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[torqued] Update offline values (#26261)

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* add qlog mode to torqued

* update offline valujes from qlogs

* resollve comments

* update refs

* resolve comments
old-commit-hash: b158c016cb
taco
Vivek Aithal 3 years ago committed by GitHub
parent 72f6a3b56d
commit d843347126
4 changed files with 33 additions and 22 deletions
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  1. 1
      selfdrive/car/torque_data/override.yaml
  2. 29
      selfdrive/car/torque_data/params.yaml
  3. 23
      selfdrive/locationd/torqued.py
  4. 2
      selfdrive/test/process_replay/ref_commit

1
selfdrive/car/torque_data/override.yaml
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@ -21,7 +21,6 @@ FORD FOCUS 4TH GEN: [.nan, 1.5, .nan]
COMMA BODY: [.nan, 1000, .nan]
# Totally new cars
KIA EV6 2022: [3.5, 3.0, 0.0]
RAM 1500 5TH GEN: [2.0, 2.0, 0.0]
RAM HD 5TH GEN: [1.4, 1.4, 0.0]
SUBARU OUTBACK 6TH GEN: [2.3, 2.3, 0.11]

29
selfdrive/car/torque_data/params.yaml
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@ -39,17 +39,18 @@ HYUNDAI SONATA 2020: [2.9638737459977467, 2.1259108157250735, 0.0781366561692759
HYUNDAI SONATA HYBRID 2021: [2.8990264092395734, 2.061410192222139, 0.0899805488717382]
JEEP GRAND CHEROKEE 2019: [1.7321233388827006, 1.289689569171081, 0.15046331002097185]
JEEP GRAND CHEROKEE V6 2018: [1.8776598027756923, 1.4057367824262523, 0.11725947414922003]
KIA EV6 2022: [3.2, 3.0, 0.05]
KIA K5 2021: [2.405339728085138, 1.460032270828705, 0.11650989850813716]
KIA NIRO EV 2020: [2.9215954981365337, 2.1500583840260044, 0.09236802474810267]
KIA SORENTO GT LINE 2018: [2.464854685101844, 1.5335274218367956, 0.12056170567599558]
KIA STINGER GT2 2018: [2.7499043387418967, 1.849652021986449, 0.12048334239559202]
LEXUS ES 2019: [2.0203086922726112, 2.134803912579666, 0.12757526789308554]
LEXUS ES HYBRID 2019: [2.392442298703042, 1.863360677810788, 0.17690002108856212]
LEXUS ES 2019: [1.935835, 2.134803912579666, 0.093439]
LEXUS ES HYBRID 2019: [2.135678, 1.863360677810788, 0.109627]
LEXUS NX 2018: [2.302625600642627, 2.1382378491466625, 0.14986840878892838]
LEXUS NX 2020: [2.4331999786982936, 2.1045680431705414, 0.14099899317761067]
LEXUS NX HYBRID 2018: [2.4025593501080955, 1.8080446063815507, 0.15349361249519017]
LEXUS RX 2016: [1.5876816543130423, 1.0427699298523752, 0.21334066732397142]
LEXUS RX 2020: [1.5228812994274734, 1.431102486563665, 0.2093316728710659]
LEXUS RX 2020: [1.5228812994274734, 1.431102486563665, 0.164117]
LEXUS RX HYBRID 2017: [1.6984261557042386, 1.3211501880159107, 0.1820354534928893]
LEXUS RX HYBRID 2020: [1.5522309889823778, 1.255230465866663, 0.2220954003055114]
MAZDA CX-9 2021: [1.7601682915983443, 1.0889677335154337, 0.17713792194297195]
@ -62,31 +63,31 @@ TOYOTA AVALON 2019: [1.7036141952825095, 1.239619084240008, 0.08459830394899492]
TOYOTA AVALON 2022: [2.3154403649717357, 2.7777922854327124, 0.11453999639164605]
TOYOTA C-HR 2018: [1.5591084333664578, 1.271271459066948, 0.20259087058453193]
TOYOTA C-HR 2021: [1.7678810166088303, 1.3742176337919942, 0.2319674583741509]
TOYOTA CAMRY 2018: [2.1172995371905015, 1.7156177222420887, 0.13519250664782062]
TOYOTA CAMRY 2021: [2.6922769557433055, 2.3476510120007434, 0.1450430192989234]
TOYOTA CAMRY HYBRID 2018: [2.0974120828287774, 1.7996193116697359, 0.13823613467632756]
TOYOTA CAMRY HYBRID 2021: [2.6426668350384457, 2.3901492458927986, 0.16103875108816076]
TOYOTA CAMRY 2018: [2.1172995371905015, 1.7156177222420887, 0.105192506]
TOYOTA CAMRY 2021: [2.446083, 2.3476510120007434, 0.121615]
TOYOTA CAMRY HYBRID 2018: [1.996333, 1.7996193116697359, 0.112565]
TOYOTA CAMRY HYBRID 2021: [2.263582, 2.3901492458927986, 0.115257]
TOYOTA COROLLA 2017: [3.117154369115421, 1.8438132575043773, 0.12289685869250652]
TOYOTA COROLLA HYBRID TSS2 2019: [1.9079729107361805, 1.8118712531729109, 0.22251440891543514]
TOYOTA COROLLA TSS2 2019: [2.0742917676766712, 1.9258612322678952, 0.16888685704519352]
TOYOTA HIGHLANDER 2017: [1.8696367437248915, 1.626293990451463, 0.17485372210240796]
TOYOTA HIGHLANDER 2020: [2.022340166827233, 1.6183134804881791, 0.14592306380054457]
TOYOTA HIGHLANDER HYBRID 2018: [1.9421825202382728, 1.6433903296845025, 0.16928956792275918]
TOYOTA HIGHLANDER HYBRID 2020: [2.103373061114133, 2.104015182965606, 0.14447040132184993]
TOYOTA HIGHLANDER HYBRID 2018: [1.752033, 1.6433903296845025, 0.144600]
TOYOTA HIGHLANDER HYBRID 2020: [1.901174, 2.104015182965606, 0.14447040132184993]
TOYOTA MIRAI 2021: [2.506899832157829, 1.7417213930750164, 0.20182618449440565]
TOYOTA PRIUS 2017: [2.0183401513314294, 1.5023147650693636, 0.20856908464957724]
TOYOTA PRIUS TSS2 2021: [2.327639738920072, 1.9104337425537743, 0.2030762265549664]
TOYOTA PRIUS 2017: [1.746445, 1.5023147650693636, 0.151515]
TOYOTA PRIUS TSS2 2021: [1.972600, 1.9104337425537743, 0.170968]
TOYOTA RAV4 2017: [2.085695074355425, 2.2142832316984733, 0.13339165270103975]
TOYOTA RAV4 2019: [2.5038362866776835, 2.0993589721530252, 0.1552425356342368]
TOYOTA RAV4 2019: [2.331293, 2.0993589721530252, 0.129822]
TOYOTA RAV4 2019 8965: [2.5084506298290377, 2.4216520504763475, 0.11992835265067918]
TOYOTA RAV4 2019 x02: [2.7209621987605024, 2.2148637653781593, 0.10862567142268198]
TOYOTA RAV4 HYBRID 2017: [1.9796257271652042, 1.7503987331707576, 0.14628860048885406]
TOYOTA RAV4 HYBRID 2019: [2.2271858492309153, 2.074844961405639, 0.14382216826893632]
TOYOTA RAV4 HYBRID 2019 8965: [2.1077397198131336, 1.8162215166877735, 0.13891369391200137]
TOYOTA RAV4 HYBRID 2019 x02: [2.803624333289342, 2.272367966572498, 0.11364569214387774]
TOYOTA RAV4 HYBRID 2022: [2.241883248393209, 1.9304407208090029, 0.1565442715453653]
TOYOTA RAV4 HYBRID 2022: [2.241883248393209, 1.9304407208090029, 0.112174]
TOYOTA RAV4 HYBRID 2022 x02: [3.044930631831037, 2.3979189796380918, 0.14023209146703736]
TOYOTA SIENNA 2018: [1.8660896232147548, 1.3208264576110418, 0.18799149615227198]
TOYOTA SIENNA 2018: [1.689726, 1.3208264576110418, 0.140456]
VOLKSWAGEN ARTEON 1ST GEN: [1.45136518053819, 1.3639364049316804, 0.23806361745695032]
VOLKSWAGEN ATLAS 1ST GEN: [1.4677006726964945, 1.6733266634075656, 0.12959584092073367]
VOLKSWAGEN GOLF 7TH GEN: [1.3750394140491293, 1.5814743077200641, 0.2018321939386586]

23
selfdrive/locationd/torqued.py
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@ -16,7 +16,9 @@ from selfdrive.controls.lib.vehicle_model import ACCELERATION_DUE_TO_GRAVITY
HISTORY = 5 # secs
POINTS_PER_BUCKET = 1500
MIN_POINTS_TOTAL = 4000
MIN_POINTS_TOTAL_QLOG = 800
FIT_POINTS_TOTAL = 2000
FIT_POINTS_TOTAL_QLOG = 800
MIN_VEL = 15 # m/s
FRICTION_FACTOR = 1.5 # ~85% of data coverage
FACTOR_SANITY = 0.3
@ -26,7 +28,7 @@ MIN_FILTER_DECAY = 50
MAX_FILTER_DECAY = 250
LAT_ACC_THRESHOLD = 1
STEER_BUCKET_BOUNDS = [(-0.5, -0.3), (-0.3, -0.2), (-0.2, -0.1), (-0.1, 0), (0, 0.1), (0.1, 0.2), (0.2, 0.3), (0.3, 0.5)]
MIN_BUCKET_POINTS = [100, 300, 500, 500, 500, 500, 300, 100]
MIN_BUCKET_POINTS = np.array([100, 300, 500, 500, 500, 500, 300, 100])
MAX_RESETS = 5.0
MAX_INVALID_THRESHOLD = 10
MIN_ENGAGE_BUFFER = 2 # secs
@ -58,10 +60,11 @@ class NPQueue:
class PointBuckets:
def __init__(self, x_bounds, min_points):
def __init__(self, x_bounds, min_points, min_points_total):
self.x_bounds = x_bounds
self.buckets = {bounds: NPQueue(maxlen=POINTS_PER_BUCKET, rowsize=3) for bounds in x_bounds}
self.buckets_min_points = {bounds: min_point for bounds, min_point in zip(x_bounds, min_points)}
self.min_points_total = min_points_total
def bucket_lengths(self):
return [len(v) for v in self.buckets.values()]
@ -70,7 +73,7 @@ class PointBuckets:
return sum(self.bucket_lengths())
def is_valid(self):
return all(len(v) >= min_pts for v, min_pts in zip(self.buckets.values(), self.buckets_min_points.values())) and (self.__len__() >= MIN_POINTS_TOTAL)
return all(len(v) >= min_pts for v, min_pts in zip(self.buckets.values(), self.buckets_min_points.values())) and (self.__len__() >= self.min_points_total)
def add_point(self, x, y):
for bound_min, bound_max in self.x_bounds:
@ -90,9 +93,17 @@ class PointBuckets:
class TorqueEstimator:
def __init__(self, CP):
def __init__(self, CP, decimated=False):
self.hist_len = int(HISTORY / DT_MDL)
self.lag = CP.steerActuatorDelay + .2 # from controlsd
if decimated:
self.min_bucket_points = MIN_BUCKET_POINTS / 10
self.min_points_total = MIN_POINTS_TOTAL_QLOG
self.fit_points = FIT_POINTS_TOTAL_QLOG
else:
self.min_bucket_points = MIN_BUCKET_POINTS
self.min_points_total = MIN_POINTS_TOTAL
self.fit_points = FIT_POINTS_TOTAL
self.offline_friction = 0.0
self.offline_latAccelFactor = 0.0
@ -157,10 +168,10 @@ class TorqueEstimator:
self.invalid_values_tracker = 0.0
self.decay = MIN_FILTER_DECAY
self.raw_points = defaultdict(lambda: deque(maxlen=self.hist_len))
self.filtered_points = PointBuckets(x_bounds=STEER_BUCKET_BOUNDS, min_points=MIN_BUCKET_POINTS)
self.filtered_points = PointBuckets(x_bounds=STEER_BUCKET_BOUNDS, min_points=self.min_bucket_points, min_points_total=self.min_points_total)
def estimate_params(self):
points = self.filtered_points.get_points(FIT_POINTS_TOTAL)
points = self.filtered_points.get_points(self.fit_points)
# total least square solution as both x and y are noisy observations
# this is empirically the slope of the hysteresis parallelogram as opposed to the line through the diagonals
try:

2
selfdrive/test/process_replay/ref_commit
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@ -1 +1 @@
fbafde6f1c46b50c219c3ec3121b94ee0848a7be
f4ea2499a95e198914fd275a8380178e8ff65a31
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