Merge remote-tracking branch 'origin/master' into online-lag

.github/workflows/selfdrive_tests.yaml

@@ -315,7 +315,7 @@ jobs:
       run: |
         ${{ env.RUN }} "source selfdrive/test/setup_xvfb.sh && \
                         source selfdrive/test/setup_vsound.sh && \
-                        CI=1 pytest tools/sim/tests/test_metadrive_bridge.py"
+                        CI=1 pytest -s tools/sim/tests/test_metadrive_bridge.py"
 
   create_ui_report:
     # This job name needs to be the same as UI_JOB_NAME in ui_preview.yaml

common/realtime.py

@@ -27,11 +27,6 @@ class Priority:
   CTRL_HIGH = 53
 
 
-def set_realtime_priority(level: int) -> None:
-  if not PC:
-    os.sched_setscheduler(0, os.SCHED_FIFO, os.sched_param(level))
-
-
 def set_core_affinity(cores: list[int]) -> None:
   if not PC:
     os.sched_setaffinity(0, cores)
@@ -39,7 +34,8 @@ def set_core_affinity(cores: list[int]) -> None:
 
 def config_realtime_process(cores: int | list[int], priority: int) -> None:
   gc.disable()
-  set_realtime_priority(priority)
+  if not PC:
+    os.sched_setscheduler(0, os.SCHED_FIFO, os.sched_param(priority))
   c = cores if isinstance(cores, list) else [cores, ]
   set_core_affinity(c)
 

opendbc_repo

@@ -1 +1 @@
-Subproject commit 4bfb262fd52bc6946de1c8280efc424910bd9d60
+Subproject commit 130bf3183f4ab871ee8dd56b122cfbb038542606

panda

@@ -1 +1 @@
-Subproject commit 3ff97305c565d5e43931052b9ec4747b2f617401
+Subproject commit 978ee190051806f8e5b7b8fede6b6be4e4db4aae

selfdrive/car/card.py

@@ -7,8 +7,6 @@ import cereal.messaging as messaging
 
 from cereal import car, log
 
-from panda import ALTERNATIVE_EXPERIENCE
-
 from openpilot.common.params import Params
 from openpilot.common.realtime import config_realtime_process, Priority, Ratekeeper
 from openpilot.common.swaglog import cloudlog, ForwardingHandler
@@ -19,6 +17,7 @@ from opendbc.car.carlog import carlog
 from opendbc.car.fw_versions import ObdCallback
 from opendbc.car.car_helpers import get_car, get_radar_interface
 from opendbc.car.interfaces import CarInterfaceBase, RadarInterfaceBase
+from opendbc.safety import ALTERNATIVE_EXPERIENCE
 from openpilot.selfdrive.pandad import can_capnp_to_list, can_list_to_can_capnp
 from openpilot.selfdrive.car.cruise import VCruiseHelper
 from openpilot.selfdrive.car.car_specific import MockCarState

selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py

@@ -3,7 +3,7 @@ import os
 import time
 import numpy as np
 from cereal import log
-from opendbc.car.interfaces import ACCEL_MIN
+from opendbc.car.interfaces import ACCEL_MIN, ACCEL_MAX
 from openpilot.common.realtime import DT_MDL
 from openpilot.common.swaglog import cloudlog
 # WARNING: imports outside of constants will not trigger a rebuild
@@ -55,6 +55,8 @@ FCW_IDXS = T_IDXS < 5.0
 T_DIFFS = np.diff(T_IDXS, prepend=[0.])
 COMFORT_BRAKE = 2.5
 STOP_DISTANCE = 6.0
+CRUISE_MIN_ACCEL = -1.2
+CRUISE_MAX_ACCEL = 1.6
 
 def get_jerk_factor(personality=log.LongitudinalPersonality.standard):
   if personality==log.LongitudinalPersonality.relaxed:
@@ -281,7 +283,7 @@ class LongitudinalMpc:
     elif self.mode == 'blended':
       a_change_cost = 40.0 if prev_accel_constraint else 0
       cost_weights = [0., 0.1, 0.2, 5.0, a_change_cost, 1.0]
-      constraint_cost_weights = [LIMIT_COST, LIMIT_COST, LIMIT_COST, 50.0]
+      constraint_cost_weights = [LIMIT_COST, LIMIT_COST, LIMIT_COST, DANGER_ZONE_COST]
     else:
       raise NotImplementedError(f'Planner mode {self.mode} not recognized in planner cost set')
     self.set_cost_weights(cost_weights, constraint_cost_weights)
@@ -325,12 +327,6 @@ class LongitudinalMpc:
     lead_xv = self.extrapolate_lead(x_lead, v_lead, a_lead, a_lead_tau)
     return lead_xv
 
-  def set_accel_limits(self, min_a, max_a):
-    # TODO this sets a max accel limit, but the minimum limit is only for cruise decel
-    # needs refactor
-    self.cruise_min_a = min_a
-    self.max_a = max_a
-
   def update(self, radarstate, v_cruise, x, v, a, j, personality=log.LongitudinalPersonality.standard):
     t_follow = get_T_FOLLOW(personality)
     v_ego = self.x0[1]
@@ -346,8 +342,7 @@ class LongitudinalMpc:
     lead_1_obstacle = lead_xv_1[:,0] + get_stopped_equivalence_factor(lead_xv_1[:,1])
 
     self.params[:,0] = ACCEL_MIN
-    # negative accel constraint causes problems because negative speed is not allowed
-    self.params[:,1] = max(0.0, self.max_a)
+    self.params[:,1] = ACCEL_MAX
 
     # Update in ACC mode or ACC/e2e blend
     if self.mode == 'acc':
@@ -355,9 +350,9 @@ class LongitudinalMpc:
 
       # Fake an obstacle for cruise, this ensures smooth acceleration to set speed
       # when the leads are no factor.
-      v_lower = v_ego + (T_IDXS * self.cruise_min_a * 1.05)
+      v_lower = v_ego + (T_IDXS * CRUISE_MIN_ACCEL * 1.05)
       # TODO does this make sense when max_a is negative?
-      v_upper = v_ego + (T_IDXS * self.max_a * 1.05)
+      v_upper = v_ego + (T_IDXS * CRUISE_MAX_ACCEL * 1.05)
       v_cruise_clipped = np.clip(v_cruise * np.ones(N+1),
                                  v_lower,
                                  v_upper)

selfdrive/controls/lib/longitudinal_planner.py

@@ -16,7 +16,6 @@ from openpilot.selfdrive.car.cruise import V_CRUISE_MAX, V_CRUISE_UNSET
 from openpilot.common.swaglog import cloudlog
 
 LON_MPC_STEP = 0.2  # first step is 0.2s
-A_CRUISE_MIN = -1.2
 A_CRUISE_MAX_VALS = [1.6, 1.2, 0.8, 0.6]
 A_CRUISE_MAX_BP = [0., 10.0, 25., 40.]
 CONTROL_N_T_IDX = ModelConstants.T_IDXS[:CONTROL_N]
@@ -76,7 +75,10 @@ class LongitudinalPlanner:
 
     self.a_desired = init_a
     self.v_desired_filter = FirstOrderFilter(init_v, 2.0, self.dt)
+    self.prev_accel_clip = [ACCEL_MIN, ACCEL_MAX]
     self.v_model_error = 0.0
+    self.output_a_target = 0.0
+    self.output_should_stop = False
 
     self.v_desired_trajectory = np.zeros(CONTROL_N)
     self.a_desired_trajectory = np.zeros(CONTROL_N)
@@ -128,17 +130,16 @@ class LongitudinalPlanner:
     prev_accel_constraint = not (reset_state or sm['carState'].standstill)
 
     if self.mpc.mode == 'acc':
-      accel_limits = [A_CRUISE_MIN, get_max_accel(v_ego)]
+      accel_clip = [ACCEL_MIN, get_max_accel(v_ego)]
       steer_angle_without_offset = sm['carState'].steeringAngleDeg - sm['liveParameters'].angleOffsetDeg
-      accel_limits_turns = limit_accel_in_turns(v_ego, steer_angle_without_offset, accel_limits, self.CP)
+      accel_clip = limit_accel_in_turns(v_ego, steer_angle_without_offset, accel_clip, self.CP)
     else:
-      accel_limits = [ACCEL_MIN, ACCEL_MAX]
-      accel_limits_turns = [ACCEL_MIN, ACCEL_MAX]
+      accel_clip = [ACCEL_MIN, ACCEL_MAX]
 
     if reset_state:
       self.v_desired_filter.x = v_ego
       # Clip aEgo to cruise limits to prevent large accelerations when becoming active
-      self.a_desired = np.clip(sm['carState'].aEgo, accel_limits[0], accel_limits[1])
+      self.a_desired = np.clip(sm['carState'].aEgo, accel_clip[0], accel_clip[1])
 
     # Prevent divergence, smooth in current v_ego
     self.v_desired_filter.x = max(0.0, self.v_desired_filter.update(v_ego))
@@ -149,18 +150,14 @@ class LongitudinalPlanner:
     self.allow_throttle = throttle_prob > ALLOW_THROTTLE_THRESHOLD or v_ego <= MIN_ALLOW_THROTTLE_SPEED
 
     if not self.allow_throttle:
-      clipped_accel_coast = max(accel_coast, accel_limits_turns[0])
-      clipped_accel_coast_interp = np.interp(v_ego, [MIN_ALLOW_THROTTLE_SPEED, MIN_ALLOW_THROTTLE_SPEED*2], [accel_limits_turns[1], clipped_accel_coast])
-      accel_limits_turns[1] = min(accel_limits_turns[1], clipped_accel_coast_interp)
+      clipped_accel_coast = max(accel_coast, accel_clip[0])
+      clipped_accel_coast_interp = np.interp(v_ego, [MIN_ALLOW_THROTTLE_SPEED, MIN_ALLOW_THROTTLE_SPEED*2], [accel_clip[1], clipped_accel_coast])
+      accel_clip[1] = min(accel_clip[1], clipped_accel_coast_interp)
 
     if force_slow_decel:
       v_cruise = 0.0
-    # clip limits, cannot init MPC outside of bounds
-    accel_limits_turns[0] = min(accel_limits_turns[0], self.a_desired + 0.05)
-    accel_limits_turns[1] = max(accel_limits_turns[1], self.a_desired - 0.05)
 
     self.mpc.set_weights(prev_accel_constraint, personality=sm['selfdriveState'].personality)
-    self.mpc.set_accel_limits(accel_limits_turns[0], accel_limits_turns[1])
     self.mpc.set_cur_state(self.v_desired_filter.x, self.a_desired)
     self.mpc.update(sm['radarState'], v_cruise, x, v, a, j, personality=sm['selfdriveState'].personality)
 
@@ -178,6 +175,15 @@ class LongitudinalPlanner:
     self.a_desired = float(np.interp(self.dt, CONTROL_N_T_IDX, self.a_desired_trajectory))
     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,
+                                                                        action_t=action_t, vEgoStopping=self.CP.vEgoStopping)
+
+    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)
+    self.output_a_target = np.clip(output_a_target, accel_clip[0], accel_clip[1])
+    self.prev_accel_clip = accel_clip
+
   def publish(self, sm, pm):
     plan_send = messaging.new_message('longitudinalPlan')
 
@@ -196,11 +202,8 @@ class LongitudinalPlanner:
     longitudinalPlan.longitudinalPlanSource = self.mpc.source
     longitudinalPlan.fcw = self.fcw
 
-    action_t =  self.CP.longitudinalActuatorDelay + DT_MDL
-    a_target, should_stop = get_accel_from_plan(longitudinalPlan.speeds, longitudinalPlan.accels,
-                                                action_t=action_t, vEgoStopping=self.CP.vEgoStopping)
-    longitudinalPlan.aTarget = float(a_target)
-    longitudinalPlan.shouldStop = bool(should_stop)
+    longitudinalPlan.aTarget = float(self.output_a_target)
+    longitudinalPlan.shouldStop = bool(self.output_should_stop)
     longitudinalPlan.allowBrake = True
     longitudinalPlan.allowThrottle = bool(self.allow_throttle)
 

selfdrive/debug/clear_dtc.py

@@ -4,6 +4,7 @@ import argparse
 from subprocess import check_output, CalledProcessError
 from opendbc.car.carlog import carlog
 from opendbc.car.uds import UdsClient, MessageTimeoutError, SESSION_TYPE, DTC_GROUP_TYPE
+from opendbc.safety import Safety
 from panda import Panda
 
 parser = argparse.ArgumentParser(description="clear DTC status")
@@ -24,7 +25,7 @@ except CalledProcessError as e:
     raise e
 
 panda = Panda()
-panda.set_safety_mode(Panda.SAFETY_ELM327)
+panda.set_safety_mode(Safety.SAFETY_ELM327)
 uds_client = UdsClient(panda, args.addr, bus=args.bus)
 print("extended diagnostic session ...")
 try:

selfdrive/debug/hyundai_enable_radar_points.py

@@ -18,6 +18,7 @@ from subprocess import check_output, CalledProcessError
 
 from opendbc.car.carlog import carlog
 from opendbc.car.uds import UdsClient, SESSION_TYPE, DATA_IDENTIFIER_TYPE
+from opendbc.safety import Safety
 from panda.python import Panda
 
 class ConfigValues(NamedTuple):
@@ -96,7 +97,7 @@ if __name__ == "__main__":
     sys.exit(0)
 
   panda = Panda()
-  panda.set_safety_mode(Panda.SAFETY_ELM327)
+  panda.set_safety_mode(Safety.SAFETY_ELM327)
   uds_client = UdsClient(panda, 0x7D0, bus=args.bus)
 
   print("\n[START DIAGNOSTIC SESSION]")

selfdrive/debug/read_dtc_status.py

@@ -4,6 +4,7 @@ import argparse
 from subprocess import check_output, CalledProcessError
 from opendbc.car.carlog import carlog
 from opendbc.car.uds import UdsClient, SESSION_TYPE, DTC_REPORT_TYPE, DTC_STATUS_MASK_TYPE, get_dtc_num_as_str, get_dtc_status_names
+from opendbc.safety import Safety
 from panda import Panda
 
 parser = argparse.ArgumentParser(description="read DTC status")
@@ -24,7 +25,7 @@ except CalledProcessError as e:
     raise e
 
 panda = Panda()
-panda.set_safety_mode(Panda.SAFETY_ELM327)
+panda.set_safety_mode(Safety.SAFETY_ELM327)
 uds_client = UdsClient(panda, args.addr, bus=args.bus)
 print("extended diagnostic session ...")
 uds_client.diagnostic_session_control(SESSION_TYPE.EXTENDED_DIAGNOSTIC)

selfdrive/debug/vw_mqb_config.py

@@ -6,6 +6,7 @@ from enum import IntEnum
 from opendbc.car.carlog import carlog
 from opendbc.car.uds import UdsClient, MessageTimeoutError, NegativeResponseError, SESSION_TYPE,\
   DATA_IDENTIFIER_TYPE, ACCESS_TYPE
+from opendbc.safety import Safety
 from panda import Panda
 from datetime import date
 
@@ -38,7 +39,7 @@ if __name__ == "__main__":
     carlog.setLevel('DEBUG')
 
   panda = Panda()
-  panda.set_safety_mode(Panda.SAFETY_ELM327)
+  panda.set_safety_mode(Safety.SAFETY_ELM327)
   bus = 1 if panda.has_obd() else 0
   uds_client = UdsClient(panda, MQB_EPS_CAN_ADDR, MQB_EPS_CAN_ADDR + RX_OFFSET, bus, timeout=0.2)
 

selfdrive/locationd/calibrationd.py

@@ -6,7 +6,6 @@ While the roll calibration is a real value that can be estimated, here we assume
 and the image input into the neural network is not corrected for roll.
 '''
 
-import gc
 import os
 import capnp
 import numpy as np
@@ -16,7 +15,7 @@ from cereal import log
 import cereal.messaging as messaging
 from openpilot.common.conversions import Conversions as CV
 from openpilot.common.params import Params
-from openpilot.common.realtime import set_realtime_priority
+from openpilot.common.realtime import config_realtime_process
 from openpilot.common.transformations.orientation import rot_from_euler, euler_from_rot
 from openpilot.common.swaglog import cloudlog
 
@@ -256,8 +255,7 @@ class Calibrator:
 
 
 def main() -> NoReturn:
-  gc.disable()
-  set_realtime_priority(1)
+  config_realtime_process([0, 1, 2, 3], 5)
 
   pm = messaging.PubMaster(['liveCalibration'])
   sm = messaging.SubMaster(['cameraOdometry', 'carState', 'carParams'], poll='cameraOdometry')

selfdrive/modeld/dmonitoringmodeld.py

@@ -8,7 +8,6 @@ if TICI:
   os.environ['QCOM'] = '1'
 else:
   from openpilot.selfdrive.modeld.runners.ort_helpers import make_onnx_cpu_runner
-import gc
 import math
 import time
 import pickle
@@ -21,7 +20,7 @@ from cereal import messaging
 from cereal.messaging import PubMaster, SubMaster
 from msgq.visionipc import VisionIpcClient, VisionStreamType, VisionBuf
 from openpilot.common.swaglog import cloudlog
-from openpilot.common.realtime import set_realtime_priority
+from openpilot.common.realtime import config_realtime_process
 from openpilot.common.transformations.model import dmonitoringmodel_intrinsics, DM_INPUT_SIZE
 from openpilot.common.transformations.camera import _ar_ox_fisheye, _os_fisheye
 from openpilot.selfdrive.modeld.models.commonmodel_pyx import CLContext, MonitoringModelFrame
@@ -140,9 +139,8 @@ def get_driverstate_packet(model_output: np.ndarray, frame_id: int, location_ts:
 
 
 def main():
-  gc.disable()
   setproctitle(PROCESS_NAME)
-  set_realtime_priority(1)
+  config_realtime_process([0, 1, 2, 3], 5)
 
   sentry.set_tag("daemon", PROCESS_NAME)
   cloudlog.bind(daemon=PROCESS_NAME)

selfdrive/monitoring/dmonitoringd.py

@@ -1,15 +1,12 @@
 #!/usr/bin/env python3
-import gc
-
 import cereal.messaging as messaging
 from openpilot.common.params import Params
-from openpilot.common.realtime import set_realtime_priority
+from openpilot.common.realtime import config_realtime_process
 from openpilot.selfdrive.monitoring.helpers import DriverMonitoring
 
 
 def dmonitoringd_thread():
-  gc.disable()
-  set_realtime_priority(2)
+  config_realtime_process([0, 1, 2, 3], 5)
 
   params = Params()
   pm = messaging.PubMaster(['driverMonitoringState'])

selfdrive/selfdrived/selfdrived.py

@@ -7,7 +7,7 @@ import cereal.messaging as messaging
 
 from cereal import car, log
 from msgq.visionipc import VisionIpcClient, VisionStreamType
-from panda import ALTERNATIVE_EXPERIENCE
+from opendbc.safety import ALTERNATIVE_EXPERIENCE
 
 
 from openpilot.common.params import Params

selfdrive/test/longitudinal_maneuvers/maneuver.py

@@ -66,7 +66,7 @@ class Maneuver:
         print("Crashed!!!!")
         valid = False
 
-      if self.ensure_start and log['v_rel'] > 0 and log['speeds'][-1] <= 0.1:
+      if self.ensure_start and log['v_rel'] > 0 and log['acceleration'] < 1e-3:
         print('LongitudinalPlanner not starting!')
         valid = False
 

selfdrive/test/longitudinal_maneuvers/plant.py

@@ -30,8 +30,8 @@ class Plant:
 
     self.distance = 0.
     self.speed = speed
+    self.should_stop = False
     self.acceleration = 0.0
-    self.speeds = []
 
     # lead car
     self.lead_relevancy = lead_relevancy
@@ -134,9 +134,9 @@ class Plant:
           'liveParameters': lp.liveParameters,
           'modelV2': model.modelV2}
     self.planner.update(sm)
-    self.speed = self.planner.v_desired_filter.x
-    self.acceleration = self.planner.a_desired
-    self.speeds = self.planner.v_desired_trajectory.tolist()
+    self.acceleration = self.planner.output_a_target
+    self.speed = self.speed + self.acceleration * self.ts
+    self.should_stop = self.planner.output_should_stop
     fcw = self.planner.fcw
     self.distance_lead = self.distance_lead + v_lead * self.ts
 
@@ -168,7 +168,7 @@ class Plant:
       "distance": self.distance,
       "speed": self.speed,
       "acceleration": self.acceleration,
-      "speeds": self.speeds,
+      "should_stop": self.should_stop,
       "distance_lead": self.distance_lead,
       "fcw": fcw,
     }

selfdrive/test/longitudinal_maneuvers/test_longitudinal.py

@@ -150,10 +150,7 @@ def create_maneuvers(kwargs):
       enabled=False,
       **kwargs,
     ),
-  ]
-  if not kwargs['e2e']:
-    # allow_throttle won't trigger with e2e
-    maneuvers.append(Maneuver(
+    Maneuver(
       "slow to 5m/s with allow_throttle = False and pitch = +0.1",
       duration=30.,
       initial_speed=20.,
@@ -164,7 +161,7 @@ def create_maneuvers(kwargs):
       breakpoints=[0.0, 2., 2.01],
       ensure_slowdown=True,
       **kwargs,
-    ))
+    )]
   if not kwargs['force_decel']:
     # controls relies on planner commanding to move for stock-ACC resume spamming
     maneuvers.append(Maneuver(

selfdrive/test/process_replay/migration.py

@@ -6,15 +6,15 @@ import traceback
 
 from cereal import messaging, car, log
 from opendbc.car.fingerprints import MIGRATION
-from opendbc.car.toyota.values import EPS_SCALE
-from opendbc.car.ford.values import CAR as FORD, FordFlags
+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 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.system.manager.process_config import managed_processes
 from openpilot.tools.lib.logreader import LogIterable
-from panda import Panda
 
 MessageWithIndex = tuple[int, capnp.lib.capnp._DynamicStructReader]
 MigrationOps = tuple[list[tuple[int, capnp.lib.capnp._DynamicStructReader]], list[capnp.lib.capnp._DynamicStructReader], list[int]]
@@ -269,19 +269,19 @@ def migrate_carOutput(msgs):
 def migrate_pandaStates(msgs):
   # TODO: safety param migration should be handled automatically
   safety_param_migration = {
-    "TOYOTA_PRIUS": EPS_SCALE["TOYOTA_PRIUS"] | Panda.FLAG_TOYOTA_STOCK_LONGITUDINAL,
-    "TOYOTA_RAV4": EPS_SCALE["TOYOTA_RAV4"] | Panda.FLAG_TOYOTA_ALT_BRAKE,
-    "KIA_EV6": Panda.FLAG_HYUNDAI_EV_GAS | Panda.FLAG_HYUNDAI_CANFD_HDA2,
+    "TOYOTA_PRIUS": EPS_SCALE["TOYOTA_PRIUS"] | ToyotaSafetyFlags.FLAG_TOYOTA_STOCK_LONGITUDINAL,
+    "TOYOTA_RAV4": EPS_SCALE["TOYOTA_RAV4"] | ToyotaSafetyFlags.FLAG_TOYOTA_ALT_BRAKE,
+    "KIA_EV6": HyundaiSafetyFlags.FLAG_HYUNDAI_EV_GAS | HyundaiSafetyFlags.FLAG_HYUNDAI_CANFD_HDA2,
   }
   # TODO: get new Ford route
-  safety_param_migration |= {car: Panda.FLAG_FORD_LONG_CONTROL for car in (set(FORD) - FORD.with_flags(FordFlags.CANFD))}
+  safety_param_migration |= {car: FordSafetyFlags.FLAG_FORD_LONG_CONTROL for car in (set(FORD) - FORD.with_flags(FordFlags.CANFD))}
 
   # Migrate safety param base on carParams
   CP = next((m.carParams for _, m in msgs if m.which() == 'carParams'), None)
   assert CP is not None, "carParams message not found"
   fingerprint = MIGRATION.get(CP.carFingerprint, CP.carFingerprint)
   if fingerprint in safety_param_migration:
-    safety_param = safety_param_migration[fingerprint]
+    safety_param = safety_param_migration[fingerprint].value
   elif len(CP.safetyConfigs):
     safety_param = CP.safetyConfigs[0].safetyParam
     if CP.safetyConfigs[0].safetyParamDEPRECATED != 0:

selfdrive/test/process_replay/process_replay.py

@@ -18,11 +18,11 @@ from cereal import car
 from cereal.services import SERVICE_LIST
 from msgq.visionipc import VisionIpcServer, get_endpoint_name as vipc_get_endpoint_name
 from opendbc.car.car_helpers import get_car, interfaces
+from opendbc.safety import ALTERNATIVE_EXPERIENCE
 from openpilot.common.params import Params
 from openpilot.common.prefix import OpenpilotPrefix
 from openpilot.common.timeout import Timeout
 from openpilot.common.realtime import DT_CTRL
-from panda.python import ALTERNATIVE_EXPERIENCE
 from openpilot.selfdrive.car.card import can_comm_callbacks
 from openpilot.system.manager.process_config import managed_processes
 from openpilot.selfdrive.test.process_replay.vision_meta import meta_from_camera_state, available_streams

selfdrive/test/process_replay/ref_commit

@@ -1 +1 @@
-95f1384edc0dc00959b0e804de1aaafc35d2f15f
+b8595cc8351043a7c49b41e7c36f93ffd2e3dc6d

selfdrive/test/test_onroad.py

@@ -34,7 +34,7 @@ CPU usage budget
 TEST_DURATION = 25
 LOG_OFFSET = 8
 
-MAX_TOTAL_CPU = 275.  # total for all 8 cores
+MAX_TOTAL_CPU = 280.  # total for all 8 cores
 PROCS = {
   # Baseline CPU usage by process
   "selfdrive.controls.controlsd": 16.0,
@@ -42,7 +42,7 @@ PROCS = {
   "selfdrive.car.card": 26.0,
   "./loggerd": 14.0,
   "./encoderd": 17.0,
-  "./camerad": 14.5,
+  "./camerad": 10.0,
   "selfdrive.controls.plannerd": 9.0,
   "./ui": 18.0,
   "selfdrive.locationd.paramsd": 9.0,
@@ -99,12 +99,12 @@ TIMINGS = {
   "wideRoadCameraState": [1.5, 0.35],
 }
 
-LOGS_SIZE_RATE = {
-  "qlog.zst": 0.0083,
-  "rlog.zst": 0.135,
-  "qcamera.ts": 0.03828,
+LOGS_SIZE = {  # MB per segment
+  "qlog.zst": 0.5,
+  "rlog.zst": 8.1,
+  "qcamera.ts": 2.3,
 }
-LOGS_SIZE_RATE.update(dict.fromkeys(['ecamera.hevc', 'fcamera.hevc'], 1.2740))
+LOGS_SIZE.update(dict.fromkeys(['ecamera.hevc', 'fcamera.hevc', 'dcamera.hevc'], 76.5))
 
 
 def cputime_total(ct):
@@ -126,6 +126,7 @@ class TestOnroad:
     # setup env
     params = Params()
     params.remove("CurrentRoute")
+    params.put_bool("RecordFront", True)
     set_params_enabled()
     os.environ['REPLAY'] = '1'
     os.environ['TESTING_CLOSET'] = '1'
@@ -212,12 +213,13 @@ class TestOnroad:
     big_logs = [f for f, n in cnt.most_common(3) if n / sum(cnt.values()) > 30.]
     assert len(big_logs) == 0, f"Log spam: {big_logs}"
 
-  def test_log_sizes(self):
+  def test_log_sizes(self, subtests):
     for f, sz in self.log_sizes.items():
-      rate = LOGS_SIZE_RATE[f.name]
-      minn = rate * TEST_DURATION * 0.8
-      maxx = rate * TEST_DURATION * 1.2
-      assert minn < sz <  maxx
+      rate = LOGS_SIZE[f.name]/60.
+      minn = rate * TEST_DURATION * 0.5
+      maxx = rate * TEST_DURATION * 1.5
+      with subtests.test(file=f.name):
+        assert minn < sz <  maxx
 
   def test_ui_timings(self):
     result = "\n"
@@ -311,24 +313,8 @@ class TestOnroad:
   def test_gpu_usage(self):
     assert self.gpu_procs == {"weston", "ui", "camerad", "selfdrive.modeld.modeld", "selfdrive.modeld.dmonitoringmodeld"}
 
-  def test_camera_processing_time(self):
-    result = "\n"
-    result += "------------------------------------------------\n"
-    result += "-------------- ImgProc Timing ------------------\n"
-    result += "------------------------------------------------\n"
-
-    ts = []
-    for s in ['roadCameraState', 'driverCameraState', 'wideCameraState']:
-      ts.extend(getattr(m, s).processingTime for m in self.msgs[s])
-    assert min(ts) < 0.025, f"high execution time: {min(ts)}"
-    result += f"execution time: min  {min(ts):.5f}s\n"
-    result += f"execution time: max  {max(ts):.5f}s\n"
-    result += f"execution time: mean {np.mean(ts):.5f}s\n"
-    result += "------------------------------------------------\n"
-    print(result)
-
   @pytest.mark.skip("TODO: enable once timings are fixed")
-  def test_camera_frame_timings(self):
+  def test_camera_frame_timings(self, subtests):
     result = "\n"
     result += "------------------------------------------------\n"
     result += "-----------------  SoF Timing ------------------\n"
@@ -337,11 +323,12 @@ class TestOnroad:
       ts = [getattr(m, m.which()).timestampSof for m in self.lr if name in m.which()]
       d_ms = np.diff(ts) / 1e6
       d50 = np.abs(d_ms-50)
-      assert max(d50) < 1.0, f"high sof delta vs 50ms: {max(d50)}"
       result += f"{name} sof delta vs 50ms: min  {min(d50):.5f}s\n"
       result += f"{name} sof delta vs 50ms: max  {max(d50):.5f}s\n"
       result += f"{name} sof delta vs 50ms: mean {d50.mean():.5f}s\n"
-      result += "------------------------------------------------\n"
+      with subtests.test(camera=name):
+        assert max(d50) < 1.0, f"high SOF delta vs 50ms: {max(d50)}"
+    result += "------------------------------------------------\n"
     print(result)
 
   def test_mpc_execution_timings(self):

system/camerad/cameras/camera_qcom2.cc

@@ -55,7 +55,7 @@ public:
 
   float fl_pix = 0;
 
-  CameraState(SpectraMaster *master, const CameraConfig &config) : camera(master, config, config.stream_type == VISION_STREAM_DRIVER ? ISP_BPS_PROCESSED : ISP_IFE_PROCESSED) {};
+  CameraState(SpectraMaster *master, const CameraConfig &config) : camera(master, config, config.stream_type == VISION_STREAM_ROAD ? ISP_RAW_OUTPUT : ISP_IFE_PROCESSED) {};
   ~CameraState();
   void init(VisionIpcServer *v, cl_device_id device_id, cl_context ctx);
   void update_exposure_score(float desired_ev, int exp_t, int exp_g_idx, float exp_gain);
@@ -283,7 +283,7 @@ void camerad_thread() {
 
   // *** per-cam init ***
   std::vector<std::unique_ptr<CameraState>> cams;
-  for (const auto &config : {WIDE_ROAD_CAMERA_CONFIG, ROAD_CAMERA_CONFIG, DRIVER_CAMERA_CONFIG}) {
+  for (const auto &config : {WIDE_ROAD_CAMERA_CONFIG, DRIVER_CAMERA_CONFIG, ROAD_CAMERA_CONFIG}) {
     auto cam = std::make_unique<CameraState>(&m, config);
     cam->init(&v, device_id, ctx);
     cams.emplace_back(std::move(cam));

system/hardware/tici/tests/test_power_draw.py

@@ -31,7 +31,7 @@ class Proc:
 
 
 PROCS = [
-  Proc(['camerad'], 1.6, msgs=['roadCameraState', 'wideRoadCameraState', 'driverCameraState']),
+  Proc(['camerad'], 1.75, msgs=['roadCameraState', 'wideRoadCameraState', 'driverCameraState']),
   Proc(['modeld'], 1.12, atol=0.2, msgs=['modelV2']),
   Proc(['dmonitoringmodeld'], 0.6, msgs=['driverStateV2']),
   Proc(['encoderd'], 0.23, msgs=[]),

tools/sim/lib/simulated_car.py

@@ -1,11 +1,12 @@
+import traceback
 import cereal.messaging as messaging
 
 from opendbc.can.packer import CANPacker
 from opendbc.can.parser import CANParser
+from opendbc.car.honda.values import HondaSafetyFlags
 from openpilot.common.params import Params
 from openpilot.selfdrive.pandad.pandad_api_impl import can_list_to_can_capnp
 from openpilot.tools.sim.lib.common import SimulatorState
-from panda.python import Panda
 
 
 class SimulatedCar:
@@ -94,14 +95,18 @@ class SimulatedCar:
       'controlsAllowed': True,
       'safetyModel': 'hondaBosch',
       'alternativeExperience': self.sm["carParams"].alternativeExperience,
-      'safetyParam': Panda.FLAG_HONDA_RADARLESS | Panda.FLAG_HONDA_BOSCH_LONG,
+      'safetyParam': HondaSafetyFlags.FLAG_HONDA_RADARLESS.value | HondaSafetyFlags.FLAG_HONDA_BOSCH_LONG.value,
     }
     self.pm.send('pandaStates', dat)
 
   def update(self, simulator_state: SimulatorState):
-    self.send_can_messages(simulator_state)
+    try:
+      self.send_can_messages(simulator_state)
 
-    if self.idx % 50 == 0: # only send panda states at 2hz
-      self.send_panda_state(simulator_state)
+      if self.idx % 50 == 0: # only send panda states at 2hz
+        self.send_panda_state(simulator_state)
 
-    self.idx += 1
+      self.idx += 1
+    except Exception:
+      traceback.print_exc()
+      raise