openpilot v0.6.3 release

old-commit-hash: d5f9caa82d

selfdrive/controls/lib/pathplanner.py

@@ -2,12 +2,13 @@ import os
 import math
 import numpy as np
 
+# from common.numpy_fast import clip
 from common.realtime import sec_since_boot
 from selfdrive.services import service_list
 from selfdrive.swaglog import cloudlog
 from selfdrive.controls.lib.lateral_mpc import libmpc_py
 from selfdrive.controls.lib.drive_helpers import MPC_COST_LAT
-from selfdrive.controls.lib.model_parser import ModelParser
+from selfdrive.controls.lib.lane_planner import LanePlanner
 import selfdrive.messaging as messaging
 
 LOG_MPC = os.environ.get('LOG_MPC', False)
@@ -21,10 +22,7 @@ def calc_states_after_delay(states, v_ego, steer_angle, curvature_factor, steer_
 
 class PathPlanner(object):
   def __init__(self, CP):
-    self.MP = ModelParser()
-
-    self.l_poly = [0., 0., 0., 0.]
-    self.r_poly = [0., 0., 0., 0.]
+    self.LP = LanePlanner()
 
     self.last_cloudlog_t = 0
 
@@ -33,6 +31,7 @@ class PathPlanner(object):
 
     self.setup_mpc(CP.steerRateCost)
     self.solution_invalid_cnt = 0
+    self.path_offset_i = 0.0
 
   def setup_mpc(self, steer_rate_cost):
     self.libmpc = libmpc_py.libmpc
@@ -50,10 +49,6 @@ class PathPlanner(object):
     self.angle_steers_des_prev = 0.0
     self.angle_steers_des_time = 0.0
 
-    self.l_poly = libmpc_py.ffi.new("double[4]")
-    self.r_poly = libmpc_py.ffi.new("double[4]")
-    self.p_poly = libmpc_py.ffi.new("double[4]")
-
   def update(self, sm, CP, VM):
     v_ego = sm['carState'].vEgo
     angle_steers = sm['carState'].steeringAngle
@@ -62,23 +57,28 @@ class PathPlanner(object):
     angle_offset_average = sm['liveParameters'].angleOffsetAverage
     angle_offset_bias = sm['controlsState'].angleModelBias + angle_offset_average
 
-    self.MP.update(v_ego, sm['model'])
+    self.LP.update(v_ego, sm['model'])
 
     # Run MPC
     self.angle_steers_des_prev = self.angle_steers_des_mpc
     VM.update_params(sm['liveParameters'].stiffnessFactor, sm['liveParameters'].steerRatio)
     curvature_factor = VM.curvature_factor(v_ego)
-    self.l_poly = list(self.MP.l_poly)
-    self.r_poly = list(self.MP.r_poly)
-    self.p_poly = list(self.MP.p_poly)
+
+    # TODO: Check for active, override, and saturation
+    # if active:
+    #   self.path_offset_i += self.LP.d_poly[3] / (60.0 * 20.0)
+    #   self.path_offset_i = clip(self.path_offset_i, -0.5,  0.5)
+    #   self.LP.d_poly[3] += self.path_offset_i
+    # else:
+    #   self.path_offset_i = 0.0
 
     # account for actuation delay
     self.cur_state = calc_states_after_delay(self.cur_state, v_ego, angle_steers - angle_offset_average, curvature_factor, VM.sR, CP.steerActuatorDelay)
 
     v_ego_mpc = max(v_ego, 5.0)  # avoid mpc roughness due to low speed
     self.libmpc.run_mpc(self.cur_state, self.mpc_solution,
-                        self.l_poly, self.r_poly, self.p_poly,
-                        self.MP.l_prob, self.MP.r_prob, self.MP.p_prob, curvature_factor, v_ego_mpc, self.MP.lane_width)
+                        list(self.LP.l_poly), list(self.LP.r_poly), list(self.LP.d_poly),
+                        self.LP.l_prob, self.LP.r_prob, curvature_factor, v_ego_mpc, self.LP.lane_width)
 
     # reset to current steer angle if not active or overriding
     if active:
@@ -112,17 +112,16 @@ class PathPlanner(object):
     plan_send = messaging.new_message()
     plan_send.init('pathPlan')
     plan_send.valid = sm.all_alive_and_valid(service_list=['carState', 'controlsState', 'liveParameters', 'model'])
-    plan_send.pathPlan.laneWidth = float(self.MP.lane_width)
-    plan_send.pathPlan.dPoly = [float(x) for x in self.MP.d_poly]
-    plan_send.pathPlan.cPoly = [float(x) for x in self.MP.c_poly]
-    plan_send.pathPlan.cProb = float(self.MP.c_prob)
-    plan_send.pathPlan.lPoly = [float(x) for x in self.l_poly]
-    plan_send.pathPlan.lProb = float(self.MP.l_prob)
-    plan_send.pathPlan.rPoly = [float(x) for x in self.r_poly]
-    plan_send.pathPlan.rProb = float(self.MP.r_prob)
+    plan_send.pathPlan.laneWidth = float(self.LP.lane_width)
+    plan_send.pathPlan.dPoly = [float(x) for x in self.LP.d_poly]
+    plan_send.pathPlan.lPoly = [float(x) for x in self.LP.l_poly]
+    plan_send.pathPlan.lProb = float(self.LP.l_prob)
+    plan_send.pathPlan.rPoly = [float(x) for x in self.LP.r_poly]
+    plan_send.pathPlan.rProb = float(self.LP.r_prob)
+
     plan_send.pathPlan.angleSteers = float(self.angle_steers_des_mpc)
     plan_send.pathPlan.rateSteers = float(rate_desired)
-    plan_send.pathPlan.angleOffset = float(angle_offset_average)
+    plan_send.pathPlan.angleOffset = float(self.path_offset_i)
     plan_send.pathPlan.mpcSolutionValid = bool(plan_solution_valid)
     plan_send.pathPlan.paramsValid = bool(sm['liveParameters'].valid)
     plan_send.pathPlan.sensorValid = bool(sm['liveParameters'].sensorValid)