openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for over 200 supported car makes and models.
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#!/usr/bin/env python3
import os
import math
import unittest
import hypothesis.strategies as st
from hypothesis import Phase, given, settings
import importlib
from parameterized import parameterized
from cereal import car
from openpilot.common.realtime import DT_CTRL
from openpilot.selfdrive.car import gen_empty_fingerprint
from openpilot.selfdrive.car.car_helpers import interfaces
from openpilot.selfdrive.car.fingerprints import all_known_cars
from openpilot.selfdrive.car.fw_versions import FW_VERSIONS
from openpilot.selfdrive.car.interfaces import get_interface_attr
from openpilot.selfdrive.test.fuzzy_generation import DrawType, FuzzyGenerator
ALL_ECUS = list({ecu for ecus in FW_VERSIONS.values() for ecu in ecus.keys()})
MAX_EXAMPLES = int(os.environ.get('MAX_EXAMPLES', '5'))
def get_fuzzy_car_interface_args(draw: DrawType) -> dict:
# Fuzzy CAN fingerprints and FW versions to test more states of the CarInterface
fingerprint_strategy = st.fixed_dictionaries({key: st.dictionaries(st.integers(min_value=0, max_value=0x800),
st.integers(min_value=0, max_value=64)) for key in
gen_empty_fingerprint()})
# only pick from possible ecus to reduce search space
car_fw_strategy = st.lists(st.sampled_from(ALL_ECUS))
params_strategy = st.fixed_dictionaries({
'fingerprints': fingerprint_strategy,
'car_fw': car_fw_strategy,
'experimental_long': st.booleans(),
})
params: dict = draw(params_strategy)
params['car_fw'] = [car.CarParams.CarFw(ecu=fw[0], address=fw[1], subAddress=fw[2] or 0) for fw in params['car_fw']]
return params
class TestCarInterfaces(unittest.TestCase):
@classmethod
def setUpClass(cls):
os.environ['NO_RADAR_SLEEP'] = '1'
# FIXME: Due to the lists used in carParams, Phase.target is very slow and will cause
# many generated examples to overrun when max_examples > ~20, don't use it
@parameterized.expand([(car,) for car in sorted(all_known_cars())])
@settings(max_examples=MAX_EXAMPLES, deadline=500,
phases=(Phase.reuse, Phase.generate, Phase.shrink))
@given(data=st.data())
def test_car_interfaces(self, car_name, data):
CarInterface, CarController, CarState = interfaces[car_name]
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)
car_interface = CarInterface(car_params, CarController, CarState)
assert car_params
assert car_interface
self.assertGreater(car_params.mass, 1)
self.assertGreater(car_params.wheelbase, 0)
# centerToFront is center of gravity to front wheels, assert a reasonable range
self.assertTrue(car_params.wheelbase * 0.3 < car_params.centerToFront < car_params.wheelbase * 0.7)
self.assertGreater(car_params.maxLateralAccel, 0)
# Longitudinal sanity checks
self.assertEqual(len(car_params.longitudinalTuning.kpV), len(car_params.longitudinalTuning.kpBP))
self.assertEqual(len(car_params.longitudinalTuning.kiV), len(car_params.longitudinalTuning.kiBP))
self.assertEqual(len(car_params.longitudinalTuning.deadzoneV), len(car_params.longitudinalTuning.deadzoneBP))
# Lateral sanity checks
if car_params.steerControlType != car.CarParams.SteerControlType.angle:
tune = car_params.lateralTuning
if tune.which() == 'pid':
self.assertTrue(not math.isnan(tune.pid.kf) and tune.pid.kf > 0)
self.assertTrue(len(tune.pid.kpV) > 0 and len(tune.pid.kpV) == len(tune.pid.kpBP))
self.assertTrue(len(tune.pid.kiV) > 0 and len(tune.pid.kiV) == len(tune.pid.kiBP))
elif tune.which() == 'torque':
self.assertTrue(not math.isnan(tune.torque.kf) and tune.torque.kf > 0)
self.assertTrue(not math.isnan(tune.torque.friction) and tune.torque.friction > 0)
elif tune.which() == 'indi':
self.assertTrue(len(tune.indi.outerLoopGainV))
cc_msg = FuzzyGenerator.get_random_msg(data.draw, car.CarControl, real_floats=True)
# Run car interface
now_nanos = 0
CC = car.CarControl.new_message(**cc_msg)
for _ in range(10):
car_interface.update(CC, [])
car_interface.apply(CC, now_nanos)
car_interface.apply(CC, now_nanos)
now_nanos += DT_CTRL * 1e9 # 10 ms
CC = car.CarControl.new_message(**cc_msg)
CC.enabled = True
for _ in range(10):
car_interface.update(CC, [])
car_interface.apply(CC, now_nanos)
car_interface.apply(CC, now_nanos)
now_nanos += DT_CTRL * 1e9 # 10ms
# Test radar interface
RadarInterface = importlib.import_module(f'selfdrive.car.{car_params.carName}.radar_interface').RadarInterface
radar_interface = RadarInterface(car_params)
assert radar_interface
# Run radar interface once
radar_interface.update([])
if not car_params.radarUnavailable and radar_interface.rcp is not None and \
hasattr(radar_interface, '_update') and hasattr(radar_interface, 'trigger_msg'):
radar_interface._update([radar_interface.trigger_msg])
def test_interface_attrs(self):
"""Asserts basic behavior of interface attribute getter"""
num_brands = len(get_interface_attr('CAR'))
self.assertGreaterEqual(num_brands, 13)
# Should return value for all brands when not combining, even if attribute doesn't exist
ret = get_interface_attr('FAKE_ATTR')
self.assertEqual(len(ret), num_brands)
# Make sure we can combine dicts
ret = get_interface_attr('DBC', combine_brands=True)
self.assertGreaterEqual(len(ret), 170)
# We don't support combining non-dicts
ret = get_interface_attr('CAR', combine_brands=True)
self.assertEqual(len(ret), 0)
# If brand has None value, it shouldn't return when ignore_none=True is specified
none_brands = {b for b, v in get_interface_attr('FINGERPRINTS').items() if v is None}
self.assertGreaterEqual(len(none_brands), 1)
ret = get_interface_attr('FINGERPRINTS', ignore_none=True)
none_brands_in_ret = none_brands.intersection(ret)
self.assertEqual(len(none_brands_in_ret), 0, f'Brands with None values in ignore_none=True result: {none_brands_in_ret}')
if __name__ == "__main__":
unittest.main()