A2mosayyebi401822045-golabadi400634087

src/__main__.py

@@ -4,27 +4,43 @@
 
 from src.simulator_handler import SimulatorHandler
 from utils.vehicle_command import VehicleCommand
+from path_following_handler import PathFollowingHandler
+import warnings
+
+warnings.filterwarnings("ignore")
 
 if __name__ == "__main__":
-    simulator_handler = SimulatorHandler(town_name="Town04")
-    simulator_handler.spawn_vehicle(spawn_index=13)
-    simulator_handler.set_weather(weather=carla.WeatherParameters.ClearNoon)
+    simulator_handler = SimulatorHandler(town_name="Town10HD_Opt")
 
-    # potential weather choices are [ClearNoon, ClearSunset, CloudyNoon, CloudySunset,
-    # WetNoon, WetSunset, MidRainyNoon, MidRainSunset, HardRainNoon, HardRainSunset,
-    # SoftRainNoon, SoftRainSunset]
+    simulator_handler.set_weather(weather=carla.WeatherParameters.ClearNoon)
 
-    # add sensors
+    # potential weather choices we have [ ClearSunset,CloudySunset,CloudyNoon,ClearNoon]
+    # WetNoon, WetSunset,HardRainNoon,HardRainSunset,MidRainyNoon,SoftRainNoon, SoftRainSunset]
+    path_following_handler = PathFollowingHandler(client=simulator_handler.client)
+    ego_spawn_point = path_following_handler.ego_spawn_point
+    ego_vehicle = simulator_handler.spawn_ego_vehicles(road_id=ego_spawn_point["road_id"],
+                                                       filtered_points_index=ego_spawn_point["filtered_points_index"])
+    # sensors we have:
     rgb_cam = simulator_handler.rgb_cam()
     gnss_sensor = simulator_handler.gnss()
     imu_sensor = simulator_handler.imu()
 
-    # listen to sensor data
+    # listen to sensor data:
     rgb_cam.listen(lambda image: simulator_handler.rgb_cam_callback(image))
     imu_sensor.listen(lambda imu: simulator_handler.imu_callback(imu))
     gnss_sensor.listen(lambda gnss: simulator_handler.gnss_callback(gnss))
-    VehicleCommand(throttle=1.0).send_control(simulator_handler.vehicle)
-    time.sleep(20.0)
-
-
-
+    # VehicleCommand(throttle=1.0).send_control(simulator_handler.vehicle)
+
+    if path_following_handler.debug_mode:
+        path_following_handler.start()
+    else:
+        # ego_vehicle = path_following_handler.spawn_ego_vehicles(road_id=ego_spawn_point["road_id"],
+        # filtered_points_index=ego_spawn_point["filtered_points_index"])
+        ego_pid_controller = path_following_handler.pid_controller(ego_vehicle,
+                                                                   path_following_handler.pid_values_lateral,
+                                                                   path_following_handler.pid_values_longitudinal)
+        path_following_handler.vehicle_and_controller_inputs(ego_vehicle, ego_pid_controller)
+        path_following_handler.start()
+
+    # time.sleep(20.0)
+    # simulator_handler.clearing()

src/path_following_handler.py

@@ -9,6 +9,7 @@
 
 from src.utils.carla_utils import draw_waypoints, filter_waypoints, TrajectoryToFollow, InfiniteLoopThread
 from src.utils.controller import VehiclePIDController
+# from src.simulator_handler import SimulatorHandler
 
 
 class PathFollowingHandler(InfiniteLoopThread, ABC):
@@ -26,6 +27,7 @@ def __init__(self, client: carla.Client, debug_mode: bool = False,
             {'road_id': road_id_list, 'filtered_points_index': filtered_point_index_list}
 
         self.world: World = self.client.get_world()
+        self.spectator = self.world.get_spectator()
         if os.path.basename(self.world.get_map().name) != carla_map:
             self.world: World = client.load_world(carla_map)
         self.waypoints: list = self.client.get_world().get_map().generate_waypoints(distance=1.0)
@@ -34,15 +36,15 @@ def __init__(self, client: carla.Client, debug_mode: bool = False,
             self.waypoints_to_visualize = {'road_id': [4], 'filtered_points_index': [0]}
         self.pid_values_lateral: Union[Dict[str, float], Dict[str, float], Dict[str, float]] = \
             {'K_P': 1,
-             'K_D': 0.07,
-             'K_I': 0.05}  # control steering
+             'K_D': 0.09,
+             'K_I': 0.04}  #steering control
         self.pid_values_longitudinal: Union[Dict[str, float], Dict[str, float], Dict[str, float]] = \
-            {'K_P': 1,
-             'K_D': 0.07,
-             'K_I': 0.05}  # control speed
+            {'K_P': 1.5,
+             'K_D': 0.09,
+             'K_I': 0.08}  #speed control
         self.vehicle_to_target_distance_threshold: float = 2.5
 
-        self.desired_speed: int = 20  # meter per second
+        self.desired_speed: int = 20  #meter per second
         self.reached_destination: bool = False
         self.previous_waypoint: Union[carla.Waypoint, None] = None
 
@@ -93,6 +95,7 @@ def pid_controller(vehicle, args_lateral: dict, args_longitudinal: dict) -> Vehi
         return ego_pid_controller_
 
     def follow_trajectory(self, vehicle: Any, ego_pid_controller_: VehiclePIDController) -> None:
+
         for trajectory_point_index in range(len(self.trajectory_to_follow['road_id'])):
             current_road_id, current_filtered_point_index = \
                 self.trajectory_to_follow['road_id'][trajectory_point_index], \
@@ -117,6 +120,20 @@ def follow_trajectory(self, vehicle: Any, ego_pid_controller_: VehiclePIDControl
             self.__follow_target_waypoints__(vehicle, target_waypoint, ego_pid_controller_)
             self.previous_waypoint = target_waypoint
 
+    def infinite_trajectory_tracking(self, vehicle, ego_pid_controller_):
+        curr_waypoint_index = {'road_id': 13, 'filtered_points_index': 0} #get first way point
+        curr_waypoint = filter_waypoints(self.waypoints,
+                                         road_id=curr_waypoint_index['road_id'])[curr_waypoint_index['filtered_points_index']]
+        print(curr_waypoint)
+        while True:
+            way_points = curr_waypoint.next_until_lane_end(2)
+            draw_waypoints(self.world, self.waypoints, road_id=curr_waypoint.road_id , life_time=30)
+            for target_waypoint in way_points:
+                self.__follow_target_waypoints__(vehicle, target_waypoint, ego_pid_controller_)
+            curr_waypoint = target_waypoint.next(3.5)[0]
+
+
+
     def vehicle_and_controller_inputs(self, ego_vehicle_, ego_pid_controller_):
         self.ego_vehicle = ego_vehicle_
         self.ego_pid_controller = ego_pid_controller_
@@ -128,9 +145,10 @@ def __step__(self):
             sys.exit(1)
 
         if not self.reached_destination:
-            self.follow_trajectory(self.ego_vehicle, self.ego_pid_controller)
-            self.reached_destination = True
-            print("Destination has been reached.")
+            # self.follow_trajectory(self.ego_vehicle, self.ego_pid_controller)
+            self.infinite_trajectory_tracking(self.ego_vehicle, self.ego_pid_controller)
+            # self.reached_destination = True
+            # print("Destination has been reached.")
         else:
             sys.exit(1)
 

src/simulator_handler.py

@@ -5,9 +5,12 @@
 import numpy as np
 import pandas as pd
 from matplotlib import pyplot as plt
+from src.path_following_handler import PathFollowingHandler
+from src.utils.carla_utils import draw_waypoints, filter_waypoints, TrajectoryToFollow, InfiniteLoopThread
+from typing import Any, Union, Dict, List
 
 
-class SimulatorHandler:
+class SimulatorHandler():
     def __init__(self, town_name):
         self.spawn_point = None
         self.vehicle = None
@@ -23,29 +26,42 @@ def __init__(self, town_name):
 
         try:
             print("Trying to communicate with the client...")
-            client = carla.Client("localhost", 2000)
-            client.set_timeout(8.0)
-            self.world = client.get_world()
+            self.client = carla.Client("localhost", 2000)
+            self.client.set_timeout(8.0)
+            self.world = self.client.get_world()
             if os.path.basename(self.world.get_map().name) != town_name:
-                self.world: carla.World = client.load_world(town_name)
+                self.world: carla.World = self.client.load_world(town_name)
 
             self.blueprint_library = self.world.get_blueprint_library()
             self.actor_list = []
             self.vehicle_list = []
-            self.IM_WIDTH = 800  # Ideally a config file should be defined for such parameters
-            self.IM_HEIGHT = 600
+            self.IM_WIDTH = 1280  # Ideally a config file should be defined for such parameters
+            self.IM_HEIGHT = 720
             print("Successfully connected to CARLA client")
         except Exception as error:
             raise Exception(f"Error while initializing the simulator: {error}")
 
         self.imu_dataframe = pd.DataFrame({})
         self.gnss_dataframe = pd.DataFrame({})
-
-    def spawn_vehicle(self, spawn_index: int = 90):
-        self.vehicle_blueprint = self.blueprint_library.filter("model3")[0]  # choosing the car
-        self.spawn_point = self.world.get_map().get_spawn_points()[spawn_index]
-        self.vehicle = self.world.spawn_actor(self.vehicle_blueprint, self.spawn_point)
+        self.waypoints: list = self.client.get_world().get_map().generate_waypoints(distance=1.0)
+
+    # def spawn_vehicle(self, spawn_index: int = 90):
+    #    self.vehicle_blueprint = self.blueprint_library.filter("model3")[0]  # selecting the car
+    #    self.spawn_point = self.world.get_map().get_spawn_points()[spawn_index]
+    #    self.vehicle = self.world.spawn_actor(self.vehicle_blueprint, self.spawn_point)
+    #    self.actor_list.append(self.vehicle)
+
+    def spawn_ego_vehicles(self, road_id: int, filtered_points_index: int) -> Any:
+        print("spawning ego vehicle at road_id={} filtered_points_index={}".format(road_id,
+                                                                                   filtered_points_index))
+        vehicle_blueprint = \
+            self.client.get_world().get_blueprint_library().filter("model3")[0]
+        filtered_waypoints = filter_waypoints(self.waypoints, road_id=road_id)
+        spawn_point = filtered_waypoints[filtered_points_index].transform
+        spawn_point.location.z += 2
+        self.vehicle = self.client.get_world().spawn_actor(vehicle_blueprint, spawn_point)
         self.actor_list.append(self.vehicle)
+        return self.vehicle
 
     def set_weather(self, weather=carla.WeatherParameters.ClearNoon):
         self.world.set_weather(weather)
@@ -90,11 +106,6 @@ def rgb_cam_callback(self, image):
 
         rgba_image = raw_image.reshape((self.IM_HEIGHT, self.IM_WIDTH, 4))  # because carla rgb cam is rgba
         rgb_image = rgba_image[:, :, :3]
-        rgb_image = cv2.cvtColor(rgb_image, cv2.COLOR_BGR2RGB)
-        plt.imshow(rgb_image)
-        plt.show()
-        # cv2.imshow("rgb camera", rgb_image)  # FixMe: Replace with pygame visualization
-        # cv2.waitKey(1)
 
     def imu_callback(self, imu):  # accelerometer is m/s^2 and gyroscope data is rad/sec
         imu_dict = {}
@@ -108,7 +119,7 @@ def imu_callback(self, imu):  # accelerometer is m/s^2 and gyroscope data is rad
         # create a pandas dataframe
         self.imu_dataframe = self.imu_dataframe.append(imu_dict, ignore_index=True)
         # save the dataframe to a csv file
-        self.imu_dataframe.to_csv(os.path.join(self.save_dir, "imu.csv"), index=False)
+        self.imu_dataframe.to_csv(os.path.join(self.save_dir, "imu.csv"), index=False, mode='a')
 
     def gnss_callback(self, gnss):
         gnss_dict = {}
@@ -117,4 +128,10 @@ def gnss_callback(self, gnss):
         gnss_dict["longitude"] = gnss.longitude
         gnss_dict["altitude"] = gnss.altitude
         self.gnss_dataframe = self.gnss_dataframe.append(gnss_dict, ignore_index=True)
-        self.gnss_dataframe.to_csv(os.path.join(self.save_dir, "gnss.csv"), index=False)
+        self.gnss_dataframe.to_csv(os.path.join(self.save_dir, "gnss.csv"), index=False, mode='a')
+
+    def clearing(self):
+        for actor in self.world.get_actors().filter('*vehicle*'):
+            actor.destroy()
+        for actor in self.world.get_actors().filter('*sensor*'):
+            actor.destroy()