Calculate average desired curvature using planned distance
Added toggle to calculate average desired curvature using planned distance instead of the car's speed. Credit goes to Pfeiferj! https: //github.com/pfeiferj Co-Authored-By: Jacob Pfeifer <jacob@pfeifer.dev>
This commit is contained in:
@@ -22,6 +22,7 @@ struct FrogPilotLateralPlan @0xda96579883444c35 {
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}
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struct FrogPilotLongitudinalPlan @0x80ae746ee2596b11 {
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distances @3 :List(Float32);
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}
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struct FrogPilotNavigation @0xa5cd762cd951a455 {
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@@ -217,6 +217,7 @@ std::unordered_map<std::string, uint32_t> keys = {
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{"AlwaysOnLateral", PERSISTENT},
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{"AlwaysOnLateralMain", PERSISTENT},
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{"ApiCache_DriveStats", PERSISTENT},
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{"AverageCurvature", PERSISTENT},
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{"FrogPilotTogglesUpdated", PERSISTENT},
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{"GasRegenCmd", PERSISTENT},
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{"LateralTune", PERSISTENT},
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@@ -649,7 +649,9 @@ class Controls:
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self.desired_curvature, self.desired_curvature_rate = get_lag_adjusted_curvature(self.CP, CS.vEgo,
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lat_plan.psis,
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lat_plan.curvatures,
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lat_plan.curvatureRates)
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lat_plan.curvatureRates,
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frogpilot_long_plan.distances,
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self.average_desired_curvature)
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actuators.steer, actuators.steeringAngleDeg, lac_log = self.LaC.update(CC.latActive, CS, self.VM, lp,
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self.steer_limited, self.desired_curvature,
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self.desired_curvature_rate, self.sm['liveLocationKalman'])
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@@ -940,6 +942,8 @@ class Controls:
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if hasattr(obj, 'update_frogpilot_params'):
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obj.update_frogpilot_params(self.params)
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self.average_desired_curvature = self.params.get_bool("AverageCurvature")
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longitudinal_tune = self.params.get_bool("LongitudinalTune")
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self.sport_plus = self.params.get_int("AccelerationProfile") == 3 and longitudinal_tune
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@@ -16,6 +16,7 @@ V_CRUISE_INITIAL = 40
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V_CRUISE_INITIAL_EXPERIMENTAL_MODE = 105
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IMPERIAL_INCREMENT = 1.6 # should be CV.MPH_TO_KPH, but this causes rounding errors
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MIN_DIST = 0.001
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MIN_SPEED = 1.0
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CONTROL_N = 17
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CAR_ROTATION_RADIUS = 0.0
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@@ -163,11 +164,12 @@ def rate_limit(new_value, last_value, dw_step, up_step):
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return clip(new_value, last_value + dw_step, last_value + up_step)
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def get_lag_adjusted_curvature(CP, v_ego, psis, curvatures, curvature_rates):
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if len(psis) != CONTROL_N:
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def get_lag_adjusted_curvature(CP, v_ego, psis, curvatures, curvature_rates, distances, average_desired_curvature):
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if len(psis) != CONTROL_N or len(distances) != CONTROL_N:
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psis = [0.0]*CONTROL_N
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curvatures = [0.0]*CONTROL_N
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curvature_rates = [0.0]*CONTROL_N
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distances = [0.0]*CONTROL_N
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v_ego = max(MIN_SPEED, v_ego)
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# TODO this needs more thought, use .2s extra for now to estimate other delays
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@@ -178,7 +180,10 @@ def get_lag_adjusted_curvature(CP, v_ego, psis, curvatures, curvature_rates):
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# psi to calculate a simple linearization of desired curvature
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current_curvature_desired = curvatures[0]
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psi = interp(delay, ModelConstants.T_IDXS[:CONTROL_N], psis)
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average_curvature_desired = psi / (v_ego * delay)
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# Pfeiferj's #28118 PR - https://github.com/commaai/openpilot/pull/28118
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distance = interp(delay, ModelConstants.T_IDXS[:CONTROL_N], distances)
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distance = max(MIN_DIST, distance)
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average_curvature_desired = psi / distance if average_desired_curvature else psi / (v_ego * delay)
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desired_curvature = 2 * average_curvature_desired - current_curvature_desired
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# This is the "desired rate of the setpoint" not an actual desired rate
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@@ -35,6 +35,9 @@ class LateralPlanner:
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if len(md.position.x) == TRAJECTORY_SIZE and len(md.velocity.x) == TRAJECTORY_SIZE and len(md.lateralPlannerSolution.x) == TRAJECTORY_SIZE:
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self.path_xyz = np.column_stack([md.position.x, md.position.y, md.position.z])
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self.velocity_xyz = np.column_stack([md.velocity.x, md.velocity.y, md.velocity.z])
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if frogpilot_planner.average_desired_curvature:
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car_speed = np.array(md.velocity.x) - get_speed_error(md, v_ego_car)
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else:
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car_speed = np.linalg.norm(self.velocity_xyz, axis=1) - get_speed_error(md, v_ego_car)
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self.v_plan = np.clip(car_speed, MIN_SPEED, np.inf)
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self.v_ego = self.v_plan[0]
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@@ -230,6 +230,7 @@ class LongitudinalMpc:
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# self.solver = AcadosOcpSolverCython(MODEL_NAME, ACADOS_SOLVER_TYPE, N)
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self.solver.reset()
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# self.solver.options_set('print_level', 2)
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self.x_solution = np.zeros(N+1)
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self.v_solution = np.zeros(N+1)
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self.a_solution = np.zeros(N+1)
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self.prev_a = np.array(self.a_solution)
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@@ -442,6 +443,7 @@ class LongitudinalMpc:
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for i in range(N):
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self.u_sol[i] = self.solver.get(i, 'u')
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self.x_solution = self.x_sol[:,0]
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self.v_solution = self.x_sol[:,1]
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self.a_solution = self.x_sol[:,2]
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self.j_solution = self.u_sol[:,0]
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@@ -1,9 +1,12 @@
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import cereal.messaging as messaging
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import numpy as np
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from openpilot.common.conversions import Conversions as CV
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from openpilot.common.numpy_fast import interp
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from openpilot.selfdrive.controls.lib.drive_helpers import V_CRUISE_MAX
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from openpilot.selfdrive.controls.lib.drive_helpers import CONTROL_N, V_CRUISE_MAX
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from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import T_IDXS as T_IDXS_MPC
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from openpilot.selfdrive.controls.lib.longitudinal_planner import A_CRUISE_MIN, A_CRUISE_MAX_VALS, A_CRUISE_MAX_BP, get_max_accel
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from openpilot.selfdrive.modeld.constants import ModelConstants
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# Acceleration profiles - Credit goes to the DragonPilot team!
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# MPH = [0., 35, 35, 40, 40, 45, 45, 67, 67, 67, 123]
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@@ -34,6 +37,8 @@ class FrogPilotPlanner:
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def __init__(self, params):
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self.v_cruise = 0
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self.x_desired_trajectory = np.zeros(CONTROL_N)
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self.update_frogpilot_params(params)
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def update(self, sm, mpc):
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@@ -55,6 +60,9 @@ class FrogPilotPlanner:
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self.v_cruise = self.update_v_cruise(carState, controlsState, modelData, enabled, v_cruise, v_ego)
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self.x_desired_trajectory_full = np.interp(ModelConstants.T_IDXS, T_IDXS_MPC, mpc.x_solution)
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self.x_desired_trajectory = self.x_desired_trajectory_full[:CONTROL_N]
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def update_v_cruise(self, carState, controlsState, modelData, enabled, v_cruise, v_ego):
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v_ego_diff = max(carState.vEgoRaw - carState.vEgoCluster, 0)
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return v_cruise - v_ego_diff
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@@ -71,12 +79,15 @@ class FrogPilotPlanner:
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frogpilot_longitudinal_plan_send.valid = sm.all_checks(service_list=['carState', 'controlsState'])
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frogpilotLongitudinalPlan = frogpilot_longitudinal_plan_send.frogpilotLongitudinalPlan
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frogpilotLongitudinalPlan.distances = self.x_desired_trajectory.tolist()
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pm.send('frogpilotLongitudinalPlan', frogpilot_longitudinal_plan_send)
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def update_frogpilot_params(self, params):
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self.is_metric = params.get_bool("IsMetric")
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lateral_tune = params.get_bool("LateralTune")
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self.average_desired_curvature = params.get_bool("AverageCurvature") and lateral_tune
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longitudinal_tune = params.get_bool("LongitudinalTune")
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self.acceleration_profile = params.get_int("AccelerationProfile") if longitudinal_tune else 0
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@@ -6,6 +6,7 @@ FrogPilotControlsPanel::FrogPilotControlsPanel(SettingsWindow *parent) : FrogPil
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{"AlwaysOnLateral", "Always on Lateral", "Maintain openpilot lateral control when the brake or gas pedals are used.\n\nDeactivation occurs only through the 'Cruise Control' button.", "../frogpilot/assets/toggle_icons/icon_always_on_lateral.png"},
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{"LateralTune", "Lateral Tuning", "Modify openpilot's steering behavior.", "../frogpilot/assets/toggle_icons/icon_lateral_tune.png"},
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{"AverageCurvature", "Average Desired Curvature", "Use Pfeiferj's distance-based curvature adjustment for improved curve handling.", ""},
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{"LongitudinalTune", "Longitudinal Tuning", "Modify openpilot's acceleration and braking behavior.", "../frogpilot/assets/toggle_icons/icon_longitudinal_tune.png"},
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{"AccelerationProfile", "Acceleration Profile", "Change the acceleration rate to be either sporty or eco-friendly.", ""},
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@@ -97,7 +98,7 @@ FrogPilotControlsPanel::FrogPilotControlsPanel(SettingsWindow *parent) : FrogPil
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conditionalExperimentalKeys = {};
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fireTheBabysitterKeys = {};
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laneChangeKeys = {};
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lateralTuneKeys = {};
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lateralTuneKeys = {"AverageCurvature"};
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longitudinalTuneKeys = {"AccelerationProfile", "AggressiveAcceleration"};
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speedLimitControllerKeys = {};
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visionTurnControlKeys = {};
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