUNDAI', 'TOYOTA', 'HONDA', 'SUBARU', 'FORD'):
+ if cfg.proc_name != 'card' and car_brand not in ('HYUNDAI', 'TOYOTA', 'HONDA', 'SUBARU', 'FORD', 'RIVIAN'):
continue
cur_log_fn = os.path.join(FAKEDATA, f"{segment}_{cfg.proc_name}_{cur_commit}.zst")
diff --git a/selfdrive/test/test_onroad.py b/selfdrive/test/test_onroad.py
index 1ea59c4856..4cd952219c 100644
--- a/selfdrive/test/test_onroad.py
+++ b/selfdrive/test/test_onroad.py
@@ -44,7 +44,6 @@ PROCS = {
"./camerad": 10.0,
"selfdrive.controls.plannerd": 9.0,
"./ui": 18.0,
- "selfdrive.locationd.paramsd": 9.0,
"./sensord": 7.0,
"selfdrive.controls.radard": 2.0,
"selfdrive.modeld.modeld": 22.0,
@@ -53,6 +52,8 @@ PROCS = {
"selfdrive.locationd.calibrationd": 2.0,
"selfdrive.locationd.torqued": 5.0,
"selfdrive.locationd.locationd": 25.0,
+ "selfdrive.locationd.paramsd": 9.0,
+ "selfdrive.locationd.lagd": 11.0,
"selfdrive.ui.soundd": 3.0,
"selfdrive.monitoring.dmonitoringd": 4.0,
"./proclogd": 2.0,
@@ -95,6 +96,7 @@ TIMINGS = {
"modelV2": [2.5, 0.35],
"driverStateV2": [2.5, 0.40],
"livePose": [2.5, 0.35],
+ "liveParameters": [2.5, 0.35],
"wideRoadCameraState": [1.5, 0.35],
}
@@ -187,7 +189,7 @@ class TestOnroad:
def test_manager_starting_time(self):
st = self.ts['managerState']['t'][0]
- assert (st - self.manager_st) < 10, f"manager.py took {st - self.manager_st}s to publish the first 'managerState' msg"
+ assert (st - self.manager_st) < 12.5, f"manager.py took {st - self.manager_st}s to publish the first 'managerState' msg"
def test_cloudlog_size(self):
msgs = self.msgs['logMessage']
@@ -391,8 +393,12 @@ class TestOnroad:
result += "----------------- Model Timing -----------------\n"
result += "------------------------------------------------\n"
cfgs = [
- ("modelV2", 0.045, 0.040), # TODO: this should be stricter but it's hard to measure exactly
- ("driverStateV2", 0.045, 0.035),
+ # since multiple processes use the GPU and can preempt each other,
+ # these numbers are not fully self-contained.
+ ("modelV2", 0.06, 0.040),
+
+ # can miss cycles here and there, just important the avg frequency is 20Hz
+ ("driverStateV2", 0.2, 0.05),
]
for (s, instant_max, avg_max) in cfgs:
ts = [getattr(m, s).modelExecutionTime for m in self.msgs[s]]
diff --git a/selfdrive/ui/qt/offroad/developer_panel.cc b/selfdrive/ui/qt/offroad/developer_panel.cc
index 365aec09c4..a095228da2 100644
--- a/selfdrive/ui/qt/offroad/developer_panel.cc
+++ b/selfdrive/ui/qt/offroad/developer_panel.cc
@@ -26,7 +26,7 @@ DeveloperPanel::DeveloperPanel(SettingsWindow *parent) : ListWidget(parent) {
addItem(longManeuverToggle);
experimentalLongitudinalToggle = new ParamControl(
- "ExperimentalLongitudinalEnabled",
+ "AlphaLongitudinalEnabled",
tr("openpilot Longitudinal Control (Alpha)"),
QString("%1
%2")
.arg(tr("WARNING: openpilot longitudinal control is in alpha for this car and will disable Automatic Emergency Braking (AEB)."))
@@ -68,8 +68,8 @@ void DeveloperPanel::updateToggles(bool _offroad) {
capnp::FlatArrayMessageReader cmsg(aligned_buf.align(cp_bytes.data(), cp_bytes.size()));
cereal::CarParams::Reader CP = cmsg.getRoot();
- if (!CP.getExperimentalLongitudinalAvailable() || is_release) {
- params.remove("ExperimentalLongitudinalEnabled");
+ if (!CP.getAlphaLongitudinalAvailable() || is_release) {
+ params.remove("AlphaLongitudinalEnabled");
experimentalLongitudinalToggle->setEnabled(false);
}
@@ -78,7 +78,7 @@ void DeveloperPanel::updateToggles(bool _offroad) {
* - is not a release branch, and
* - the car supports experimental longitudinal control (alpha)
*/
- experimentalLongitudinalToggle->setVisible(CP.getExperimentalLongitudinalAvailable() && !is_release);
+ experimentalLongitudinalToggle->setVisible(CP.getAlphaLongitudinalAvailable() && !is_release);
longManeuverToggle->setEnabled(hasLongitudinalControl(CP) && _offroad);
} else {
diff --git a/selfdrive/ui/qt/offroad/firehose.cc b/selfdrive/ui/qt/offroad/firehose.cc
index 2923dbffe5..80de9cfa40 100644
--- a/selfdrive/ui/qt/offroad/firehose.cc
+++ b/selfdrive/ui/qt/offroad/firehose.cc
@@ -106,7 +106,7 @@ void FirehosePanel::refresh() {
toggle_label->setText(tr("ACTIVE"));
toggle_label->setStyleSheet("font-size: 60px; font-weight: bold; color: #2ecc71;");
} else {
- toggle_label->setText(tr("INACTIVE: connect to unmetered network"));
+ toggle_label->setText(tr("INACTIVE: connect to an unmetered network"));
toggle_label->setStyleSheet("font-size: 60px;");
}
}
diff --git a/selfdrive/ui/qt/offroad/settings.cc b/selfdrive/ui/qt/offroad/settings.cc
index 4d0516bda1..7a79413e2d 100644
--- a/selfdrive/ui/qt/offroad/settings.cc
+++ b/selfdrive/ui/qt/offroad/settings.cc
@@ -152,7 +152,7 @@ void TogglesPanel::updateToggles() {
QString long_desc = unavailable + " " + \
tr("openpilot longitudinal control may come in a future update.");
- if (CP.getExperimentalLongitudinalAvailable()) {
+ if (CP.getAlphaLongitudinalAvailable()) {
if (is_release) {
long_desc = unavailable + " " + tr("An alpha version of openpilot longitudinal control can be tested, along with Experimental mode, on non-release branches.");
} else {
diff --git a/selfdrive/ui/qt/util.cc b/selfdrive/ui/qt/util.cc
index 399a1a98d7..ff381fe39c 100644
--- a/selfdrive/ui/qt/util.cc
+++ b/selfdrive/ui/qt/util.cc
@@ -193,8 +193,8 @@ QPixmap bootstrapPixmap(const QString &id) {
bool hasLongitudinalControl(const cereal::CarParams::Reader &car_params) {
// Using the experimental longitudinal toggle, returns whether longitudinal control
// will be active without needing a restart of openpilot
- return car_params.getExperimentalLongitudinalAvailable()
- ? Params().getBool("ExperimentalLongitudinalEnabled")
+ return car_params.getAlphaLongitudinalAvailable()
+ ? Params().getBool("AlphaLongitudinalEnabled")
: car_params.getOpenpilotLongitudinalControl();
}
diff --git a/selfdrive/ui/tests/test_ui/run.py b/selfdrive/ui/tests/test_ui/run.py
index 35323cf000..c830680aa6 100755
--- a/selfdrive/ui/tests/test_ui/run.py
+++ b/selfdrive/ui/tests/test_ui/run.py
@@ -56,7 +56,7 @@ def setup_settings_firehose(click, pm: PubMaster):
def setup_settings_developer(click, pm: PubMaster):
CP = car.CarParams()
- CP.experimentalLongitudinalAvailable = True
+ CP.alphaLongitudinalAvailable = True
Params().put("CarParamsPersistent", CP.to_bytes())
setup_settings_device(click, pm)
diff --git a/selfdrive/ui/translations/main_ar.ts b/selfdrive/ui/translations/main_ar.ts
index 8f43e64e8a..2afc088b24 100644
--- a/selfdrive/ui/translations/main_ar.ts
+++ b/selfdrive/ui/translations/main_ar.ts
@@ -327,10 +327,6 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
ACTIVE
نشط
-
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to unmetered network
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>غير نشط</span>: اتصل بشبكة غير محسوبة
-
For maximum effectiveness, bring your device inside and connect to a good USB-C adapter and Wi-Fi weekly.<br><br>Firehose Mode can also work while you're driving if connected to a hotspot or unlimited SIM card.<br><br><br><b>Frequently Asked Questions</b><br><br><i>Does it matter how or where I drive?</i> Nope, just drive as you normally would.<br><br><i>Do all of my segments get pulled in Firehose Mode?</i> No, we selectively pull a subset of your segments.<br><br><i>What's a good USB-C adapter?</i> Any fast phone or laptop charger should be fine.<br><br><i>Does it matter which software I run?</i> Yes, only upstream openpilot (and particular forks) are able to be used for training.
للحصول على أقصى فعالية، أحضر جهازك إلى الداخل واتصل بمحول USB-C جيد وشبكة Wi-Fi أسبوعياً.<br><br>يمكن أن يعمل وضع خرطوم الحريق أيضاً أثناء القيادة إذا كنت متصلاً بنقطة اتصال أو ببطاقة SIM غير محدودة.<br><br><br><b>الأسئلة المتكررة</b><br><br><i>هل يهم كيف أو أين أقود؟</i> لا، فقط قد كما تفعل عادة.<br><br><i>هل يتم سحب كل مقاطع رحلاتي في وضع خرطوم الحريق؟</i> لا، نقوم بسحب مجموعة مختارة من مقاطع رحلاتك.<br><br><i>ما هو محول USB-C الجيد؟</i> أي شاحن سريع للهاتف أو اللابتوب يجب أن يكون مناسباً.<br><br><i>هل يهم أي برنامج أستخدم؟</i> نعم، فقط النسخة الأصلية من openpilot (وأفرع معينة) يمكن استخدامها للتدريب.
@@ -346,6 +342,10 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
حتى الآن، يوجد </b>%n مقطع<b>%n من قيادتك في مجموعة بيانات التدريب.
+
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to an unmetered network
+
+
HudRenderer
diff --git a/selfdrive/ui/translations/main_de.ts b/selfdrive/ui/translations/main_de.ts
index d440e790fc..986c0fa54f 100644
--- a/selfdrive/ui/translations/main_de.ts
+++ b/selfdrive/ui/translations/main_de.ts
@@ -68,23 +68,23 @@
Hidden Network
-
+ Verborgenes Netzwerk
CONNECT
- CONNECT
+ VERBINDEN
Enter SSID
- SSID eingeben
+ SSID eingeben
Enter password
- Passwort eingeben
+ Passwort eingeben
for "%1"
- für "%1"
+ für "%1"
@@ -117,31 +117,31 @@
DeveloperPanel
Joystick Debug Mode
-
+ Joystick Debug-Modus
Longitudinal Maneuver Mode
-
+ Längsmanöver-Modus
openpilot Longitudinal Control (Alpha)
-
+ openpilot Längsregelung (Alpha)
WARNING: openpilot longitudinal control is in alpha for this car and will disable Automatic Emergency Braking (AEB).
-
+ WARNUNG: Die openpilot Längsregelung befindet sich für dieses Fahrzeug im Alpha-Stadium und deaktiviert das automatische Notbremsen (AEB).
On this car, openpilot defaults to the car's built-in ACC instead of openpilot's longitudinal control. Enable this to switch to openpilot longitudinal control. Enabling Experimental mode is recommended when enabling openpilot longitudinal control alpha.
-
+ Bei diesem Fahrzeug verwendet openpilot standardmäßig den eingebauten Tempomaten anstelle der openpilot Längsregelung. Aktiviere diese Option, um auf die openpilot Längsregelung umzuschalten. Es wird empfohlen, den experimentellen Modus zu aktivieren, wenn die openpilot Längsregelung (Alpha) aktiviert wird.
Enable ADB
-
+ ADB aktivieren
ADB (Android Debug Bridge) allows connecting to your device over USB or over the network. See https://docs.comma.ai/how-to/connect-to-comma for more info.
-
+ ADB (Android Debug Bridge) ermöglicht die Verbindung zu deinem Gerät über USB oder Netzwerk. Siehe https://docs.comma.ai/how-to/connect-to-comma für weitere Informationen.
@@ -280,11 +280,11 @@
Pair Device
-
+ Gerät koppeln
PAIR
-
+ KOPPELN
@@ -309,37 +309,39 @@
FirehosePanel
🔥 Firehose Mode 🔥
-
+ 🔥 Firehose-Modus 🔥
openpilot learns to drive by watching humans, like you, drive.
Firehose Mode allows you to maximize your training data uploads to improve openpilot's driving models. More data means bigger models, which means better Experimental Mode.
-
+ openpilot lernt das Fahren, indem es Menschen wie dir beim Fahren zuschaut.
+
+Der Firehose-Modus ermöglicht es dir, deine Trainingsdaten-Uploads zu maximieren, um die Fahrmodelle von openpilot zu verbessern. Mehr Daten bedeuten größere Modelle, was zu einem besseren Experimentellen Modus führt.
Firehose Mode: ACTIVE
-
+ Firehose-Modus: AKTIV
ACTIVE
-
-
-
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to unmetered network
-
+ AKTIV
For maximum effectiveness, bring your device inside and connect to a good USB-C adapter and Wi-Fi weekly.<br><br>Firehose Mode can also work while you're driving if connected to a hotspot or unlimited SIM card.<br><br><br><b>Frequently Asked Questions</b><br><br><i>Does it matter how or where I drive?</i> Nope, just drive as you normally would.<br><br><i>Do all of my segments get pulled in Firehose Mode?</i> No, we selectively pull a subset of your segments.<br><br><i>What's a good USB-C adapter?</i> Any fast phone or laptop charger should be fine.<br><br><i>Does it matter which software I run?</i> Yes, only upstream openpilot (and particular forks) are able to be used for training.
-
+ Für maximale Effektivität bring dein Gerät jede Woche nach drinnen und verbinde es mit einem guten USB-C-Adapter und WLAN.<br><br>Der Firehose-Modus funktioniert auch während der Fahrt, wenn das Gerät mit einem Hotspot oder einer ungedrosselten SIM-Karte verbunden ist.<br><br><br><b>Häufig gestellte Fragen</b><br><br><i>Spielt es eine Rolle, wie oder wo ich fahre?</i> Nein, fahre einfach wie gewohnt.<br><br><i>Werden im Firehose-Modus alle meine Segmente hochgeladen?</i> Nein, wir wählen selektiv nur einen Teil deiner Segmente aus.<br><br><i>Welcher USB-C-Adapter ist gut?</i> Jedes Schnellladegerät für Handy oder Laptop sollte ausreichen.<br><br><i>Spielt es eine Rolle, welche Software ich nutze?</i> Ja, nur das offizielle Upstream‑openpilot (und bestimmte Forks) kann für das Training verwendet werden.
<b>%n segment(s)</b> of your driving is in the training dataset so far.
-
-
-
+
+ <b>%n Segment</b> deiner Fahrten ist bisher im Trainingsdatensatz.
+ <b>%n Segmente</b> deiner Fahrten sind bisher im Trainingsdatensatz.
+
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to an unmetered network
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INAKTIV</span>: Verbinde dich mit einem ungedrosselten Netzwerk
+
HudRenderer
@@ -411,48 +413,49 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
OffroadAlert
Immediately connect to the internet to check for updates. If you do not connect to the internet, openpilot won't engage in %1
-
+ Stelle sofort eine Internetverbindung her, um nach Updates zu suchen. Wenn du keine Verbindung herstellst, kann openpilot in %1 nicht mehr aktiviert werden.
Connect to internet to check for updates. openpilot won't automatically start until it connects to internet to check for updates.
-
+ Verbinde dich mit dem Internet, um nach Updates zu suchen. openpilot startet nicht automatisch, bis eine Internetverbindung besteht und nach Updates gesucht wurde.
Unable to download updates
%1
-
+ Updates konnten nicht heruntergeladen werden
+%1
Taking camera snapshots. System won't start until finished.
-
+ Kamera-Snapshots werden aufgenommen. Das System startet erst, wenn dies abgeschlossen ist.
An update to your device's operating system is downloading in the background. You will be prompted to update when it's ready to install.
-
+ Ein Update für das Betriebssystem deines Geräts wird im Hintergrund heruntergeladen. Du wirst aufgefordert, das Update zu installieren, sobald es bereit ist.
Device failed to register. It will not connect to or upload to comma.ai servers, and receives no support from comma.ai. If this is an official device, visit https://comma.ai/support.
-
+ Gerät konnte nicht registriert werden. Es wird keine Verbindung zu den comma.ai-Servern herstellen oder Daten hochladen und erhält keinen Support von comma.ai. Wenn dies ein offizielles Gerät ist, besuche https://comma.ai/support.
NVMe drive not mounted.
-
+ NVMe-Laufwerk nicht gemounted.
Unsupported NVMe drive detected. Device may draw significantly more power and overheat due to the unsupported NVMe.
-
+ Nicht unterstütztes NVMe-Laufwerk erkannt. Das Gerät kann dadurch deutlich mehr Strom verbrauchen und überhitzen.
openpilot was unable to identify your car. Your car is either unsupported or its ECUs are not recognized. Please submit a pull request to add the firmware versions to the proper vehicle. Need help? Join discord.comma.ai.
-
+ openpilot konnte dein Auto nicht identifizieren. Dein Auto wird entweder nicht unterstützt oder die Steuergeräte (ECUs) werden nicht erkannt. Bitte reiche einen Pull Request ein, um die Firmware-Versionen für das richtige Fahrzeug hinzuzufügen. Hilfe findest du auf discord.comma.ai.
openpilot detected a change in the device's mounting position. Ensure the device is fully seated in the mount and the mount is firmly secured to the windshield.
-
+ openpilot hat eine Änderung der Montageposition des Geräts erkannt. Stelle sicher, dass das Gerät vollständig in der Halterung sitzt und die Halterung fest an der Windschutzscheibe befestigt ist.
Device temperature too high. System cooling down before starting. Current internal component temperature: %1
-
+ Gerätetemperatur zu hoch. Das System kühlt ab, bevor es startet. Aktuelle interne Komponententemperatur: %1
@@ -474,23 +477,23 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
OnroadAlerts
openpilot Unavailable
-
+ openpilot nicht verfügbar
TAKE CONTROL IMMEDIATELY
-
+ ÜBERNIMM SOFORT DIE KONTROLLE
Reboot Device
-
+ Gerät neu starten
Waiting to start
-
+ Warten auf Start
System Unresponsive
-
+ System reagiert nicht
@@ -513,7 +516,7 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
Please connect to Wi-Fi to complete initial pairing
-
+ Bitte verbinde dich mit WLAN, um die Koppelung abzuschließen.
@@ -547,15 +550,15 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
24/7 LTE connectivity
-
+ 24/7 LTE-Verbindung
1 year of drive storage
-
+ Fahrdaten-Speicherung für 1 Jahr
Remote snapshots
-
+ Remote-Snapshots
@@ -606,7 +609,7 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
now
-
+ jetzt
@@ -637,16 +640,17 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
Unable to mount data partition. Partition may be corrupted. Press confirm to erase and reset your device.
-
+ Datenpartition konnte nicht gemounted werden. Die Partition ist möglicherweise beschädigt. Drücke Bestätigen, um das Gerät zu löschen und zurückzusetzen.
Resetting device...
This may take up to a minute.
-
+ Gerät wird zurückgesetzt...
+Dies kann bis zu einer Minute dauern.
System reset triggered. Press confirm to erase all content and settings. Press cancel to resume boot.
-
+ System-Reset ausgelöst. Drücke Bestätigen, um alle Inhalte und Einstellungen zu löschen. Drücke Abbrechen, um den Startvorgang fortzusetzen.
@@ -673,11 +677,11 @@ This may take up to a minute.
Developer
-
+ Entwickler
Firehose
-
+ Firehose
@@ -752,11 +756,11 @@ This may take up to a minute.
No custom software found at this URL.
-
+ Keine benutzerdefinierte Software unter dieser URL gefunden.
Something went wrong. Reboot the device.
-
+ Etwas ist schiefgelaufen. Starte das Gerät neu.
Select a language
@@ -764,15 +768,15 @@ This may take up to a minute.
Choose Software to Install
-
+ Wähle die zu installierende Software
openpilot
- openpilot
+ openpilot
Custom Software
-
+ Benutzerdefinierte Software
@@ -923,23 +927,23 @@ This may take up to a minute.
failed to check for update
-
+ Update-Prüfung fehlgeschlagen
up to date, last checked %1
-
+ Auf dem neuesten Stand, zuletzt geprüft am %1
DOWNLOAD
-
+ HERUNTERLADEN
update available
-
+ Update verfügbar
never
-
+ nie
@@ -1000,11 +1004,11 @@ This may take up to a minute.
Welcome to openpilot
-
+ Willkommen bei openpilot
You must accept the Terms and Conditions to use openpilot. Read the latest terms at <span style='color: #465BEA;'>https://comma.ai/terms</span> before continuing.
-
+ Du musst die Nutzungsbedingungen akzeptieren, um openpilot zu verwenden. Lies die aktuellen Bedingungen unter <span style='color: #465BEA;'>https://comma.ai/terms</span>, bevor du fortfährst.
@@ -1071,51 +1075,51 @@ This may take up to a minute.
Aggressive
-
+ Aggressiv
Standard
-
+ Standard
Relaxed
-
+ Entspannt
Driving Personality
-
+ Fahrstil
End-to-End Longitudinal Control
-
+ Ende-zu-Ende Längsregelung
openpilot longitudinal control may come in a future update.
-
+ Die openpilot Längsregelung könnte in einem zukünftigen Update verfügbar sein.
An alpha version of openpilot longitudinal control can be tested, along with Experimental mode, on non-release branches.
-
+ Eine Alpha-Version der openpilot Längsregelung kann zusammen mit dem Experimentellen Modus auf non-stable Branches getestet werden.
Enable the openpilot longitudinal control (alpha) toggle to allow Experimental mode.
-
+ Aktiviere den Schalter für openpilot Längsregelung (Alpha), um den Experimentellen Modus zu erlauben.
Standard is recommended. In aggressive mode, openpilot will follow lead cars closer and be more aggressive with the gas and brake. In relaxed mode openpilot will stay further away from lead cars. On supported cars, you can cycle through these personalities with your steering wheel distance button.
-
+ Standard wird empfohlen. Im aggressiven Modus folgt openpilot vorausfahrenden Fahrzeugen enger und ist beim Gasgeben und Bremsen aggressiver. Im entspannten Modus hält openpilot mehr Abstand zu vorausfahrenden Fahrzeugen. Bei unterstützten Fahrzeugen kannst du mit der Abstandstaste am Lenkrad zwischen diesen Fahrstilen wechseln.
The driving visualization will transition to the road-facing wide-angle camera at low speeds to better show some turns. The Experimental mode logo will also be shown in the top right corner.
-
+ Die Fahrvisualisierung wechselt bei niedrigen Geschwindigkeiten auf die nach vorne gerichtete Weitwinkelkamera, um Kurven besser darzustellen. Das Logo des Experimentellen Modus wird außerdem oben rechts angezeigt.
Always-On Driver Monitoring
-
+ Dauerhaft aktive Fahrerüberwachung
Enable driver monitoring even when openpilot is not engaged.
-
+ Fahrerüberwachung auch aktivieren, wenn openpilot nicht aktiv ist.
@@ -1157,15 +1161,15 @@ This may take up to a minute.
WiFiPromptWidget
Open
-
+ Öffnen
Maximize your training data uploads to improve openpilot's driving models.
-
+ Maximiere deine Trainingsdaten-Uploads, um die Fahrmodelle von openpilot zu verbessern.
<span style='font-family: "Noto Color Emoji";'>🔥</span> Firehose Mode <span style='font-family: Noto Color Emoji;'>🔥</span>
-
+ <span style='font-family: "Noto Color Emoji";'>🔥</span> Firehose-Modus <span style='font-family: Noto Color Emoji;'>🔥</span>
diff --git a/selfdrive/ui/translations/main_es.ts b/selfdrive/ui/translations/main_es.ts
index 235051bb73..a2d095c064 100644
--- a/selfdrive/ui/translations/main_es.ts
+++ b/selfdrive/ui/translations/main_es.ts
@@ -137,11 +137,11 @@
Enable ADB
-
+ Activar ADB
ADB (Android Debug Bridge) allows connecting to your device over USB or over the network. See https://docs.comma.ai/how-to/connect-to-comma for more info.
-
+ ADB (Android Debug Bridge) permite conectar a su dispositivo por USB o por red. Visite https://docs.comma.ai/how-to/connect-to-comma para más información.
@@ -309,37 +309,39 @@
FirehosePanel
🔥 Firehose Mode 🔥
-
+ 🔥 Modo Firehose 🔥
openpilot learns to drive by watching humans, like you, drive.
Firehose Mode allows you to maximize your training data uploads to improve openpilot's driving models. More data means bigger models, which means better Experimental Mode.
-
+ openpilot aprende a conducir observando a humanos, como tú, conducir.
+
+El Modo Firehose te permite maximizar las subidas de datos de entrenamiento para mejorar los modelos de conducción de openpilot. Más datos significan modelos más grandes, lo que significa un mejor Modo Experimental.
Firehose Mode: ACTIVE
-
+ Modo Firehose: ACTIVO
ACTIVE
-
-
-
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to unmetered network
-
+ ACTIVO
For maximum effectiveness, bring your device inside and connect to a good USB-C adapter and Wi-Fi weekly.<br><br>Firehose Mode can also work while you're driving if connected to a hotspot or unlimited SIM card.<br><br><br><b>Frequently Asked Questions</b><br><br><i>Does it matter how or where I drive?</i> Nope, just drive as you normally would.<br><br><i>Do all of my segments get pulled in Firehose Mode?</i> No, we selectively pull a subset of your segments.<br><br><i>What's a good USB-C adapter?</i> Any fast phone or laptop charger should be fine.<br><br><i>Does it matter which software I run?</i> Yes, only upstream openpilot (and particular forks) are able to be used for training.
-
+ Para máxima efectividad, traiga su dispositivo adentro y conéctelo a un buen adaptador USB-C y Wi-Fi semanalmente.<br><br>El Modo Firehose también puede funcionar mientras conduce si está conectado a un punto de acceso o tarjeta SIM ilimitada.<br><br><br><b>Preguntas Frecuentes</b><br><br><i>¿Importa cómo o dónde conduzco?</i> No, solo conduzca como lo haría normalmente.<br><br><i>¿Se extraen todos mis segmentos en el Modo Firehose?</i> No, seleccionamos selectivamente un subconjunto de sus segmentos.<br><br><i>¿Qué es un buen adaptador USB-C?</i> Cualquier cargador rápido de teléfono o portátil debería funcionar.<br><br><i>¿Importa qué software ejecuto?</i> Sí, solo el openpilot original (y forks específicos) pueden usarse para el entrenamiento.
<b>%n segment(s)</b> of your driving is in the training dataset so far.
-
-
-
+
+ <b>%n segmento</b> de tu conducción está en el conjunto de datos de entrenamiento hasta ahora.
+ <b>%n segmentos</b> de tu conducción están en el conjunto de datos de entrenamiento hasta ahora.
+
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to an unmetered network
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVO</span>: conéctate a una red sin límite de datos
+
HudRenderer
@@ -679,7 +681,7 @@ Esto puede tardar un minuto.
Firehose
-
+ Firehose
@@ -1000,11 +1002,11 @@ Esto puede tardar un minuto.
Welcome to openpilot
-
+ Bienvenido a openpilot
You must accept the Terms and Conditions to use openpilot. Read the latest terms at <span style='color: #465BEA;'>https://comma.ai/terms</span> before continuing.
-
+ Debe aceptar los Términos y Condiciones para usar openpilot. Lea los términos más recientes en <span style='color: #465BEA;'>https://comma.ai/terms</span> antes de continuar.
@@ -1157,15 +1159,15 @@ Esto puede tardar un minuto.
WiFiPromptWidget
Open
-
+ Abrir
Maximize your training data uploads to improve openpilot's driving models.
-
+ Maximice sus cargas de datos de entrenamiento para mejorar los modelos de conducción de openpilot.
<span style='font-family: "Noto Color Emoji";'>🔥</span> Firehose Mode <span style='font-family: Noto Color Emoji;'>🔥</span>
-
+ <span style='font-family: "Noto Color Emoji";'>🔥</span> Modo Firehose <span style='font-family: Noto Color Emoji;'>🔥</span>
diff --git a/selfdrive/ui/translations/main_fr.ts b/selfdrive/ui/translations/main_fr.ts
index 4ed97e2338..673056bf3b 100644
--- a/selfdrive/ui/translations/main_fr.ts
+++ b/selfdrive/ui/translations/main_fr.ts
@@ -325,10 +325,6 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
ACTIVE
-
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to unmetered network
-
-
For maximum effectiveness, bring your device inside and connect to a good USB-C adapter and Wi-Fi weekly.<br><br>Firehose Mode can also work while you're driving if connected to a hotspot or unlimited SIM card.<br><br><br><b>Frequently Asked Questions</b><br><br><i>Does it matter how or where I drive?</i> Nope, just drive as you normally would.<br><br><i>Do all of my segments get pulled in Firehose Mode?</i> No, we selectively pull a subset of your segments.<br><br><i>What's a good USB-C adapter?</i> Any fast phone or laptop charger should be fine.<br><br><i>Does it matter which software I run?</i> Yes, only upstream openpilot (and particular forks) are able to be used for training.
@@ -340,6 +336,10 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
+
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to an unmetered network
+
+
HudRenderer
diff --git a/selfdrive/ui/translations/main_ja.ts b/selfdrive/ui/translations/main_ja.ts
index 7c67d83020..da99fdd6e7 100644
--- a/selfdrive/ui/translations/main_ja.ts
+++ b/selfdrive/ui/translations/main_ja.ts
@@ -315,30 +315,32 @@
openpilot learns to drive by watching humans, like you, drive.
Firehose Mode allows you to maximize your training data uploads to improve openpilot's driving models. More data means bigger models, which means better Experimental Mode.
-
+ openpilotは人間であるあなたの運転から学び、AI学習します。
+
+Firehoseモードを有効にすると、学習データを最大限アップロードし、openpilotの運転モデルを向上させることができます。より多くのデータはより大きなモデルとなり、Experimentalモードの精度を向上させます。
Firehose Mode: ACTIVE
-
+ Firehoseモード: 作動中
ACTIVE
-
-
-
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to unmetered network
-
+ 動作中
For maximum effectiveness, bring your device inside and connect to a good USB-C adapter and Wi-Fi weekly.<br><br>Firehose Mode can also work while you're driving if connected to a hotspot or unlimited SIM card.<br><br><br><b>Frequently Asked Questions</b><br><br><i>Does it matter how or where I drive?</i> Nope, just drive as you normally would.<br><br><i>Do all of my segments get pulled in Firehose Mode?</i> No, we selectively pull a subset of your segments.<br><br><i>What's a good USB-C adapter?</i> Any fast phone or laptop charger should be fine.<br><br><i>Does it matter which software I run?</i> Yes, only upstream openpilot (and particular forks) are able to be used for training.
-
+ 最大の効果を得るためにはデバイスを屋内に持ち込み、大容量のUSB-C充電器とWi-Fiに毎週接続してください。<br><br>Firehoseモードは公衆無線LANや大容量契約のSIMカードに接続していれば、運転中でも動作します。<br><br><br><b>よくある質問(FAQ)</b><br><br><i>運転のやり方や走る場所は重要ですか？</i> いいえ、普段どおりに運転するだけで大丈夫です。<br><br><i>Firehoseモードでは全てのデータがアップロードされますか？</i> いいえ、アップロードするデータを選ぶことができます。<br><br><i>大容量のUSB-C充電器とは何ですか？</i> スマートフォンやノートパソコンを高速に充電できるものを使って下さい。<br><br><i>どのフォークを使うかは重要ですか？</i>はい、トレーニングには公式のopenpilot(および特定のフォーク)のみが使用できます。
<b>%n segment(s)</b> of your driving is in the training dataset so far.
-
-
+
+ あなたの運転の<b>%nセグメント</b>がこれまでのトレーニングデータに含まれています。
+
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to an unmetered network
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>動作停止</span>: 大容量のネットワークに接続してください
+
HudRenderer
@@ -945,7 +947,7 @@ This may take up to a minute.
Warning: This grants SSH access to all public keys in your GitHub settings. Never enter a GitHub username other than your own. A comma employee will NEVER ask you to add their GitHub username.
- 警告: これは、GitHub の設定にあるすべての公開鍵への SSH アクセスを許可するものです。自分以外の GitHub のユーザー名を入力しないでください。commaのスタッフが GitHub のユーザー名を追加するようお願いすることはありません。
+ 警告: これはGitHubの設定にあるすべての公開鍵への SSH アクセスを許可するものです。自分以外のGitHubユーザー名を入力しないでください。commaのスタッフがGitHubのユーザー名を追加するようお願いすることはありません。
ADD
@@ -953,7 +955,7 @@ This may take up to a minute.
Enter your GitHub username
- GitHub のユーザー名を入力してください
+ GitHubのユーザー名を入力してください
LOADING
@@ -995,18 +997,18 @@ This may take up to a minute.
Welcome to openpilot
-
+ openpilotへようこそ
You must accept the Terms and Conditions to use openpilot. Read the latest terms at <span style='color: #465BEA;'>https://comma.ai/terms</span> before continuing.
-
+ openpilotを使用するには利用規約に同意する必要があります。続行する前に最新の規約を以下でご確認ください: <span style='color: #465BEA;'>https://comma.ai/terms</span>
TogglesPanel
Enable openpilot
- openpilot を有効化
+ openpilotを有効化
Use the openpilot system for adaptive cruise control and lane keep driver assistance. Your attention is required at all times to use this feature. Changing this setting takes effect when the car is powered off.
@@ -1014,7 +1016,7 @@ This may take up to a minute.
Enable Lane Departure Warnings
- 車線逸脱警報機能の有効化
+ 車線逸脱警報の有効化
Receive alerts to steer back into the lane when your vehicle drifts over a detected lane line without a turn signal activated while driving over 31 mph (50 km/h).
diff --git a/selfdrive/ui/translations/main_ko.ts b/selfdrive/ui/translations/main_ko.ts
index 5abc6ce9b2..1d8d76f219 100644
--- a/selfdrive/ui/translations/main_ko.ts
+++ b/selfdrive/ui/translations/main_ko.ts
@@ -102,7 +102,7 @@
DeclinePage
You must accept the Terms and Conditions in order to use openpilot.
- openpilot을 사용하려면 이용약관에 동의해야 합니다.
+ 오픈파일럿을 사용하려면 이용약관에 동의해야 합니다.
Back
@@ -121,19 +121,19 @@
Longitudinal Maneuver Mode
- 롱컨 제어 모드
+ 가감속 제어 조작 모드
openpilot Longitudinal Control (Alpha)
- openpilot 가감속 제어 (알파)
+ 오픈파일럿 가감속 제어 (알파)
WARNING: openpilot longitudinal control is in alpha for this car and will disable Automatic Emergency Braking (AEB).
- 경고: openpilot 가감속 제어는 알파 기능으로 차량의 자동긴급제동(AEB)기능이 작동하지 않습니다.
+ 경고: 오픈파일럿 가감속 제어는 알파 기능으로 차량의 자동긴급제동(AEB)기능이 작동하지 않습니다.
On this car, openpilot defaults to the car's built-in ACC instead of openpilot's longitudinal control. Enable this to switch to openpilot longitudinal control. Enabling Experimental mode is recommended when enabling openpilot longitudinal control alpha.
- 이 차량에서 openpilot은 openpilot 가감속 제어 대신 기본적으로 차량의 ACC로 가감속을 제어합니다. openpilot 가감속 제어로 전환하려면 이 기능을 활성화하세요. openpilot 가감속 제어 알파 기능을 활성화하는 경우 실험 모드 활성화를 권장합니다.
+ 이 차량에서 오픈파일럿은 오픈파일럿 가감속 제어 대신 기본적으로 차량의 ACC로 가감속을 제어합니다. 오픈파일럿 가감속 제어로 전환하려면 이 기능을 활성화하세요. 오픈파일럿 가감속 제어 알파 기능을 활성화하는 경우 실험 모드 활성화를 권장합니다.
Enable ADB
@@ -192,7 +192,7 @@
Review the rules, features, and limitations of openpilot
- openpilot의 규칙, 기능 및 제한 다시 확인
+ 오픈파일럿의 규칙, 기능 및 제한 다시 확인
Are you sure you want to review the training guide?
@@ -228,7 +228,7 @@
openpilot requires the device to be mounted within 4° left or right and within 5° up or 9° down. openpilot is continuously calibrating, resetting is rarely required.
- openpilot 장치는 좌우 4°, 위로 5°, 아래로 9° 이내 각도로 장착되어야 합니다. openpilot은 지속적으로 자동 보정되며 재설정은 거의 필요하지 않습니다.
+ 오픈파일럿 장치는 좌우 4°, 위로 5°, 아래로 9° 이내 각도로 장착되어야 합니다. 오픈파일럿은 지속적으로 자동 보정되며 재설정은 거의 필요하지 않습니다.
Your device is pointed %1° %2 and %3° %4.
@@ -317,7 +317,7 @@
Firehose Mode allows you to maximize your training data uploads to improve openpilot's driving models. More data means bigger models, which means better Experimental Mode.
오픈파일럿은 여러분과 같은 사람이 운전하는 모습을 보면서 운전하는 법을 배웁니다.
-파이어호스 모드를 사용하면 훈련 데이터 업로드를 최대화하여 오픈파일럿의 주행 모델을 개선할 수 있습니다. 더 많은 데이터는 더 큰 모델을 의미하며, 이는 더 나은 실험 모드를 의미합니다.
+파이어호스 모드를 사용하면 학습 데이터 업로드를 최대화하여 오픈파일럿의 주행 모델을 개선할 수 있습니다. 더 많은 데이터는 더 큰 모델을 의미하며, 이는 더 나은 실험 모드를 의미합니다.
Firehose Mode: ACTIVE
@@ -325,22 +325,22 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
ACTIVE
- 활성화
-
-
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to unmetered network
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>비활성</span>: 무제한 네트워크에 연결
+ 활성 상태
For maximum effectiveness, bring your device inside and connect to a good USB-C adapter and Wi-Fi weekly.<br><br>Firehose Mode can also work while you're driving if connected to a hotspot or unlimited SIM card.<br><br><br><b>Frequently Asked Questions</b><br><br><i>Does it matter how or where I drive?</i> Nope, just drive as you normally would.<br><br><i>Do all of my segments get pulled in Firehose Mode?</i> No, we selectively pull a subset of your segments.<br><br><i>What's a good USB-C adapter?</i> Any fast phone or laptop charger should be fine.<br><br><i>Does it matter which software I run?</i> Yes, only upstream openpilot (and particular forks) are able to be used for training.
- 최대한의 효과를 얻으려면 매주 장치를 실내로 가져와 좋은 USB-C 케이블에 연결하고 Wi-Fi에 연결하세요.<br><br>파이어호스 모드는 핫스팟 또는 무제한 SIM 카드에 연결된 경우에는 운전 중에도 작동할 수 있습니다.<br><br><br><b>자주 묻는 질문</b><br><br><i>운전 방법이나 장소가 중요한가요?</i> 아니요, 평소처럼 운전하시면 됩니다.<br><br><i>파이어호스 모드에서 제 모든 구간을 가져오나요?.<br><br><i> 아니요, 저희는 여러분의 구간 중 일부를 선별적으로 가져옵니다.<br><br><i>좋은 USB-C 케이블은 무엇인가요?</i> 휴대폰이나 노트북 고속 충전기가 있으면 됩니다.<br><br><i>어떤 소프트웨어를 실행하는지가 중요한가요?</i> 예, 오직 공식 openpilot의 특정 포크만 트레이닝에 사용할 수 있습니다.
+ 최대한의 효과를 얻으려면 매주 장치를 실내로 가져와 좋은 USB-C 충전기와 Wi-Fi에 연결하세요.<br><br>파이어호스 모드는 핫스팟 또는 무제한 네트워크에 연결된 경우 주행 중에도 작동할 수 있습니다.<br><br><br><b>자주 묻는 질문</b><br><br><i>운전 방법이나 장소가 중요한가요?</i> 아니요, 평소처럼 운전하시면 됩니다.<br><br><i>파이어호스 모드에서 제 모든 구간을 가져오나요?<br><br><i> 아니요, 저희는 여러분의 구간 중 일부를 선별적으로 가져옵니다.<br><br><i>좋은 USB-C 충전기는 무엇인가요?</i> 휴대폰이나 노트북충전이 가능한 고속 충전기이면 괜찮습니다.<br><br><i>어떤 소프트웨어를 실행하는지가 중요한가요?</i> 예, 오직 공식 오픈파일럿의 특정 포크만 트레이닝에 사용할 수 있습니다.
<b>%n segment(s)</b> of your driving is in the training dataset so far.
-
-
+
+ <b>%n 구간</b> 의 운전이 지금까지의 학습 데이터셋에 포함되어 있습니다.
+
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to an unmetered network
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>비활성 상태</span>: 무제한 네트워크에 연결 하세요
+
HudRenderer
@@ -411,11 +411,11 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
OffroadAlert
Immediately connect to the internet to check for updates. If you do not connect to the internet, openpilot won't engage in %1
- 즉시 인터넷에 연결하여 업데이트를 확인하세요. 인터넷에 연결되어 있지 않으면 %1 이후에는 openpilot이 활성화되지 않습니다.
+ 즉시 인터넷에 연결하여 업데이트를 확인하세요. 인터넷에 연결되어 있지 않으면 %1 이후에는 오픈파일럿이 활성화되지 않습니다.
Connect to internet to check for updates. openpilot won't automatically start until it connects to internet to check for updates.
- 업데이트를 확인하려면 인터넷에 연결하세요. openpilot은 업데이트를 확인하기 위해 인터넷에 연결할 때까지 자동으로 시작되지 않습니다.
+ 업데이트 확인을 위해 인터넷 연결이 필요합니다. 오픈파일럿은 업데이트 확인을 위해 인터넷에 연결될 때까지 자동으로 시작되지 않습니다.
Unable to download updates
@@ -445,15 +445,15 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
openpilot was unable to identify your car. Your car is either unsupported or its ECUs are not recognized. Please submit a pull request to add the firmware versions to the proper vehicle. Need help? Join discord.comma.ai.
- openpilot이 차량을 식별할 수 없습니다. 지원되지 않는 차량이거나 ECU가 인식되지 않습니다. 해당 차량에 맞는 펌웨어 버전을 추가하려면 PR을 제출하세요. 도움이 필요하시면 discord.comma.ai에 가입하세요.
+ 오픈파일럿이 차량을 식별할 수 없습니다. 지원되지 않는 차량이거나 ECU가 인식되지 않습니다. 해당 차량에 맞는 펌웨어 버전을 추가하려면 PR을 제출하세요. 도움이 필요하시면 discord.comma.ai에 참여하세요.
openpilot detected a change in the device's mounting position. Ensure the device is fully seated in the mount and the mount is firmly secured to the windshield.
- openpilot 장치의 장착 위치가 변경되었습니다. 장치가 마운트에 완전히 장착되고 마운트가 앞유리에 단단히 고정되었는지 확인하세요.
+ 오픈파일럿 장치의 장착 위치가 변경되었습니다. 장치가 마운트에 완전히 장착되고 마운트가 앞유리에 단단히 고정되었는지 확인하세요.
Device temperature too high. System cooling down before starting. Current internal component temperature: %1
- 장치의 온도가 너무 높습니다. 시작 전에 온도를 낮춰주세요. 현재 내부 구성 요소 온도: %1
+ 장치 온도가 너무 높습니다. 시작하기 전에 시스템을 냉각하고 있습니다. 현재 내부 구성 요소 온도: %1
@@ -536,7 +536,7 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
Become a comma prime member at connect.comma.ai
- connect.comma.ai에 접속하여 comma prime 회원으로 등록하세요
+ connect.comma.ai에서 comma prime 사용자로 등록하세요
PRIME FEATURES:
@@ -552,7 +552,7 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
1 year of drive storage
- 1년간 드라이브 로그 저장
+ 1년간 주행 로그 저장
Remote snapshots
@@ -582,7 +582,7 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
openpilot
- openpilot
+ 오픈파일럿
%n minute(s) ago
@@ -767,7 +767,7 @@ This may take up to a minute.
openpilot
- openpilot
+ 오픈파일럿
Custom Software
@@ -997,7 +997,7 @@ This may take up to a minute.
Welcome to openpilot
- 오픈 파일럿에 오신 것을 환영합니다.
+ 오픈파일럿에 오신 것을 환영합니다.
You must accept the Terms and Conditions to use openpilot. Read the latest terms at <span style='color: #465BEA;'>https://comma.ai/terms</span> before continuing.
@@ -1008,11 +1008,11 @@ This may take up to a minute.
TogglesPanel
Enable openpilot
- openpilot 사용
+ 오픈파일럿 사용
Use the openpilot system for adaptive cruise control and lane keep driver assistance. Your attention is required at all times to use this feature. Changing this setting takes effect when the car is powered off.
- 어댑티브 크루즈 컨트롤 및 차로 유지 보조를 위해 openpilot 시스템을 사용할 수 있습니다. 이 기능을 사용할 때에는 언제나 주의를 기울여야 합니다. 설정을 변경하면 차량 시동이 꺼졌을 때 적용됩니다.
+ 오픈파일럿 시스템을 사용하여 어댑티브 크루즈 컨트롤과 차로 유지 보조 기능을 활용하십시오. 이 기능을 사용할 때에는 항상 주의를 기울여야 합니다. 설정 변경은 차량을 재시동해야 적용됩니다.
Enable Lane Departure Warnings
@@ -1044,7 +1044,7 @@ This may take up to a minute.
When enabled, pressing the accelerator pedal will disengage openpilot.
- 활성화된 경우 가속 페달을 밟으면 openpilot이 해제됩니다.
+ 활성화된 경우 가속 페달을 밟으면 오픈파일럿이 해제됩니다.
Experimental Mode
@@ -1052,11 +1052,11 @@ This may take up to a minute.
openpilot defaults to driving in <b>chill mode</b>. Experimental mode enables <b>alpha-level features</b> that aren't ready for chill mode. Experimental features are listed below:
- openpilot은 기본적으로 <b>안정 모드</b>로 주행합니다. 실험 모드는 안정화되지 않은 <b>알파 수준의 기능</b>을 활성화합니다. 실험 모드의 기능은 아래와 같습니다:
+ 오픈파일럿은 기본적으로 <b>안정 모드</b>로 주행합니다. 실험 모드는 안정화되지 않은 <b>알파 수준의 기능</b>을 활성화합니다. 실험 모드의 기능은 아래와 같습니다:
Let the driving model control the gas and brakes. openpilot will drive as it thinks a human would, including stopping for red lights and stop signs. Since the driving model decides the speed to drive, the set speed will only act as an upper bound. This is an alpha quality feature; mistakes should be expected.
- openpilot의 주행모델이 가감속을 제어합니다. openpilot은 신호등과 정지 표지판을 보고 멈추는 것을 포함하여 인간이 운전하는 것처럼 생각하고 주행합니다. 주행 모델이 주행할 속도를 결정하므로 설정된 속도는 최대 주행 속도로만 기능합니다. 이 기능은 알파 수준이므로 사용에 각별히 주의해야 합니다.
+ 주행모델이 가감속을 제어하도록 합니다. 오픈파일럿은 빨간불과 정지신호를 보고 정지하는것을 포함하여 사람이 운전하는 방식대로 작동하며 주행 모델이 속도를 결정하므로 설정 속도는 최대 제한 속도로만 작동합니다. 이는 알파 수준의 기능이며 오류가 발생할수있으니 사용에 주의해야 합니다.
New Driving Visualization
@@ -1064,11 +1064,11 @@ This may take up to a minute.
Experimental mode is currently unavailable on this car since the car's stock ACC is used for longitudinal control.
- 차량에 장착된 ACC로 가감속을 제어하기 때문에 현재 이 차량에서는 실험 모드를 사용할 수 없습니다.
+ 차량의 ACC가 가감속 제어에 사용되기 때문에, 이 차량에서는 실험 모드를 사용할 수 없습니다.
openpilot longitudinal control may come in a future update.
- openpilot 가감속 제어는 향후 업데이트에서 지원될 수 있습니다.
+ 오픈파일럿 가감속 제어는 향후 업데이트에서 지원될 수 있습니다.
Aggressive
@@ -1088,11 +1088,11 @@ This may take up to a minute.
An alpha version of openpilot longitudinal control can be tested, along with Experimental mode, on non-release branches.
- openpilot 가감속 제어 알파 버전은 비 릴리즈 브랜치에서 실험 모드와 함께 테스트할 수 있습니다.
+ 오픈파일럿 가감속 제어 알파 버전은 비 릴리즈 브랜치에서 실험 모드와 함께 테스트할 수 있습니다.
Enable the openpilot longitudinal control (alpha) toggle to allow Experimental mode.
- 실험 모드를 사용하려면 openpilot E2E 가감속 제어 (알파) 토글을 활성화하세요.
+ 실험 모드를 사용하려면 오픈파일럿 E2E 가감속 제어 (알파) 토글을 활성화하세요.
End-to-End Longitudinal Control
@@ -1100,7 +1100,7 @@ This may take up to a minute.
Standard is recommended. In aggressive mode, openpilot will follow lead cars closer and be more aggressive with the gas and brake. In relaxed mode openpilot will stay further away from lead cars. On supported cars, you can cycle through these personalities with your steering wheel distance button.
- 표준 모드를 권장합니다. 공격적 모드의 openpilot은 선두 차량을 더 가까이 따라가고 가감속제어를 사용하여 더욱 공격적으로 움직입니다. 편안한 모드의 openpilot은 선두 차량으로부터 더 멀리 떨어져 있습니다. 지원되는 차량에서는 스티어링 휠 거리 버튼을 사용하여 이러한 특성을 순환할 수 있습니다.
+ 표준 모드를 권장합니다. 공격적 모드의 오픈파일럿은 선두 차량을 더 가까이 따라가고 가감속제어를 사용하여 더욱 공격적으로 움직입니다. 편안한 모드의 오픈파일럿은 선두 차량으로부터 더 멀리 떨어져 있습니다. 지원되는 차량에서는 차간거리 버튼을 사용하여 이러한 특성을 순환할 수 있습니다.
The driving visualization will transition to the road-facing wide-angle camera at low speeds to better show some turns. The Experimental mode logo will also be shown in the top right corner.
@@ -1112,7 +1112,7 @@ This may take up to a minute.
Enable driver monitoring even when openpilot is not engaged.
- openpilot이 활성화되지 않은 경우에도 드라이버 모니터링을 활성화합니다.
+ 오픈파일럿이 활성화되지 않은 경우에도 드라이버 모니터링을 활성화합니다.
@@ -1158,7 +1158,7 @@ This may take up to a minute.
Maximize your training data uploads to improve openpilot's driving models.
- 훈련 데이터 업로드를 최대화하여 오픈파일럿의 주행 모델을 개선하세요.
+ 오픈파일럿의 주행 모델 개선을 위해 학습 데이터 업로드를 최대화하세요.
<span style='font-family: "Noto Color Emoji";'>🔥</span> Firehose Mode <span style='font-family: Noto Color Emoji;'>🔥</span>
diff --git a/selfdrive/ui/translations/main_pt-BR.ts b/selfdrive/ui/translations/main_pt-BR.ts
index 57b5b4ffa5..4971b7fbfa 100644
--- a/selfdrive/ui/translations/main_pt-BR.ts
+++ b/selfdrive/ui/translations/main_pt-BR.ts
@@ -327,10 +327,6 @@ O Modo Firehose permite maximizar o envio de dados de treinamento para melhorar
ACTIVE
ATIVO
-
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to unmetered network
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INATIVO</span>: conecte-se a uma rede sem restrição <br> de dados
-
For maximum effectiveness, bring your device inside and connect to a good USB-C adapter and Wi-Fi weekly.<br><br>Firehose Mode can also work while you're driving if connected to a hotspot or unlimited SIM card.<br><br><br><b>Frequently Asked Questions</b><br><br><i>Does it matter how or where I drive?</i> Nope, just drive as you normally would.<br><br><i>Do all of my segments get pulled in Firehose Mode?</i> No, we selectively pull a subset of your segments.<br><br><i>What's a good USB-C adapter?</i> Any fast phone or laptop charger should be fine.<br><br><i>Does it matter which software I run?</i> Yes, only upstream openpilot (and particular forks) are able to be used for training.
Para maior eficácia, leve seu dispositivo para dentro de casa e conecte-o a um bom adaptador USB-C e Wi-Fi semanalmente.<br><br>O Modo Firehose também pode funcionar enquanto você dirige, se estiver conectado a um hotspot ou a um chip SIM com dados ilimitados.<br><br><br><b>Perguntas Frequentes</b><br><br><i>Importa como ou onde eu dirijo?</i> Não, basta dirigir normalmente.<br><br><i>Todos os meus segmentos são enviados no Modo Firehose?</i> Não, selecionamos apenas um subconjunto dos seus segmentos.<br><br><i>Qual é um bom adaptador USB-C?</i> Qualquer carregador rápido de telefone ou laptop deve ser suficiente.<br><br><i>Importa qual software eu uso?</i> Sim, apenas o openpilot oficial (e alguns forks específicos) podem ser usados para treinamento.
@@ -342,6 +338,10 @@ O Modo Firehose permite maximizar o envio de dados de treinamento para melhorar
<b>%n segmentos</b> da sua direção estão no conjunto de dados de treinamento até agora.
+
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to an unmetered network
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INATIVO</span>: conecte-se a uma rede sem limite <br> de dados
+
HudRenderer
diff --git a/selfdrive/ui/translations/main_th.ts b/selfdrive/ui/translations/main_th.ts
index 6db0085567..aab2270a01 100644
--- a/selfdrive/ui/translations/main_th.ts
+++ b/selfdrive/ui/translations/main_th.ts
@@ -117,31 +117,31 @@
DeveloperPanel
Joystick Debug Mode
-
+ โหมดดีบักจอยสติ๊ก
Longitudinal Maneuver Mode
-
+ โหมดการควบคุมการเร่ง/เบรค
openpilot Longitudinal Control (Alpha)
- ระบบควบคุมการเร่ง/เบรคโดย openpilot (Alpha)
+ ระบบควบคุมการเร่ง/เบรคโดย openpilot (Alpha)
WARNING: openpilot longitudinal control is in alpha for this car and will disable Automatic Emergency Braking (AEB).
- คำเตือน: การควบคุมการเร่ง/เบรคโดย openpilot สำหรับรถคันนี้ยังอยู่ในสถานะ alpha และระบบเบรคฉุกเฉินอัตโนมัติ (AEB) จะถูกปิด
+ คำเตือน: การควบคุมการเร่ง/เบรคโดย openpilot สำหรับรถคันนี้ยังอยู่ในสถานะ alpha และระบบเบรคฉุกเฉินอัตโนมัติ (AEB) จะถูกปิด
On this car, openpilot defaults to the car's built-in ACC instead of openpilot's longitudinal control. Enable this to switch to openpilot longitudinal control. Enabling Experimental mode is recommended when enabling openpilot longitudinal control alpha.
- โดยปกติสำหรับรถคันนี้ openpilot จะควบคุมการเร่ง/เบรคด้วยระบบ ACC จากโรงงาน แทนการควยคุมโดย openpilot เปิดสวิตซ์นี้เพื่อให้ openpilot ควบคุมการเร่ง/เบรค แนะนำให้เปิดโหมดทดลองเมื่อต้องการให้ openpilot ควบคุมการเร่ง/เบรค ซึ่งอยู่ในสถานะ alpha
+ โดยปกติสำหรับรถคันนี้ openpilot จะควบคุมการเร่ง/เบรคด้วยระบบ ACC จากโรงงาน แทนการควยคุมโดย openpilot เปิดสวิตซ์นี้เพื่อให้ openpilot ควบคุมการเร่ง/เบรค แนะนำให้เปิดโหมดทดลองเมื่อต้องการให้ openpilot ควบคุมการเร่ง/เบรค ซึ่งอยู่ในสถานะ alpha
Enable ADB
-
+ เปิด ADB
ADB (Android Debug Bridge) allows connecting to your device over USB or over the network. See https://docs.comma.ai/how-to/connect-to-comma for more info.
-
+ ADB (Android Debug Bridge) อนุญาตให้เชื่อมต่ออุปกรณ์ของคุณผ่าน USB หรือผ่านเครือข่าย ดูข้อมูลเพิ่มเติมที่ https://docs.comma.ai/how-to/connect-to-comma
@@ -309,36 +309,38 @@
FirehosePanel
🔥 Firehose Mode 🔥
-
+ 🔥 โหมดสายยางดับเพลิง 🔥
openpilot learns to drive by watching humans, like you, drive.
Firehose Mode allows you to maximize your training data uploads to improve openpilot's driving models. More data means bigger models, which means better Experimental Mode.
-
+ openpilot เรียนรู้วิธีขับรถจากการเฝ้าดูการขับขี่ของมนุษย์เช่นคุณ
+
+โหมดสายยางดับเพลิงช่วยให้คุณอัปโหลดข้อมูลการฝึกฝนได้มากที่สุด เพื่อนำไปพัฒนาโมเดลการขับขี่ของ openpilot ข้อมูลที่มากขึ้นหมายถึงโมเดลที่ใหญ่ขึ้น และนั่นหมายถึงโหมดทดลองที่ดีขึ้น
Firehose Mode: ACTIVE
-
+ โหมดสายยางดับเพลิง: เปิดใช้งาน
ACTIVE
-
-
-
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to unmetered network
-
+ เปิดใช้งาน
For maximum effectiveness, bring your device inside and connect to a good USB-C adapter and Wi-Fi weekly.<br><br>Firehose Mode can also work while you're driving if connected to a hotspot or unlimited SIM card.<br><br><br><b>Frequently Asked Questions</b><br><br><i>Does it matter how or where I drive?</i> Nope, just drive as you normally would.<br><br><i>Do all of my segments get pulled in Firehose Mode?</i> No, we selectively pull a subset of your segments.<br><br><i>What's a good USB-C adapter?</i> Any fast phone or laptop charger should be fine.<br><br><i>Does it matter which software I run?</i> Yes, only upstream openpilot (and particular forks) are able to be used for training.
-
+ เพื่อประสิทธิภาพสูงสุด ควรนำอุปกรณ์เข้ามาข้างใน เชื่อมต่อกับอะแดปเตอร์ USB-C คุณภาพดี และ Wi-Fi สัปดาห์ละครั้ง<br><br>โหมดสายยางดับเพลิงยังสามารถทำงานระหว่างขับรถได้ หากเชื่อมต่อกับฮอตสปอตหรือซิมการ์ดที่มีเน็ตไม่จำกัด<br><br><br><b>คำถามที่พบบ่อย</b><br><br><i>วิธีการขับหรือสถานที่ขับขี่มีผลหรือไม่?</i>ไม่มีผล แค่ขับขี่ตามปกติของคุณ<br><br><i>เซกเมนต์ทั้งหมดของฉันจะถูกดึงข้อมูลในโหมดสายยางดับเพลิงหรือไม่?</i>ไม่ใช่ เราจะเลือกดึงข้อมูลเพียงบางส่วนจากเซกเมนต์ของคุณ<br><br><i>อะแดปเตอร์ USB-C แบบไหนดี?</i>ที่ชาร์จเร็วของโทรศัพท์หรือแล็ปท็อปแบบใดก็ได้ สามารถใช้ได้<br><br><i>ซอฟต์แวร์ที่ใช้มีผลหรือไม่?</i>มีผล เฉพาะ openpilot ตัวหลัก (และ fork เฉพาะบางตัว) เท่านั้น ที่สามารถนำข้อมูลไปใช้ฝึกฝนโมเดลได้
<b>%n segment(s)</b> of your driving is in the training dataset so far.
-
-
+
+ มีการขับขี่ของคุณ <b>%n เซกเมนต์</b> อยู่ในชุดข้อมูลการฝึกฝนแล้วในขณะนี้
+
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to an unmetered network
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>ไม่เปิดใช้งาน</span>: เชื่อมต่อกับเครือข่ายที่ไม่จำกัดข้อมูล
+
HudRenderer
@@ -485,11 +487,11 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
Waiting to start
-
+ รอเริ่มทำงาน
System Unresponsive
-
+ ระบบไม่ตอบสนอง
@@ -512,7 +514,7 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
Please connect to Wi-Fi to complete initial pairing
-
+ กรุณาเชื่อมต่อ Wi-Fi เพื่อทำการจับคู่ครั้งแรกให้เสร็จสิ้น
@@ -554,7 +556,7 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
Remote snapshots
-
+ ภาพถ่ายระยะไกล
@@ -670,11 +672,11 @@ This may take up to a minute.
Developer
-
+ นักพัฒนา
Firehose
-
+ สายยางดับเพลิง
@@ -995,11 +997,11 @@ This may take up to a minute.
Welcome to openpilot
-
+ ยินดีต้อนรับสู่ openpilot
You must accept the Terms and Conditions to use openpilot. Read the latest terms at <span style='color: #465BEA;'>https://comma.ai/terms</span> before continuing.
-
+ คุณต้องยอมรับข้อกำหนดและเงื่อนไขเพื่อใช้งาน openpilot อ่านข้อกำหนดล่าสุดได้ที่ <span style='color: #465BEA;'>https://comma.ai/terms</span> ก่อนดำเนินการต่อ
@@ -1106,11 +1108,11 @@ This may take up to a minute.
Always-On Driver Monitoring
-
+ การเฝ้าระวังผู้ขับขี่ตลอดเวลา
Enable driver monitoring even when openpilot is not engaged.
-
+ เปิดใช้งานการเฝ้าระวังผู้ขับขี่แม้เมื่อ openpilot ไม่ได้เข้าควบคุมอยู่
@@ -1152,15 +1154,15 @@ This may take up to a minute.
WiFiPromptWidget
Open
-
+ เปิด
Maximize your training data uploads to improve openpilot's driving models.
-
+ อัปโหลดข้อมูลการฝึกฝนให้ได้มากที่สุด เพื่อพัฒนาโมเดลการขับขี่ของ openpilot
<span style='font-family: "Noto Color Emoji";'>🔥</span> Firehose Mode <span style='font-family: Noto Color Emoji;'>🔥</span>
-
+ <span style='font-family: "Noto Color Emoji";'>🔥</span> โหมดสายยางดับเพลิง <span style='font-family: Noto Color Emoji;'>🔥</span>
diff --git a/selfdrive/ui/translations/main_tr.ts b/selfdrive/ui/translations/main_tr.ts
index e640eeab4d..0b0e24dcf4 100644
--- a/selfdrive/ui/translations/main_tr.ts
+++ b/selfdrive/ui/translations/main_tr.ts
@@ -325,10 +325,6 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
ACTIVE
-
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to unmetered network
-
-
For maximum effectiveness, bring your device inside and connect to a good USB-C adapter and Wi-Fi weekly.<br><br>Firehose Mode can also work while you're driving if connected to a hotspot or unlimited SIM card.<br><br><br><b>Frequently Asked Questions</b><br><br><i>Does it matter how or where I drive?</i> Nope, just drive as you normally would.<br><br><i>Do all of my segments get pulled in Firehose Mode?</i> No, we selectively pull a subset of your segments.<br><br><i>What's a good USB-C adapter?</i> Any fast phone or laptop charger should be fine.<br><br><i>Does it matter which software I run?</i> Yes, only upstream openpilot (and particular forks) are able to be used for training.
@@ -339,6 +335,10 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
+
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to an unmetered network
+
+
HudRenderer
diff --git a/selfdrive/ui/translations/main_zh-CHS.ts b/selfdrive/ui/translations/main_zh-CHS.ts
index 4cc2d401eb..963946e4da 100644
--- a/selfdrive/ui/translations/main_zh-CHS.ts
+++ b/selfdrive/ui/translations/main_zh-CHS.ts
@@ -121,7 +121,7 @@
Longitudinal Maneuver Mode
- 纵向机动模式
+ 纵向操控测试模式
openpilot Longitudinal Control (Alpha)
@@ -327,10 +327,6 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
ACTIVE
激活中
-
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to unmetered network
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>未激活</span>：请连接至不限流量的网络
-
For maximum effectiveness, bring your device inside and connect to a good USB-C adapter and Wi-Fi weekly.<br><br>Firehose Mode can also work while you're driving if connected to a hotspot or unlimited SIM card.<br><br><br><b>Frequently Asked Questions</b><br><br><i>Does it matter how or where I drive?</i> Nope, just drive as you normally would.<br><br><i>Do all of my segments get pulled in Firehose Mode?</i> No, we selectively pull a subset of your segments.<br><br><i>What's a good USB-C adapter?</i> Any fast phone or laptop charger should be fine.<br><br><i>Does it matter which software I run?</i> Yes, only upstream openpilot (and particular forks) are able to be used for training.
为了达到最佳效果，请每周将您的设备带回室内，并连接到优质的 USB-C 充电器和 Wi-Fi。<br><br>Firehose 模式在行驶时也能运行，但需连接到移动热点或使用不限流量的 SIM 卡。<br><br><br><b>常见问题</b><br><br><i>我开车的方式或地点有影响吗？</i>不会，请像平常一样驾驶即可。<br><br><i>Firehose 模式会上传所有的驾驶片段吗？</i>不会，我们会选择性地上传部分片段。<br><br><i>什么是好的 USB-C 充电器？</i>任何快速手机或笔记本电脑充电器都应该适用。<br><br><i>我使用的软件版本有影响吗？</i>有的，只有官方 openpilot（以及特定的分支）可以用于训练。
@@ -341,6 +337,10 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
<b>目前已有 %n 段</b> 您的驾驶数据被纳入训练数据集。
+
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to an unmetered network
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>闲置</span>：请连接到不限流量的网络
+
HudRenderer
diff --git a/selfdrive/ui/translations/main_zh-CHT.ts b/selfdrive/ui/translations/main_zh-CHT.ts
index 78519f2647..1946493247 100644
--- a/selfdrive/ui/translations/main_zh-CHT.ts
+++ b/selfdrive/ui/translations/main_zh-CHT.ts
@@ -121,7 +121,7 @@
Longitudinal Maneuver Mode
- 縱向機動模式
+ 縱向操控測試模式
openpilot Longitudinal Control (Alpha)
@@ -327,10 +327,6 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
ACTIVE
啟用中
-
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to unmetered network
- <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>未啟用</span>：請連接至不限流量的網路
-
For maximum effectiveness, bring your device inside and connect to a good USB-C adapter and Wi-Fi weekly.<br><br>Firehose Mode can also work while you're driving if connected to a hotspot or unlimited SIM card.<br><br><br><b>Frequently Asked Questions</b><br><br><i>Does it matter how or where I drive?</i> Nope, just drive as you normally would.<br><br><i>Do all of my segments get pulled in Firehose Mode?</i> No, we selectively pull a subset of your segments.<br><br><i>What's a good USB-C adapter?</i> Any fast phone or laptop charger should be fine.<br><br><i>Does it matter which software I run?</i> Yes, only upstream openpilot (and particular forks) are able to be used for training.
為了達到最佳效果，請每週將您的裝置帶回室內，並連接至優質的 USB-C 充電器與 Wi-Fi。<br><br>訓練資料上傳模式在行駛時也能運作，但需連接至行動熱點或使用不限流量的 SIM 卡。<br><br><br><b>常見問題</b><br><br><i>我開車的方式或地點有影響嗎？</i> 不會，請像平常一樣駕駛即可。<br><br><i>訓練資料上傳模式會上傳所有的駕駛片段嗎？</i>不會，我們會選擇性地上傳部分片段。<br><br><i>什麼是好的 USB-C 充電器？</i>任何快速手機或筆電充電器都應該適用。<br><br><i>我使用的軟體版本有影響嗎？</i>有的，只有官方 openpilot（以及特定的分支）可以用於訓練。
@@ -341,6 +337,10 @@ Firehose Mode allows you to maximize your training data uploads to improve openp
<b>目前已有 %n 段</b> 您的駕駛數據被納入訓練資料集。
+
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>INACTIVE</span>: connect to an unmetered network
+ <span stylesheet='font-size: 60px; font-weight: bold; color: #e74c3c;'>閒置中</span>：請連接到不按流量計費的網絡
+
HudRenderer
diff --git a/system/athena/athenad.py b/system/athena/athenad.py
index b36bdb103d..5813bc90a5 100755
--- a/system/athena/athenad.py
+++ b/system/athena/athenad.py
@@ -16,7 +16,7 @@ import threading
import time
from dataclasses import asdict, dataclass, replace
from datetime import datetime
-from functools import partial
+from functools import partial, total_ordering
from queue import Queue
from typing import cast
from collections.abc import Callable
@@ -53,6 +53,7 @@ MAX_RETRY_COUNT = 30 # Try for at most 5 minutes if upload fails immediately
MAX_AGE = 31 * 24 * 3600 # seconds
WS_FRAME_SIZE = 4096
DEVICE_STATE_UPDATE_INTERVAL = 1.0 # in seconds
+DEFAULT_UPLOAD_PRIORITY = 99 # higher number = lower priority
NetworkType = log.DeviceState.NetworkType
@@ -68,13 +69,15 @@ class UploadFile:
url: str
headers: dict[str, str]
allow_cellular: bool
+ priority: int = DEFAULT_UPLOAD_PRIORITY
@classmethod
def from_dict(cls, d: dict) -> UploadFile:
- return cls(d.get("fn", ""), d.get("url", ""), d.get("headers", {}), d.get("allow_cellular", False))
+ return cls(d.get("fn", ""), d.get("url", ""), d.get("headers", {}), d.get("allow_cellular", False), d.get("priority", DEFAULT_UPLOAD_PRIORITY))
@dataclass
+@total_ordering
class UploadItem:
path: str
url: str
@@ -85,17 +88,28 @@ class UploadItem:
current: bool = False
progress: float = 0
allow_cellular: bool = False
+ priority: int = DEFAULT_UPLOAD_PRIORITY
@classmethod
def from_dict(cls, d: dict) -> UploadItem:
return cls(d["path"], d["url"], d["headers"], d["created_at"], d["id"], d["retry_count"], d["current"],
- d["progress"], d["allow_cellular"])
+ d["progress"], d["allow_cellular"], d["priority"])
+
+ def __lt__(self, other):
+ if not isinstance(other, UploadItem):
+ return NotImplemented
+ return self.priority < other.priority
+
+ def __eq__(self, other):
+ if not isinstance(other, UploadItem):
+ return NotImplemented
+ return self.priority == other.priority
dispatcher["echo"] = lambda s: s
recv_queue: Queue[str] = queue.Queue()
send_queue: Queue[str] = queue.Queue()
-upload_queue: Queue[UploadItem] = queue.Queue()
+upload_queue: Queue[UploadItem] = queue.PriorityQueue()
low_priority_send_queue: Queue[str] = queue.Queue()
log_recv_queue: Queue[str] = queue.Queue()
cancelled_uploads: set[str] = set()
@@ -398,6 +412,7 @@ def uploadFilesToUrls(files_data: list[UploadFileDict]) -> UploadFilesToUrlRespo
created_at=int(time.time() * 1000),
id=None,
allow_cellular=file.allow_cellular,
+ priority=file.priority,
)
upload_id = hashlib.sha1(str(item).encode()).hexdigest()
item = replace(item, id=upload_id)
diff --git a/system/athena/tests/test_athenad.py b/system/athena/tests/test_athenad.py
index e16e73a7ea..dd82325815 100644
--- a/system/athena/tests/test_athenad.py
+++ b/system/athena/tests/test_athenad.py
@@ -76,7 +76,7 @@ class TestAthenadMethods:
self.params.put(k, v)
self.params.put_bool("GsmMetered", True)
- athenad.upload_queue = queue.Queue()
+ athenad.upload_queue = queue.PriorityQueue()
athenad.cur_upload_items.clear()
athenad.cancelled_uploads.clear()
@@ -321,6 +321,26 @@ class TestAthenadMethods:
assert len(items) == 1
assert items[0]['current']
+ def test_list_upload_queue_priority(self):
+ priorities = (25, 50, 99, 75, 0)
+
+ for i in priorities:
+ fn = f'qlog_{i}.zst'
+ fp = self._create_file(fn)
+ item = athenad.UploadItem(
+ path=fp,
+ url=f"http://localhost:44444/{fn}",
+ headers={},
+ created_at=int(time.time()*1000),
+ id='',
+ allow_cellular=True,
+ priority=i
+ )
+ athenad.upload_queue.put_nowait(item)
+
+ for i in sorted(priorities):
+ assert athenad.upload_queue.get_nowait().priority == i
+
def test_list_upload_queue(self):
item = athenad.UploadItem(path="qlog.zst", url="http://localhost:44444/qlog.zst", headers={},
created_at=int(time.time()*1000), id='id', allow_cellular=True)
diff --git a/system/camerad/cameras/spectra.cc b/system/camerad/cameras/spectra.cc
index d12dbb2444..4535078771 100644
--- a/system/camerad/cameras/spectra.cc
+++ b/system/camerad/cameras/spectra.cc
@@ -19,7 +19,6 @@
#include "system/camerad/cameras/ife.h"
#include "system/camerad/cameras/spectra.h"
#include "system/camerad/cameras/bps_blobs.h"
-#include "third_party/linux/include/msm_media_info.h"
// ************** low level camera helpers ****************
diff --git a/system/camerad/sensors/ox03c10_registers.h b/system/camerad/sensors/ox03c10_registers.h
index 5c6282942b..bb7a1c5dd6 100644
--- a/system/camerad/sensors/ox03c10_registers.h
+++ b/system/camerad/sensors/ox03c10_registers.h
@@ -65,7 +65,6 @@ const struct i2c_random_wr_payload init_array_ox03c10[] = {
{0x3008, 0x80}, // io_pad_sel
// FSIN (frame sync) with external pulses
- {0x3822, 0x33}, // wait for pulse before first frame
{0x3009, 0x2},
{0x3015, 0x2},
{0x383E, 0x80},
@@ -73,6 +72,9 @@ const struct i2c_random_wr_payload init_array_ox03c10[] = {
{0x3882, 0x8}, {0x3883, 0x0D},
{0x3836, 0x1F}, {0x3837, 0x40},
+ // causes issues on some devices
+ //{0x3822, 0x33}, // wait for pulse before first frame
+
{0x3892, 0x44},
{0x3823, 0x41},
diff --git a/system/hardware/fan_controller.py b/system/hardware/fan_controller.py
index be93d5922a..7d5bec0509 100755
--- a/system/hardware/fan_controller.py
+++ b/system/hardware/fan_controller.py
@@ -27,7 +27,7 @@ class TiciFanController(BaseFanController):
if ignition != self.last_ignition:
self.controller.reset()
- error = 70 - cur_temp
+ error = 75 - cur_temp
fan_pwr_out = -int(self.controller.update(
error=error,
feedforward=np.interp(cur_temp, [60.0, 100.0], [0, -100])
diff --git a/system/hardware/tici/agnos.json b/system/hardware/tici/agnos.json
index 04e5fd3365..1a3cd382a9 100644
--- a/system/hardware/tici/agnos.json
+++ b/system/hardware/tici/agnos.json
@@ -56,28 +56,28 @@
},
{
"name": "boot",
- "url": "https://commadist.azureedge.net/agnosupdate/boot-0d0d4d5a32e00b46fa36180b4a96337f2a53302d8bd0faee95f8fe1063d1e24a.img.xz",
- "hash": "0d0d4d5a32e00b46fa36180b4a96337f2a53302d8bd0faee95f8fe1063d1e24a",
- "hash_raw": "0d0d4d5a32e00b46fa36180b4a96337f2a53302d8bd0faee95f8fe1063d1e24a",
+ "url": "https://commadist.azureedge.net/agnosupdate/boot-9b07cc366919890cc88bdd45c8c7e643bf66557caf9ad6a1373accc6dcacd892.img.xz",
+ "hash": "9b07cc366919890cc88bdd45c8c7e643bf66557caf9ad6a1373accc6dcacd892",
+ "hash_raw": "9b07cc366919890cc88bdd45c8c7e643bf66557caf9ad6a1373accc6dcacd892",
"size": 18479104,
"sparse": false,
"full_check": true,
"has_ab": true,
- "ondevice_hash": "47b2096995578a5078e393c33108b42756009dbb361c43c508fc93cd8bda99cc"
+ "ondevice_hash": "41d31b862fec1b87879b508c405adb9d7b5c0a3324f7350bd904f451605b06cf"
},
{
"name": "system",
- "url": "https://commadist.azureedge.net/agnosupdate/system-ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211.img.xz",
- "hash": "fbda983c40e75d8c4784a45c687f27dd27f97f7f0e9a71b4981ec2092ff68a72",
- "hash_raw": "ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211",
+ "url": "https://commadist.azureedge.net/agnosupdate/system-02a6f40cc305faf703ab8f993a49d720043e4df1c0787d60dcf87eedb9f2ffde.img.xz",
+ "hash": "c56256a64e6d7e16886e39a4263ffb686ed0f03d3a665c3552f54a39723f8824",
+ "hash_raw": "02a6f40cc305faf703ab8f993a49d720043e4df1c0787d60dcf87eedb9f2ffde",
"size": 4404019200,
"sparse": true,
"full_check": false,
"has_ab": true,
- "ondevice_hash": "428c744458d5f35199aab96a0928876c9deeff3e753e95044291408ba244f0af",
+ "ondevice_hash": "ed2e11f52beb8559223bf9fb989fd4ef5d2ce66eeb11ae0053fff8e41903a533",
"alt": {
- "hash": "ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211",
- "url": "https://commadist.azureedge.net/agnosupdate/system-ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211.img",
+ "hash": "02a6f40cc305faf703ab8f993a49d720043e4df1c0787d60dcf87eedb9f2ffde",
+ "url": "https://commadist.azureedge.net/agnosupdate/system-02a6f40cc305faf703ab8f993a49d720043e4df1c0787d60dcf87eedb9f2ffde.img",
"size": 4404019200
}
}
diff --git a/system/hardware/tici/all-partitions.json b/system/hardware/tici/all-partitions.json
index 4d15e76b0e..4e24b229d4 100644
--- a/system/hardware/tici/all-partitions.json
+++ b/system/hardware/tici/all-partitions.json
@@ -339,62 +339,62 @@
},
{
"name": "boot",
- "url": "https://commadist.azureedge.net/agnosupdate/boot-0d0d4d5a32e00b46fa36180b4a96337f2a53302d8bd0faee95f8fe1063d1e24a.img.xz",
- "hash": "0d0d4d5a32e00b46fa36180b4a96337f2a53302d8bd0faee95f8fe1063d1e24a",
- "hash_raw": "0d0d4d5a32e00b46fa36180b4a96337f2a53302d8bd0faee95f8fe1063d1e24a",
+ "url": "https://commadist.azureedge.net/agnosupdate/boot-9b07cc366919890cc88bdd45c8c7e643bf66557caf9ad6a1373accc6dcacd892.img.xz",
+ "hash": "9b07cc366919890cc88bdd45c8c7e643bf66557caf9ad6a1373accc6dcacd892",
+ "hash_raw": "9b07cc366919890cc88bdd45c8c7e643bf66557caf9ad6a1373accc6dcacd892",
"size": 18479104,
"sparse": false,
"full_check": true,
"has_ab": true,
- "ondevice_hash": "47b2096995578a5078e393c33108b42756009dbb361c43c508fc93cd8bda99cc"
+ "ondevice_hash": "41d31b862fec1b87879b508c405adb9d7b5c0a3324f7350bd904f451605b06cf"
},
{
"name": "system",
- "url": "https://commadist.azureedge.net/agnosupdate/system-ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211.img.xz",
- "hash": "fbda983c40e75d8c4784a45c687f27dd27f97f7f0e9a71b4981ec2092ff68a72",
- "hash_raw": "ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211",
+ "url": "https://commadist.azureedge.net/agnosupdate/system-02a6f40cc305faf703ab8f993a49d720043e4df1c0787d60dcf87eedb9f2ffde.img.xz",
+ "hash": "c56256a64e6d7e16886e39a4263ffb686ed0f03d3a665c3552f54a39723f8824",
+ "hash_raw": "02a6f40cc305faf703ab8f993a49d720043e4df1c0787d60dcf87eedb9f2ffde",
"size": 4404019200,
"sparse": true,
"full_check": false,
"has_ab": true,
- "ondevice_hash": "428c744458d5f35199aab96a0928876c9deeff3e753e95044291408ba244f0af",
+ "ondevice_hash": "ed2e11f52beb8559223bf9fb989fd4ef5d2ce66eeb11ae0053fff8e41903a533",
"alt": {
- "hash": "ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211",
- "url": "https://commadist.azureedge.net/agnosupdate/system-ff2da7bc34a1ad8e2831a13a49685243957a51b762d8f28e14e98ac90e84d211.img",
+ "hash": "02a6f40cc305faf703ab8f993a49d720043e4df1c0787d60dcf87eedb9f2ffde",
+ "url": "https://commadist.azureedge.net/agnosupdate/system-02a6f40cc305faf703ab8f993a49d720043e4df1c0787d60dcf87eedb9f2ffde.img",
"size": 4404019200
}
},
{
"name": "userdata_90",
- "url": "https://commadist.azureedge.net/agnosupdate/userdata_90-17f46ba0d0eec10cf14804c84d9bcf4f6fa864074f1b90ff2fb4873399d64b1a.img.xz",
- "hash": "1442ae218daff960783bc493a32dd489fa787e4025c64fa3132f48b1e627647f",
- "hash_raw": "17f46ba0d0eec10cf14804c84d9bcf4f6fa864074f1b90ff2fb4873399d64b1a",
+ "url": "https://commadist.azureedge.net/agnosupdate/userdata_90-175a5d3353daa5e7b7d9939cb51a2f1d7e6312b4708ad654c351da2f1ef4f108.img.xz",
+ "hash": "ff01a0ca5a2ea6661f836248043a211cd8d71c3269c139cb574b56855fabc3f4",
+ "hash_raw": "175a5d3353daa5e7b7d9939cb51a2f1d7e6312b4708ad654c351da2f1ef4f108",
"size": 96636764160,
"sparse": true,
"full_check": true,
"has_ab": false,
- "ondevice_hash": "a64fea9c3a7bec11b850a55d50ceb30a032742c90aadf0ce35cdbef9349bebba"
+ "ondevice_hash": "2f3d69e5015a45a18c3553f2edc5706aacd6d84a4b3d5010a3d76a1a3aa910b0"
},
{
"name": "userdata_89",
- "url": "https://commadist.azureedge.net/agnosupdate/userdata_89-69b2404839f87b1de5c05766550ca0217d5ed566c9f2ea41c46b5a301540a3ac.img.xz",
- "hash": "332e6cf5c221690a01ebfd0582420e039c7796a8fb2d499e44a8b657dffe4af2",
- "hash_raw": "69b2404839f87b1de5c05766550ca0217d5ed566c9f2ea41c46b5a301540a3ac",
+ "url": "https://commadist.azureedge.net/agnosupdate/userdata_89-61bdaf82d3036af6e45e86adbaab02918b41debd5b58b6708d7987084d514d1b.img.xz",
+ "hash": "714970777e02bb53a71640735bdb84b3071ecbc0346b978ce12eb667d75634ec",
+ "hash_raw": "61bdaf82d3036af6e45e86adbaab02918b41debd5b58b6708d7987084d514d1b",
"size": 95563022336,
"sparse": true,
"full_check": true,
"has_ab": false,
- "ondevice_hash": "c560c76007fd8997e01e516ab16ff445048945a13bf830bb2a4c7f6e9d2fe5f6"
+ "ondevice_hash": "95e6889a808b8d266660990e67e917cf3b63179f23588565af7f2fa54f70ac76"
},
{
"name": "userdata_30",
- "url": "https://commadist.azureedge.net/agnosupdate/userdata_30-ffc34d8753520e684448185db801c05bb81e23c54a499cc40a2e38b7009cdf36.img.xz",
- "hash": "8bfb1fdec9c8f96c97bcce1efbc7d502447bdb3b481cc408b24b5feef66839fd",
- "hash_raw": "ffc34d8753520e684448185db801c05bb81e23c54a499cc40a2e38b7009cdf36",
+ "url": "https://commadist.azureedge.net/agnosupdate/userdata_30-a40553d3fd339cb0107f1cc55fd532820f192a7a9a90d05243ad00fcbf804997.img.xz",
+ "hash": "33e5ab398620f147b885a9627b2608591bd9e1c9aa481eb705dc86707d706ea2",
+ "hash_raw": "a40553d3fd339cb0107f1cc55fd532820f192a7a9a90d05243ad00fcbf804997",
"size": 32212254720,
"sparse": true,
"full_check": true,
"has_ab": false,
- "ondevice_hash": "8f840157d73fa4469aa650d668e046c9750304af84248ab83453cbd285918859"
+ "ondevice_hash": "cd6291dea40968123f7af0b831cbfbbd6e515b676f2e427ae47ff358f6ac148e"
}
-]
\ No newline at end of file
+]
diff --git a/system/hardware/tici/tests/test_power_draw.py b/system/hardware/tici/tests/test_power_draw.py
index e1b9845c4c..669889a2ae 100644
--- a/system/hardware/tici/tests/test_power_draw.py
+++ b/system/hardware/tici/tests/test_power_draw.py
@@ -33,7 +33,7 @@ class Proc:
PROCS = [
Proc(['camerad'], 1.75, msgs=['roadCameraState', 'wideRoadCameraState', 'driverCameraState']),
Proc(['modeld'], 1.12, atol=0.2, msgs=['modelV2']),
- Proc(['dmonitoringmodeld'], 0.6, msgs=['driverStateV2']),
+ Proc(['dmonitoringmodeld'], 1.4, msgs=['driverStateV2']),
Proc(['encoderd'], 0.23, msgs=[]),
]
diff --git a/system/manager/process_config.py b/system/manager/process_config.py
index 6e048c339e..e25d556037 100644
--- a/system/manager/process_config.py
+++ b/system/manager/process_config.py
@@ -94,6 +94,7 @@ procs = [
PythonProcess("qcomgpsd", "system.qcomgpsd.qcomgpsd", qcomgps, enabled=TICI),
PythonProcess("pandad", "selfdrive.pandad.pandad", always_run),
PythonProcess("paramsd", "selfdrive.locationd.paramsd", only_onroad),
+ PythonProcess("lagd", "selfdrive.locationd.lagd", only_onroad),
NativeProcess("ubloxd", "system/ubloxd", ["./ubloxd"], ublox, enabled=TICI),
PythonProcess("pigeond", "system.ubloxd.pigeond", ublox, enabled=TICI),
PythonProcess("plannerd", "selfdrive.controls.plannerd", not_long_maneuver),
diff --git a/system/ubloxd/ublox_msg.cc b/system/ubloxd/ublox_msg.cc
index 22c99501f3..728f3b15fa 100644
--- a/system/ubloxd/ublox_msg.cc
+++ b/system/ubloxd/ublox_msg.cc
@@ -476,6 +476,10 @@ kj::Array UbloxMsgParser::gen_nav_sat(ubx_t::nav_sat_t *msg) {
svs[i].setSvId(svs_data[i]->sv_id());
svs[i].setGnssId(svs_data[i]->gnss_id());
svs[i].setFlagsBitfield(svs_data[i]->flags());
+ svs[i].setCno(svs_data[i]->cno());
+ svs[i].setElevationDeg(svs_data[i]->elev());
+ svs[i].setAzimuthDeg(svs_data[i]->azim());
+ svs[i].setPseudorangeResidual(svs_data[i]->pr_res() * 0.1);
}
return capnp::messageToFlatArray(msg_builder);
diff --git a/system/ui/lib/application.py b/system/ui/lib/application.py
index c7b7a36e5d..f5a238b81e 100644
--- a/system/ui/lib/application.py
+++ b/system/ui/lib/application.py
@@ -38,6 +38,10 @@ class GuiApplication:
self._textures: list[rl.Texture] = []
self._target_fps: int = DEFAULT_FPS
self._last_fps_log_time: float = time.monotonic()
+ self._window_close_requested = False
+
+ def request_close(self):
+ self._window_close_requested = True
def init_window(self, title: str, fps: int=DEFAULT_FPS):
atexit.register(self.close) # Automatically call close() on exit
@@ -50,9 +54,11 @@ class GuiApplication:
self._set_styles()
self._load_fonts()
- def load_texture_from_image(self, file_name: str, width: int, height: int):
+ def load_texture_from_image(self, file_name: str, width: int, height: int, alpha_premultiply = False):
"""Load and resize a texture, storing it for later automatic unloading."""
image = rl.load_image(file_name)
+ if alpha_premultiply:
+ rl.image_alpha_premultiply(image)
rl.image_resize(image, width, height)
texture = rl.load_texture_from_image(image)
# Set texture filtering to smooth the result
@@ -64,16 +70,21 @@ class GuiApplication:
return texture
def close(self):
+ if not rl.is_window_ready():
+ return
+
for texture in self._textures:
rl.unload_texture(texture)
+ self._textures = []
for font in self._fonts.values():
rl.unload_font(font)
+ self._fonts = {}
rl.close_window()
def render(self):
- while not rl.window_should_close():
+ while not (self._window_close_requested or rl.window_should_close()):
rl.begin_drawing()
rl.clear_background(rl.BLACK)
@@ -85,8 +96,8 @@ class GuiApplication:
rl.end_drawing()
self._monitor_fps()
- def font(self, font_wight: FontWeight=FontWeight.NORMAL):
- return self._fonts[font_wight]
+ def font(self, font_weight: FontWeight=FontWeight.NORMAL):
+ return self._fonts[font_weight]
@property
def width(self):
@@ -120,7 +131,6 @@ class GuiApplication:
rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiDefaultProperty.TEXT_SIZE, DEFAULT_TEXT_SIZE)
rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiDefaultProperty.BACKGROUND_COLOR, rl.color_to_int(rl.BLACK))
rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiControlProperty.TEXT_COLOR_NORMAL, rl.color_to_int(DEFAULT_TEXT_COLOR))
- rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiDefaultProperty.BACKGROUND_COLOR, rl.color_to_int(rl.Color(30, 30, 30, 255)))
rl.gui_set_style(rl.GuiControl.DEFAULT, rl.GuiControlProperty.BASE_COLOR_NORMAL, rl.color_to_int(rl.Color(50, 50, 50, 255)))
def _monitor_fps(self):
diff --git a/system/ui/spinner.py b/system/ui/spinner.py
index 639de26744..9c1882cf5f 100755
--- a/system/ui/spinner.py
+++ b/system/ui/spinner.py
@@ -1,76 +1,92 @@
#!/usr/bin/env python3
import pyray as rl
import os
-import select
-import sys
+import threading
from openpilot.common.basedir import BASEDIR
from openpilot.system.ui.lib.application import gui_app
+from openpilot.system.ui.text import wrap_text
# Constants
PROGRESS_BAR_WIDTH = 1000
PROGRESS_BAR_HEIGHT = 20
-ROTATION_TIME_SECONDS = 1.0 # Time for one full circle
-MARGIN = 200
+DEGREES_PER_SECOND = 360.0 # one full rotation per second
+MARGIN_H = 100
TEXTURE_SIZE = 360
-FONT_SIZE = 80
+FONT_SIZE = 88
+LINE_HEIGHT = 96
+DARKGRAY = (55, 55, 55, 255)
def clamp(value, min_value, max_value):
return max(min(value, max_value), min_value)
-def check_input_non_blocking():
- if sys.stdin in select.select([sys.stdin], [], [], 0)[0]:
- return sys.stdin.readline().strip()
- return ""
-
-
-def main():
- gui_app.init_window("Spinner")
-
- # Load textures
- comma_texture = gui_app.load_texture_from_image(os.path.join(BASEDIR, "selfdrive/assets/img_spinner_comma.png"), TEXTURE_SIZE, TEXTURE_SIZE)
- spinner_texture = gui_app.load_texture_from_image(os.path.join(BASEDIR, "selfdrive/assets/img_spinner_track.png"), TEXTURE_SIZE, TEXTURE_SIZE)
-
- # Initial values
- rotation = 0.0
- user_input = ""
- center = rl.Vector2(gui_app.width / 2.0, gui_app.height / 2.0)
- spinner_origin = rl.Vector2(TEXTURE_SIZE / 2.0, TEXTURE_SIZE / 2.0)
- comma_position = rl.Vector2(center.x - TEXTURE_SIZE / 2.0, center.y - TEXTURE_SIZE / 2.0)
-
- for _ in gui_app.render():
- fps = rl.get_fps()
- if fps > 0:
- degrees_per_frame = 360.0 / (ROTATION_TIME_SECONDS * fps)
- rotation = (rotation + degrees_per_frame) % 360.0
+class Spinner:
+ def __init__(self):
+ self._comma_texture = gui_app.load_texture_from_image(os.path.join(BASEDIR, "selfdrive/assets/img_spinner_comma.png"), TEXTURE_SIZE, TEXTURE_SIZE)
+ self._spinner_texture = gui_app.load_texture_from_image(os.path.join(BASEDIR, "selfdrive/assets/img_spinner_track.png"), TEXTURE_SIZE, TEXTURE_SIZE,
+ alpha_premultiply=True)
+ self._rotation = 0.0
+ self._progress: int | None = None
+ self._wrapped_lines: list[str] = []
+ self._lock = threading.Lock()
+
+ def set_text(self, text: str) -> None:
+ with self._lock:
+ if text.isdigit():
+ self._progress = clamp(int(text), 0, 100)
+ self._wrapped_lines = []
+ else:
+ self._progress = None
+ self._wrapped_lines = wrap_text(text, FONT_SIZE, gui_app.width - MARGIN_H)
+
+ def render(self):
+ with self._lock:
+ progress = self._progress
+ wrapped_lines = self._wrapped_lines
+
+ if wrapped_lines:
+ # Calculate total height required for spinner and text
+ spacing = 50
+ total_height = TEXTURE_SIZE + spacing + len(wrapped_lines) * LINE_HEIGHT
+ center_y = (gui_app.height - total_height) / 2.0 + TEXTURE_SIZE / 2.0
+ else:
+ # Center spinner vertically
+ spacing = 150
+ center_y = gui_app.height / 2.0
+ y_pos = center_y + TEXTURE_SIZE / 2.0 + spacing
+
+ center = rl.Vector2(gui_app.width / 2.0, center_y)
+ spinner_origin = rl.Vector2(TEXTURE_SIZE / 2.0, TEXTURE_SIZE / 2.0)
+ comma_position = rl.Vector2(center.x - TEXTURE_SIZE / 2.0, center.y - TEXTURE_SIZE / 2.0)
+
+ delta_time = rl.get_frame_time()
+ self._rotation = (self._rotation + DEGREES_PER_SECOND * delta_time) % 360.0
# Draw rotating spinner and static comma logo
- rl.draw_texture_pro(spinner_texture, rl.Rectangle(0, 0, TEXTURE_SIZE, TEXTURE_SIZE),
+ rl.draw_texture_pro(self._spinner_texture, rl.Rectangle(0, 0, TEXTURE_SIZE, TEXTURE_SIZE),
rl.Rectangle(center.x, center.y, TEXTURE_SIZE, TEXTURE_SIZE),
- spinner_origin, rotation, rl.WHITE)
- rl.draw_texture_v(comma_texture, comma_position, rl.WHITE)
-
- # Read user input
- if input_str := check_input_non_blocking():
- user_input = input_str
+ spinner_origin, self._rotation, rl.WHITE)
+ rl.draw_texture_v(self._comma_texture, comma_position, rl.WHITE)
# Display progress bar or text based on user input
- if user_input:
- y_pos = rl.get_screen_height() - MARGIN - PROGRESS_BAR_HEIGHT
- if user_input.isdigit():
- progress = clamp(int(user_input), 0, 100)
- bar = rl.Rectangle(center.x - PROGRESS_BAR_WIDTH / 2.0, y_pos, PROGRESS_BAR_WIDTH, PROGRESS_BAR_HEIGHT)
- rl.draw_rectangle_rounded(bar, 0.5, 10, rl.GRAY)
-
- bar.width *= progress / 100.0
- rl.draw_rectangle_rounded(bar, 0.5, 10, rl.WHITE)
- else:
- text_size = rl.measure_text_ex(gui_app.font(), user_input, FONT_SIZE, 1.0)
- rl.draw_text_ex(gui_app.font(), user_input,
- rl.Vector2(center.x - text_size.x / 2, y_pos), FONT_SIZE, 1.0, rl.WHITE)
+ if progress is not None:
+ bar = rl.Rectangle(center.x - PROGRESS_BAR_WIDTH / 2.0, y_pos, PROGRESS_BAR_WIDTH, PROGRESS_BAR_HEIGHT)
+ rl.draw_rectangle_rounded(bar, 1, 10, DARKGRAY)
+
+ bar.width *= progress / 100.0
+ rl.draw_rectangle_rounded(bar, 1, 10, rl.WHITE)
+ elif wrapped_lines:
+ for i, line in enumerate(wrapped_lines):
+ text_size = rl.measure_text_ex(gui_app.font(), line, FONT_SIZE, 0.0)
+ rl.draw_text_ex(gui_app.font(), line, rl.Vector2(center.x - text_size.x / 2, y_pos + i * LINE_HEIGHT),
+ FONT_SIZE, 0.0, rl.WHITE)
if __name__ == "__main__":
- main()
+ gui_app.init_window("Spinner")
+ spinner = Spinner()
+ spinner.set_text("Spinner text")
+ for _ in gui_app.render():
+ spinner.render()
diff --git a/system/ui/text.py b/system/ui/text.py
index 33299605d6..1337887d9b 100755
--- a/system/ui/text.py
+++ b/system/ui/text.py
@@ -1,16 +1,15 @@
#!/usr/bin/env python3
-import sys
+import re
import pyray as rl
-
-from openpilot.system.hardware import HARDWARE
+from openpilot.system.hardware import HARDWARE, PC
from openpilot.system.ui.lib.button import gui_button, ButtonStyle
from openpilot.system.ui.lib.scroll_panel import GuiScrollPanel
from openpilot.system.ui.lib.application import gui_app
MARGIN = 50
SPACING = 50
-FONT_SIZE = 60
-LINE_HEIGHT = 64
+FONT_SIZE = 72
+LINE_HEIGHT = 80
BUTTON_SIZE = rl.Vector2(310, 160)
DEMO_TEXT = """This is a sample text that will be wrapped and scrolled if necessary.
@@ -18,47 +17,63 @@ DEMO_TEXT = """This is a sample text that will be wrapped and scrolled if necess
def wrap_text(text, font_size, max_width):
lines = []
- current_line = ""
font = gui_app.font()
- for word in text.split():
- test_line = current_line + word + " "
- if rl.measure_text_ex(font, test_line, font_size, 0).x <= max_width:
- current_line = test_line
- else:
+ for paragraph in text.split("\n"):
+ if not paragraph.strip():
+ # Don't add empty lines first, ensuring wrap_text("") returns []
+ if lines:
+ lines.append("")
+ continue
+ indent = re.match(r"^\s*", paragraph).group()
+ current_line = indent
+ for word in paragraph.split():
+ test_line = current_line + word + " "
+ if rl.measure_text_ex(font, test_line, font_size, 0).x <= max_width:
+ current_line = test_line
+ else:
+ lines.append(current_line)
+ current_line = word + " "
+ current_line = current_line.rstrip()
+ if current_line:
lines.append(current_line)
- current_line = word + " "
- if current_line:
- lines.append(current_line)
return lines
+class TextWindow:
+ def __init__(self, text: str):
+ self._textarea_rect = rl.Rectangle(MARGIN, MARGIN, gui_app.width - MARGIN * 2, gui_app.height - MARGIN * 2)
+ self._wrapped_lines = wrap_text(text, FONT_SIZE, self._textarea_rect.width - 20)
+ self._content_rect = rl.Rectangle(0, 0, self._textarea_rect.width - 20, len(self._wrapped_lines) * LINE_HEIGHT)
+ self._scroll_panel = GuiScrollPanel(show_vertical_scroll_bar=True)
-def main():
- gui_app.init_window("Text")
-
- text_content = sys.argv[1] if len(sys.argv) > 1 else DEMO_TEXT
-
- textarea_rect = rl.Rectangle(MARGIN, MARGIN, gui_app.width - MARGIN * 2, gui_app.height - MARGIN * 2)
- wrapped_lines = wrap_text(text_content, FONT_SIZE, textarea_rect.width - 20)
- content_rect = rl.Rectangle(0, 0, textarea_rect.width - 20, len(wrapped_lines) * LINE_HEIGHT)
- scroll_panel = GuiScrollPanel(show_vertical_scroll_bar=True)
-
- for _ in gui_app.render():
- scroll = scroll_panel.handle_scroll(textarea_rect, content_rect)
-
- rl.begin_scissor_mode(int(textarea_rect.x), int(textarea_rect.y), int(textarea_rect.width), int(textarea_rect.height))
- for i, line in enumerate(wrapped_lines):
- position = rl.Vector2(textarea_rect.x + scroll.x, textarea_rect.y + scroll.y + i * LINE_HEIGHT)
- if position.y + LINE_HEIGHT < textarea_rect.y or position.y > textarea_rect.y + textarea_rect.height:
+ def render(self):
+ scroll = self._scroll_panel.handle_scroll(self._textarea_rect, self._content_rect)
+ rl.begin_scissor_mode(int(self._textarea_rect.x), int(self._textarea_rect.y), int(self._textarea_rect.width), int(self._textarea_rect.height))
+ for i, line in enumerate(self._wrapped_lines):
+ position = rl.Vector2(self._textarea_rect.x + scroll.x, self._textarea_rect.y + scroll.y + i * LINE_HEIGHT)
+ if position.y + LINE_HEIGHT < self._textarea_rect.y or position.y > self._textarea_rect.y + self._textarea_rect.height:
continue
- rl.draw_text_ex(gui_app.font(), line.strip(), position, FONT_SIZE, 0, rl.WHITE)
+ rl.draw_text_ex(gui_app.font(), line, position, FONT_SIZE, 0, rl.WHITE)
rl.end_scissor_mode()
button_bounds = rl.Rectangle(gui_app.width - MARGIN - BUTTON_SIZE.x, gui_app.height - MARGIN - BUTTON_SIZE.y, BUTTON_SIZE.x, BUTTON_SIZE.y)
- if gui_button(button_bounds, "Reboot", button_style=ButtonStyle.TRANSPARENT):
- HARDWARE.reboot()
+ ret = gui_button(button_bounds, "Exit" if PC else "Reboot", button_style=ButtonStyle.TRANSPARENT)
+ if ret:
+ if PC:
+ gui_app.request_close()
+ else:
+ HARDWARE.reboot()
+ return ret
+
+
+def show_text_in_window(text: str):
+ gui_app.init_window("Text")
+ text_window = TextWindow(text)
+ for _ in gui_app.render():
+ text_window.render()
+ gui_app.close()
if __name__ == "__main__":
- main()
+ show_text_in_window(DEMO_TEXT)
diff --git a/system/ui/updater.py b/system/ui/updater.py
new file mode 100755
index 0000000000..eb9d766a16
--- /dev/null
+++ b/system/ui/updater.py
@@ -0,0 +1,197 @@
+#!/usr/bin/env python3
+import sys
+import subprocess
+import threading
+import pyray as rl
+from enum import IntEnum
+
+from openpilot.system.hardware import HARDWARE
+from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.button import gui_button, ButtonStyle
+from openpilot.system.ui.lib.label import gui_text_box, gui_label
+
+# Constants
+MARGIN = 50
+BUTTON_HEIGHT = 160
+BUTTON_WIDTH = 400
+PROGRESS_BAR_HEIGHT = 72
+TITLE_FONT_SIZE = 80
+BODY_FONT_SIZE = 65
+BACKGROUND_COLOR = rl.BLACK
+PROGRESS_BG_COLOR = rl.Color(41, 41, 41, 255)
+PROGRESS_COLOR = rl.Color(54, 77, 239, 255)
+
+
+class Screen(IntEnum):
+ PROMPT = 0
+ WIFI = 1
+ PROGRESS = 2
+
+
+class Updater:
+ def __init__(self, updater_path, manifest_path):
+ self.updater = updater_path
+ self.manifest = manifest_path
+ self.current_screen = Screen.PROMPT
+
+ self.progress_value = 0
+ self.progress_text = "Loading..."
+ self.show_reboot_button = False
+ self.process = None
+ self.update_thread = None
+
+ def install_update(self):
+ self.current_screen = Screen.PROGRESS
+ self.progress_value = 0
+ self.progress_text = "Downloading..."
+ self.show_reboot_button = False
+
+ # Start the update process in a separate thread
+ self.update_thread = threading.Thread(target=self._run_update_process)
+ self.update_thread.daemon = True
+ self.update_thread.start()
+
+ def _run_update_process(self):
+ # TODO: just import it and run in a thread without a subprocess
+ cmd = [self.updater, "--swap", self.manifest]
+ self.process = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE,
+ text=True, bufsize=1, universal_newlines=True)
+
+ for line in self.process.stdout:
+ parts = line.strip().split(":")
+ if len(parts) == 2:
+ self.progress_text = parts[0]
+ try:
+ self.progress_value = int(float(parts[1]))
+ except ValueError:
+ pass
+
+ exit_code = self.process.wait()
+ if exit_code == 0:
+ HARDWARE.reboot()
+ else:
+ self.progress_text = "Update failed"
+ self.show_reboot_button = True
+
+ def render_prompt_screen(self):
+ # Title
+ title_rect = rl.Rectangle(MARGIN + 50, 250, gui_app.width - MARGIN * 2 - 100, TITLE_FONT_SIZE)
+ gui_label(title_rect, "Update Required", TITLE_FONT_SIZE, font_weight=FontWeight.BOLD)
+
+ # Description
+ desc_text = "An operating system update is required. Connect your device to Wi-Fi for the fastest update experience. \
+ The download size is approximately 1GB."
+ desc_rect = rl.Rectangle(MARGIN + 50, 250 + TITLE_FONT_SIZE + 75, gui_app.width - MARGIN * 2 - 100, BODY_FONT_SIZE * 3)
+ gui_text_box(desc_rect, desc_text, BODY_FONT_SIZE)
+
+ # Buttons at the bottom
+ button_y = gui_app.height - MARGIN - BUTTON_HEIGHT
+ button_width = (gui_app.width - MARGIN * 3) // 2
+
+ # WiFi button
+ wifi_button_rect = rl.Rectangle(MARGIN, button_y, button_width, BUTTON_HEIGHT)
+ if gui_button(wifi_button_rect, "Connect to Wi-Fi"):
+ self.current_screen = Screen.WIFI
+ return # Return to avoid processing other buttons after screen change
+
+ # Install button
+ install_button_rect = rl.Rectangle(MARGIN * 2 + button_width, button_y, button_width, BUTTON_HEIGHT)
+ if gui_button(install_button_rect, "Install", button_style=ButtonStyle.PRIMARY):
+ self.install_update()
+ return # Return to avoid further processing after action
+
+ def render_wifi_screen(self):
+ # Title and back button
+ title_rect = rl.Rectangle(MARGIN + 50, MARGIN, gui_app.width - MARGIN * 2 - 100, 60)
+ gui_label(title_rect, "Wi-Fi Networks", 60, font_weight=FontWeight.BOLD)
+
+ back_button_rect = rl.Rectangle(MARGIN, gui_app.height - MARGIN - BUTTON_HEIGHT, BUTTON_WIDTH, BUTTON_HEIGHT)
+ if gui_button(back_button_rect, "Back"):
+ self.current_screen = Screen.PROMPT
+ return # Return to avoid processing other interactions after screen change
+
+ # Draw placeholder for WiFi implementation
+ placeholder_rect = rl.Rectangle(
+ MARGIN,
+ title_rect.y + title_rect.height + MARGIN,
+ gui_app.width - MARGIN * 2,
+ gui_app.height - title_rect.height - MARGIN * 3 - BUTTON_HEIGHT
+ )
+
+ # Draw rounded rectangle background
+ rl.draw_rectangle_rounded(
+ placeholder_rect,
+ 0.1,
+ 10,
+ rl.Color(41, 41, 41, 255)
+ )
+
+ # Draw placeholder text
+ placeholder_text = "WiFi Implementation Placeholder"
+ text_size = rl.measure_text_ex(gui_app.font(), placeholder_text, 80, 1)
+ text_pos = rl.Vector2(
+ placeholder_rect.x + (placeholder_rect.width - text_size.x) / 2,
+ placeholder_rect.y + (placeholder_rect.height - text_size.y) / 2
+ )
+ rl.draw_text_ex(gui_app.font(), placeholder_text, text_pos, 80, 1, rl.WHITE)
+
+ # Draw instructions
+ instructions_text = "Real WiFi functionality would be implemented here"
+ instructions_size = rl.measure_text_ex(gui_app.font(), instructions_text, 40, 1)
+ instructions_pos = rl.Vector2(
+ placeholder_rect.x + (placeholder_rect.width - instructions_size.x) / 2,
+ text_pos.y + text_size.y + 20
+ )
+ rl.draw_text_ex(gui_app.font(), instructions_text, instructions_pos, 40, 1, rl.GRAY)
+
+ def render_progress_screen(self):
+ title_rect = rl.Rectangle(MARGIN + 100, 330, gui_app.width - MARGIN * 2 - 200, 100)
+ gui_label(title_rect, self.progress_text, 90, font_weight=FontWeight.SEMI_BOLD)
+
+ # Progress bar
+ bar_rect = rl.Rectangle(MARGIN + 100, 330 + 100 + 100, gui_app.width - MARGIN * 2 - 200, PROGRESS_BAR_HEIGHT)
+ rl.draw_rectangle_rounded(bar_rect, 0.5, 10, PROGRESS_BG_COLOR)
+
+ # Calculate the width of the progress chunk
+ progress_width = (bar_rect.width * self.progress_value) / 100
+ if progress_width > 0:
+ progress_rect = rl.Rectangle(bar_rect.x, bar_rect.y, progress_width, bar_rect.height)
+ rl.draw_rectangle_rounded(progress_rect, 0.5, 10, PROGRESS_COLOR)
+
+ # Show reboot button if needed
+ if self.show_reboot_button:
+ reboot_rect = rl.Rectangle(MARGIN + 100, gui_app.height - MARGIN - BUTTON_HEIGHT, BUTTON_WIDTH, BUTTON_HEIGHT)
+ if gui_button(reboot_rect, "Reboot"):
+ # Return True to signal main loop to exit before rebooting
+ HARDWARE.reboot()
+ return
+
+ def render(self):
+ if self.current_screen == Screen.PROMPT:
+ self.render_prompt_screen()
+ elif self.current_screen == Screen.WIFI:
+ self.render_wifi_screen()
+ elif self.current_screen == Screen.PROGRESS:
+ self.render_progress_screen()
+
+
+def main():
+ if len(sys.argv) < 3:
+ print("Usage: updater.py ")
+ sys.exit(1)
+
+ updater_path = sys.argv[1]
+ manifest_path = sys.argv[2]
+
+ try:
+ gui_app.init_window("System Update")
+ updater = Updater(updater_path, manifest_path)
+ for _ in gui_app.render():
+ updater.render()
+ finally:
+ # Make sure we clean up even if there's an error
+ gui_app.close()
+
+
+if __name__ == "__main__":
+ main()
diff --git a/tinygrad_repo b/tinygrad_repo
index 70266e9f94..0e34f9082e 160000
--- a/tinygrad_repo
+++ b/tinygrad_repo
@@ -1 +1 @@
-Subproject commit 70266e9f94d5a247ccbb2f3a46e72a2fbdaf7a8e
+Subproject commit 0e34f9082e9730b5df9c055b094a43e4565e413b
diff --git a/tools/joystick/joystick_control.py b/tools/joystick/joystick_control.py
index 74d034d505..11d17e587e 100755
--- a/tools/joystick/joystick_control.py
+++ b/tools/joystick/joystick_control.py
@@ -28,7 +28,7 @@ class Keyboard:
key = self.kb.getch().lower()
self.cancel = False
if key == 'r':
- self.axes_values = {ax: 0. for ax in self.axes_values}
+ self.axes_values = dict.fromkeys(self.axes_values, 0.)
elif key == 'c':
self.cancel = True
elif key in self.axes_map:
@@ -65,7 +65,7 @@ class Joystick:
try:
joystick_event = get_gamepad()[0]
except (OSError, UnpluggedError):
- self.axes_values = {ax: 0. for ax in self.axes_values}
+ self.axes_values = dict.fromkeys(self.axes_values, 0.)
return False
event = (joystick_event.code, joystick_event.state)
diff --git a/tools/lib/logreader.py b/tools/lib/logreader.py
index 9fe73825a8..34d3e5ea9f 100755
--- a/tools/lib/logreader.py
+++ b/tools/lib/logreader.py
@@ -300,11 +300,11 @@ class LogReader:
def _run_on_segment(self, func, i):
return func(self._get_lr(i))
- def run_across_segments(self, num_processes, func, desc=None):
+ def run_across_segments(self, num_processes, func, disable_tqdm=False, desc=None):
with multiprocessing.Pool(num_processes) as pool:
ret = []
num_segs = len(self.logreader_identifiers)
- for p in tqdm.tqdm(pool.imap(partial(self._run_on_segment, func), range(num_segs)), total=num_segs, desc=desc):
+ for p in tqdm.tqdm(pool.imap(partial(self._run_on_segment, func), range(num_segs)), total=num_segs, disable=disable_tqdm, desc=desc):
ret.extend(p)
return ret
diff --git a/tools/mac_setup.sh b/tools/mac_setup.sh
index c626ec4561..d23052d0f0 100755
--- a/tools/mac_setup.sh
+++ b/tools/mac_setup.sh
@@ -28,6 +28,8 @@ if [[ $(command -v brew) == "" ]]; then
echo 'eval "$(/opt/homebrew/bin/brew shellenv)"' >> $RC_FILE
eval "$(/opt/homebrew/bin/brew shellenv)"
fi
+else
+ brew up
fi
brew bundle --file=- <<-EOS
diff --git a/tools/plotjuggler/juggle.py b/tools/plotjuggler/juggle.py
index f66782d6f3..34f33d1959 100755
--- a/tools/plotjuggler/juggle.py
+++ b/tools/plotjuggler/juggle.py
@@ -61,13 +61,15 @@ def start_juggler(fn=None, dbc=None, layout=None, route_or_segment_name=None, pl
env["BASEDIR"] = BASEDIR
env["PATH"] = f"{INSTALL_DIR}:{os.getenv('PATH', '')}"
if dbc:
+ if os.path.exists(dbc):
+ dbc = os.path.abspath(dbc)
env["DBC_NAME"] = dbc
extra_args = ""
if fn is not None:
- extra_args += f" -d {fn}"
+ extra_args += f" -d {os.path.abspath(fn)}"
if layout is not None:
- extra_args += f" -l {layout}"
+ extra_args += f" -l {os.path.abspath(layout)}"
if route_or_segment_name is not None:
extra_args += f" --window_title \"{route_or_segment_name}{f' ({platform})' if platform is not None else ''}\""
diff --git a/tools/plotjuggler/layouts/gps.xml b/tools/plotjuggler/layouts/gps.xml
new file mode 100644
index 0000000000..8fd3b53f93
--- /dev/null
+++ b/tools/plotjuggler/layouts/gps.xml
@@ -0,0 +1,62 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/tools/plotjuggler/layouts/torque-controller.xml b/tools/plotjuggler/layouts/torque-controller.xml
index 5a0a7625e0..606df03611 100644
--- a/tools/plotjuggler/layouts/torque-controller.xml
+++ b/tools/plotjuggler/layouts/torque-controller.xml
@@ -150,44 +150,44 @@
-
-
+
+
-
+
-
+
-
+
-
+
-
+
-
+
diff --git a/tools/sim/bridge/common.py b/tools/sim/bridge/common.py
index bf3be5193d..69dec173ca 100644
--- a/tools/sim/bridge/common.py
+++ b/tools/sim/bridge/common.py
@@ -40,7 +40,7 @@ class SimulatorBridge(ABC):
def __init__(self, dual_camera, high_quality):
set_params_enabled()
self.params = Params()
- self.params.put_bool("ExperimentalLongitudinalEnabled", True)
+ self.params.put_bool("AlphaLongitudinalEnabled", True)
self.rk = Ratekeeper(100, None)
diff --git a/uv.lock b/uv.lock
index fe95157eb2..6911f053cb 100644
--- a/uv.lock
+++ b/uv.lock
@@ -12,16 +12,16 @@ resolution-markers = [
[[package]]
name = "aiohappyeyeballs"
-version = "2.5.0"
+version = "2.6.1"
source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/a2/0c/458958007041f4b4de2d307e6b75d9e7554dad0baf26fe7a48b741aac126/aiohappyeyeballs-2.5.0.tar.gz", hash = "sha256:18fde6204a76deeabc97c48bdd01d5801cfda5d6b9c8bbeb1aaaee9d648ca191", size = 22494 }
+sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760 }
wheels = [
- { url = "https://files.pythonhosted.org/packages/1b/9a/e4886864ce06e1579bd428208127fbdc0d62049c751e4e9e3b509c0059dc/aiohappyeyeballs-2.5.0-py3-none-any.whl", hash = "sha256:0850b580748c7071db98bffff6d4c94028d0d3035acc20fd721a0ce7e8cac35d", size = 15128 },
+ { url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8", size = 15265 },
]
[[package]]
name = "aiohttp"
-version = "3.11.13"
+version = "3.11.16"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "aiohappyeyeballs" },
@@ -32,53 +32,53 @@ dependencies = [
{ name = "propcache" },
{ name = "yarl" },
]
-sdist = { url = "https://files.pythonhosted.org/packages/b3/3f/c4a667d184c69667b8f16e0704127efc5f1e60577df429382b4d95fd381e/aiohttp-3.11.13.tar.gz", hash = "sha256:8ce789231404ca8fff7f693cdce398abf6d90fd5dae2b1847477196c243b1fbb", size = 7674284 }
-wheels = [
- { url = "https://files.pythonhosted.org/packages/3b/93/8e012ae31ff1bda5d43565d6f9e0bad325ba6f3f2d78f298bd39645be8a3/aiohttp-3.11.13-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:6b35aab22419ba45f8fc290d0010898de7a6ad131e468ffa3922b1b0b24e9d2e", size = 709013 },
- { url = "https://files.pythonhosted.org/packages/d8/be/fc7c436678ffe547d038319add8e44fd5e33090158752e5c480aed51a8d0/aiohttp-3.11.13-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:f81cba651db8795f688c589dd11a4fbb834f2e59bbf9bb50908be36e416dc760", size = 468896 },
- { url = "https://files.pythonhosted.org/packages/d9/1c/56906111ac9d4dab4baab43c89d35d5de1dbb38085150257895005b08bef/aiohttp-3.11.13-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f55d0f242c2d1fcdf802c8fabcff25a9d85550a4cf3a9cf5f2a6b5742c992839", size = 455968 },
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