github-actions[bot]
de77c89cf6
version: sunnypilot v2026.002.000 (staging) date: 2026-07-21T07:44:02 master commit: 2c334ede443d7391d27575af8c854a095ba702a8
104 lines
4.2 KiB
Python
104 lines
4.2 KiB
Python
import numpy as np
|
|
|
|
from openpilot.cereal import log, messaging
|
|
from opendbc.car.structs import car
|
|
from opendbc.car.car_helpers import interfaces
|
|
from opendbc.car.gm.values import CAR as GM
|
|
from opendbc.car.honda.values import CAR as HONDA
|
|
from opendbc.car.hyundai.values import CAR as HYUNDAI
|
|
from opendbc.car.toyota.values import CAR as TOYOTA
|
|
from opendbc.car.vehicle_model import VehicleModel
|
|
from openpilot.common.parameterized import parameterized
|
|
from openpilot.common.params import Params
|
|
from openpilot.common.realtime import DT_CTRL
|
|
from openpilot.selfdrive.car.helpers import convert_to_capnp
|
|
from openpilot.selfdrive.controls.lib.latcontrol_torque import LatControlTorque
|
|
from openpilot.selfdrive.locationd.helpers import Pose
|
|
from openpilot.common.mock.generators import generate_livePose
|
|
from openpilot.sunnypilot.selfdrive.car import interfaces as sunnypilot_interfaces
|
|
from openpilot.selfdrive.modeld.constants import ModelConstants
|
|
|
|
|
|
def generate_modelV2():
|
|
model = messaging.new_message('modelV2')
|
|
position = log.XYZTData.new_message()
|
|
speed = 30
|
|
position.x = [float(x) for x in (speed + 0.5) * np.array(ModelConstants.T_IDXS)]
|
|
model.modelV2.position = position
|
|
orientation = log.XYZTData.new_message()
|
|
curvature = 0.05
|
|
orientation.x = [float(curvature) for _ in ModelConstants.T_IDXS]
|
|
orientation.y = [0.0 for _ in ModelConstants.T_IDXS]
|
|
model.modelV2.orientation = orientation
|
|
velocity = log.XYZTData.new_message()
|
|
velocity.x = [float(x) for x in (speed + 0.5) * np.ones_like(ModelConstants.T_IDXS)]
|
|
velocity.x[0] = float(speed) # always start at current speed
|
|
model.modelV2.velocity = velocity
|
|
acceleration = log.XYZTData.new_message()
|
|
acceleration.x = [float(x) for x in np.zeros_like(ModelConstants.T_IDXS)]
|
|
acceleration.y = [float(y) for y in np.zeros_like(ModelConstants.T_IDXS)]
|
|
model.modelV2.acceleration = acceleration
|
|
|
|
return model
|
|
|
|
|
|
class TestNeuralNetworkLateralControl:
|
|
|
|
@parameterized.expand([HONDA.HONDA_CIVIC, TOYOTA.TOYOTA_RAV4, HYUNDAI.HYUNDAI_SANTA_CRUZ_1ST_GEN, GM.CHEVROLET_BOLT_EUV])
|
|
def test_saturation(self, car_name):
|
|
params = Params()
|
|
params.put_bool("NeuralNetworkLateralControl", True, block=True)
|
|
|
|
CarInterface = interfaces[car_name]
|
|
CP = CarInterface.get_non_essential_params(car_name)
|
|
CP_SP = CarInterface.get_non_essential_params_sp(CP, car_name)
|
|
CI = CarInterface(CP, CP_SP)
|
|
|
|
sunnypilot_interfaces.setup_interfaces(CI, params)
|
|
|
|
CP_SP = convert_to_capnp(CP_SP)
|
|
VM = VehicleModel(CP)
|
|
|
|
controller = LatControlTorque(CP.as_reader(), CP_SP.as_reader(), CI, DT_CTRL)
|
|
torque_params = CP.lateralTuning.torque
|
|
|
|
CS = car.CarState.new_message()
|
|
CS.vEgo = 30
|
|
CS.steeringPressed = False
|
|
|
|
params = log.LiveParametersData.new_message()
|
|
|
|
lp = generate_livePose()
|
|
pose = Pose.from_live_pose(lp.livePose)
|
|
|
|
mdl = generate_modelV2()
|
|
sm = {'modelV2': mdl.modelV2}
|
|
model_v2 = sm['modelV2']
|
|
controller.extension.model_v2 = model_v2
|
|
|
|
# Saturate for curvature limited and controller limited
|
|
test_lag = 0.3
|
|
for _ in range(1000):
|
|
controller.extension.update_model_v2(model_v2)
|
|
controller.extension.update_lateral_lag(test_lag)
|
|
controller.update_live_torque_params(torque_params.latAccelFactor, torque_params.latAccelOffset, torque_params.friction)
|
|
controller.extension.update_limits()
|
|
_, _, lac_log = controller.update(True, CS, VM, params, False, 0, pose, True, 0.2)
|
|
assert lac_log.saturated
|
|
|
|
for _ in range(1000):
|
|
controller.extension.update_model_v2(model_v2)
|
|
controller.extension.update_lateral_lag(test_lag)
|
|
controller.update_live_torque_params(torque_params.latAccelFactor, torque_params.latAccelOffset, torque_params.friction)
|
|
controller.extension.update_limits()
|
|
_, _, lac_log = controller.update(True, CS, VM, params, False, 0, pose, False, 0.2)
|
|
assert not lac_log.saturated
|
|
|
|
for _ in range(1000):
|
|
controller.extension.update_model_v2(model_v2)
|
|
controller.extension.update_lateral_lag(test_lag)
|
|
controller.update_live_torque_params(torque_params.latAccelFactor, torque_params.latAccelOffset, torque_params.friction)
|
|
controller.extension.update_limits()
|
|
_, _, lac_log = controller.update(True, CS, VM, params, False, 1, pose, False, 0.2)
|
|
assert lac_log.saturated
|