diff --git a/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py b/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py index 9f6383f31..5c8a98bda 100644 --- a/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py +++ b/selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py @@ -19,12 +19,13 @@ SOURCES = ['lead0', 'lead1', 'cruise'] X_DIM = 3 U_DIM = 1 -COST_E_DIM = 3 +COST_E_DIM = 4 COST_DIM = COST_E_DIM + 1 CONSTR_DIM = 4 -X_EGO_COST = 3. -X_EGO_E2E_COST = 10. +X_EGO_OBSTACLE_COST = 3. +V_EGO_COST = 0. +X_EGO_COST = 0. A_EGO_COST = 0. J_EGO_COST = 10. DANGER_ZONE_COST = 100. @@ -124,6 +125,7 @@ def gen_long_mpc_solver(): # instead. costs = [((x_obstacle - x_ego) - (desired_dist_comfort)) / (v_ego + 10.), x_ego, + v_ego, a_ego, j_ego] ocp.model.cost_y_expr = vertcat(*costs) @@ -213,7 +215,7 @@ class LongitudinalMpc(): self.set_weights_for_lead_policy() def set_weights_for_lead_policy(self): - W = np.diag([X_EGO_COST, 0.0, A_EGO_COST, J_EGO_COST]) + W = np.diag([X_EGO_OBSTACLE_COST, X_EGO_COST, V_EGO_COST, A_EGO_COST, J_EGO_COST]) Ws = np.tile(W[None], reps=(N,1,1)) self.solver.cost_set_slice(0, N, 'W', Ws, api='old') # Setting the slice without the copy make the array not contiguous, @@ -226,7 +228,7 @@ class LongitudinalMpc(): self.solver.cost_set_slice(0, N+1, 'Zl', Zls, api='old') def set_weights_for_xva_policy(self): - W = np.diag([0.0, X_EGO_E2E_COST, 0., J_EGO_COST]) + W = np.diag([0., 10., 1., 10., 1.]) Ws = np.tile(W[None], reps=(N,1,1)) self.solver.cost_set_slice(0, N, 'W', Ws, api='old') # Setting the slice without the copy make the array not contiguous, @@ -321,6 +323,8 @@ class LongitudinalMpc(): def update_with_xva(self, x, v, a): self.yref[:,1] = x + self.yref[:,2] = v + self.yref[:,3] = a self.solver.cost_set_slice(0, N, "yref", self.yref[:N], api='old') self.solver.set(N, "yref", self.yref[N][:COST_E_DIM]) self.accel_limit_arr[:,0] = -10.