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.
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

70 lines
2.3 KiB

#!/usr/bin/env python3
import math
import unittest
import numpy as np
from control import StateSpace
from openpilot.selfdrive.car.honda.interface import CarInterface
from openpilot.selfdrive.car.honda.values import CAR
from openpilot.selfdrive.controls.lib.vehicle_model import VehicleModel, dyn_ss_sol, create_dyn_state_matrices
class TestVehicleModel(unittest.TestCase):
def setUp(self):
CP = CarInterface.get_non_essential_params(CAR.HONDA_CIVIC)
self.VM = VehicleModel(CP)
def test_round_trip_yaw_rate(self):
# TODO: fix VM to work at zero speed
for u in np.linspace(1, 30, num=10):
for roll in np.linspace(math.radians(-20), math.radians(20), num=11):
for sa in np.linspace(math.radians(-20), math.radians(20), num=11):
yr = self.VM.yaw_rate(sa, u, roll)
new_sa = self.VM.get_steer_from_yaw_rate(yr, u, roll)
self.assertAlmostEqual(sa, new_sa)
def test_dyn_ss_sol_against_yaw_rate(self):
"""Verify that the yaw_rate helper function matches the results
from the state space model."""
for roll in np.linspace(math.radians(-20), math.radians(20), num=11):
for u in np.linspace(1, 30, num=10):
for sa in np.linspace(math.radians(-20), math.radians(20), num=11):
# Compute yaw rate based on state space model
_, yr1 = dyn_ss_sol(sa, u, roll, self.VM)
# Compute yaw rate using direct computations
yr2 = self.VM.yaw_rate(sa, u, roll)
self.assertAlmostEqual(float(yr1[0]), yr2)
def test_syn_ss_sol_simulate(self):
"""Verifies that dyn_ss_sol matches a simulation"""
for roll in np.linspace(math.radians(-20), math.radians(20), num=11):
for u in np.linspace(1, 30, num=10):
A, B = create_dyn_state_matrices(u, self.VM)
# Convert to discrete time system
ss = StateSpace(A, B, np.eye(2), np.zeros((2, 2)))
ss = ss.sample(0.01)
for sa in np.linspace(math.radians(-20), math.radians(20), num=11):
inp = np.array([[sa], [roll]])
# Simulate for 1 second
x1 = np.zeros((2, 1))
for _ in range(100):
x1 = ss.A @ x1 + ss.B @ inp
# Compute steady state solution directly
x2 = dyn_ss_sol(sa, u, roll, self.VM)
np.testing.assert_almost_equal(x1, x2, decimal=3)
if __name__ == "__main__":
unittest.main()