import unittest import numpy as np from selfdrive.car.honda.interface import CarInterface from selfdrive.controls.lib.lateral_mpc import libmpc_py from selfdrive.controls.lib.vehicle_model import VehicleModel from selfdrive.controls.lib.lane_planner import calc_d_poly def run_mpc(v_ref=30., x_init=0., y_init=0., psi_init=0., delta_init=0., l_prob=1., r_prob=1., p_prob=1., poly_l=np.array([0., 0., 0., 1.8]), poly_r=np.array([0., 0., 0., -1.8]), poly_p=np.array([0., 0., 0., 0.]), lane_width=3.6, poly_shift=0.): libmpc = libmpc_py.libmpc libmpc.init(1.0, 3.0, 1.0, 1.0) mpc_solution = libmpc_py.ffi.new("log_t *") p_l = poly_l.copy() p_l[3] += poly_shift p_r = poly_r.copy() p_r[3] += poly_shift p_p = poly_p.copy() p_p[3] += poly_shift d_poly = calc_d_poly(p_l, p_r, p_p, l_prob, r_prob, lane_width) CP = CarInterface.get_params("HONDA CIVIC 2016 TOURING") VM = VehicleModel(CP) v_ref = v_ref curvature_factor = VM.curvature_factor(v_ref) l_poly = libmpc_py.ffi.new("double[4]", list(map(float, p_l))) r_poly = libmpc_py.ffi.new("double[4]", list(map(float, p_r))) d_poly = libmpc_py.ffi.new("double[4]", list(map(float, d_poly))) cur_state = libmpc_py.ffi.new("state_t *") cur_state[0].x = x_init cur_state[0].y = y_init cur_state[0].psi = psi_init cur_state[0].delta = delta_init # converge in no more than 20 iterations for _ in range(20): libmpc.run_mpc(cur_state, mpc_solution, l_poly, r_poly, d_poly, l_prob, r_prob, curvature_factor, v_ref, lane_width) return mpc_solution class TestLateralMpc(unittest.TestCase): def _assert_null(self, sol, delta=1e-6): for i in range(len(sol[0].y)): self.assertAlmostEqual(sol[0].y[i], 0., delta=delta) self.assertAlmostEqual(sol[0].psi[i], 0., delta=delta) self.assertAlmostEqual(sol[0].delta[i], 0., delta=delta) def _assert_simmetry(self, sol, delta=1e-6): for i in range(len(sol[0][0].y)): self.assertAlmostEqual(sol[0][0].y[i], -sol[1][0].y[i], delta=delta) self.assertAlmostEqual(sol[0][0].psi[i], -sol[1][0].psi[i], delta=delta) self.assertAlmostEqual(sol[0][0].delta[i], -sol[1][0].delta[i], delta=delta) self.assertAlmostEqual(sol[0][0].x[i], sol[1][0].x[i], delta=delta) def _assert_identity(self, sol, ignore_y=False, delta=1e-6): for i in range(len(sol[0][0].y)): self.assertAlmostEqual(sol[0][0].psi[i], sol[1][0].psi[i], delta=delta) self.assertAlmostEqual(sol[0][0].delta[i], sol[1][0].delta[i], delta=delta) self.assertAlmostEqual(sol[0][0].x[i], sol[1][0].x[i], delta=delta) if not ignore_y: self.assertAlmostEqual(sol[0][0].y[i], sol[1][0].y[i], delta=delta) def test_straight(self): sol = run_mpc() self._assert_null(sol) def test_y_symmetry(self): sol = [] for y_init in [-0.5, 0.5]: sol.append(run_mpc(y_init=y_init)) self._assert_simmetry(sol) def test_poly_symmetry(self): sol = [] for poly_shift in [-1., 1.]: sol.append(run_mpc(poly_shift=poly_shift)) self._assert_simmetry(sol) def test_delta_symmetry(self): sol = [] for delta_init in [-0.1, 0.1]: sol.append(run_mpc(delta_init=delta_init)) self._assert_simmetry(sol) def test_psi_symmetry(self): sol = [] for psi_init in [-0.1, 0.1]: sol.append(run_mpc(psi_init=psi_init)) self._assert_simmetry(sol) def test_prob_symmetry(self): sol = [] lane_width = 3. for r_prob in [0., 1.]: sol.append(run_mpc(r_prob=r_prob, l_prob=1.-r_prob, lane_width=lane_width)) self._assert_simmetry(sol) def test_y_shift_vs_poly_shift(self): shift = 1. sol = [] sol.append(run_mpc(y_init=shift)) sol.append(run_mpc(poly_shift=-shift)) # need larger delta than standard, otherwise it false triggers. # this is acceptable because the 2 cases are very different from the optimizer standpoint self._assert_identity(sol, ignore_y=True, delta=1e-5) def test_no_overshoot(self): y_init = 1. sol = run_mpc(y_init=y_init) for y in list(sol[0].y): self.assertGreaterEqual(y_init, abs(y)) if __name__ == "__main__": unittest.main()