From f50f0bcec0cecfd7fa548a70356be0e43a1ef9a8 Mon Sep 17 00:00:00 2001 From: Qi Date: Sun, 17 Sep 2023 23:04:49 -0400 Subject: [PATCH 01/11] fixed random high level command selection --- .../brains/CARLA/utils/high_level_command.py | 47 +++++++++++++++++++ 1 file changed, 47 insertions(+) create mode 100644 behavior_metrics/brains/CARLA/utils/high_level_command.py diff --git a/behavior_metrics/brains/CARLA/utils/high_level_command.py b/behavior_metrics/brains/CARLA/utils/high_level_command.py new file mode 100644 index 00000000..abfc3a8f --- /dev/null +++ b/behavior_metrics/brains/CARLA/utils/high_level_command.py @@ -0,0 +1,47 @@ +import numpy as np +import carla + +class HighLevelCommandLoader: + def __init__(self, vehicle, map): + self.vehicle = vehicle + self.map = map + self.prev_hlc = 0 + + def get_random_hlc(self): + junction = None + vehicle_location = self.vehicle.get_transform().location + vehicle_waypoint = self.map.get_waypoint(vehicle_location) + + # check whether vehicle is at junction + for j in range(1, 11): + next_waypoint = vehicle_waypoint.next(j * 1.0)[0] + if next_waypoint.is_junction: + junction = next_waypoint.get_junction() + break + if vehicle_waypoint.is_junction: + junction = vehicle_waypoint.get_junction() + + # randomly select a turning direction + if junction is not None: + if self.prev_hlc == 0: + valid_turns = [] + waypoints = junction.get_waypoints(carla.LaneType.Driving) + for next_wp, _ in waypoints: + yaw_diff = next_wp.transform.rotation.yaw - vehicle_waypoint.transform.rotation.yaw + yaw_diff = (yaw_diff + 180) % 360 - 180 # convert to [-180, 180] + if -15 < yaw_diff < 15: + valid_turns.append(3) # Go Straight + elif 15 < yaw_diff < 165: + valid_turns.append(1) # Turn Left + elif -165 < yaw_diff < -15: + valid_turns.append(2) # Turn Right + hlc = np.random.choice(valid_turns) + else: + hlc = self.prev_hlc + else: + hlc = 0 + + self.prev_hlc = hlc + + return hlc + From c6443396900022b23632de933884d2d3edba796a Mon Sep 17 00:00:00 2001 From: Qi Date: Sun, 17 Sep 2023 23:06:12 -0400 Subject: [PATCH 02/11] select closest timestamp instead of precise matching --- behavior_metrics/utils/metrics_carla.py | 15 +++++++++------ 1 file changed, 9 insertions(+), 6 deletions(-) diff --git a/behavior_metrics/utils/metrics_carla.py b/behavior_metrics/utils/metrics_carla.py index 549f02bc..6272f4d0 100644 --- a/behavior_metrics/utils/metrics_carla.py +++ b/behavior_metrics/utils/metrics_carla.py @@ -225,16 +225,17 @@ def get_collisions(experiment_metrics, collision_points, df_checkpoints): collisions_checkpoints_different = [] previous_collisions_checkpoints_x, previous_collisions_checkpoints_y = 0, 0 for point in collision_points: - collision_point = df_checkpoints.loc[df_checkpoints['Time'] == point['Time']] + idx = (df_checkpoints['Time'] - point['Time']).abs().idxmin() + collision_point = df_checkpoints.iloc[idx] collisions_checkpoints.append(collision_point) - point_1 = np.array([collision_point.iloc[0]['pose.pose.position.x'], collision_point.iloc[0]['pose.pose.position.y']]) + point_1 = np.array([collision_point['pose.pose.position.x'], collision_point['pose.pose.position.y']]) point_2 = np.array([previous_collisions_checkpoints_x, previous_collisions_checkpoints_y]) dist = (point_2 - point_1) ** 2 dist = np.sum(dist, axis=0) dist = np.sqrt(dist) if dist > 1: collisions_checkpoints_different.append(collision_point) - previous_collisions_checkpoints_x, previous_collisions_checkpoints_y = collision_point.iloc[0]['pose.pose.position.x'], collision_point.iloc[0]['pose.pose.position.y'] + previous_collisions_checkpoints_x, previous_collisions_checkpoints_y = collision_point['pose.pose.position.x'], collision_point['pose.pose.position.y'] experiment_metrics['collisions'] = len(collisions_checkpoints_different) return experiment_metrics, collisions_checkpoints @@ -245,9 +246,11 @@ def get_lane_invasions(experiment_metrics, lane_invasion_points, df_checkpoints) previous_lane_invasion_checkpoints_x, previous_lane_invasion_checkpoints_y = 0, 0 previous_time = 0 for point in lane_invasion_points: - lane_invasion_point = df_checkpoints.loc[df_checkpoints['Time'] == point['Time']] + idx = (df_checkpoints['Time'] - point['Time']).abs().idxmin() + lane_invasion_point = df_checkpoints.iloc[idx] + lane_invasion_checkpoints.append(lane_invasion_point) - point_1 = np.array([lane_invasion_point.iloc[0]['pose.pose.position.x'], lane_invasion_point.iloc[0]['pose.pose.position.y']]) + point_1 = np.array([lane_invasion_point['pose.pose.position.x'], lane_invasion_point['pose.pose.position.y']]) point_2 = np.array([previous_lane_invasion_checkpoints_x, previous_lane_invasion_checkpoints_y]) dist = (point_2 - point_1) ** 2 dist = np.sum(dist, axis=0) @@ -255,7 +258,7 @@ def get_lane_invasions(experiment_metrics, lane_invasion_points, df_checkpoints) if dist > 1 and point['Time'] - previous_time > 0.5: lane_invasion_checkpoints_different.append(lane_invasion_point) previous_time = point['Time'] - previous_lane_invasion_checkpoints_x, previous_lane_invasion_checkpoints_y = lane_invasion_point.iloc[0]['pose.pose.position.x'], lane_invasion_point.iloc[0]['pose.pose.position.y'] + previous_lane_invasion_checkpoints_x, previous_lane_invasion_checkpoints_y = lane_invasion_point['pose.pose.position.x'], lane_invasion_point['pose.pose.position.y'] experiment_metrics['lane_invasions'] = len(lane_invasion_checkpoints_different) return experiment_metrics, lane_invasion_checkpoints From c98cd7c656fb8c21a2f964a083441f30674672f7 Mon Sep 17 00:00:00 2001 From: Qi Date: Mon, 18 Sep 2023 06:04:08 -0400 Subject: [PATCH 03/11] added test suite --- ...a_segmentation_based_imitation_learning.py | 38 ++------ ...02_anticlockwise_imitation_learning.launch | 4 +- ...ockwise_imitation_learning_template.launch | 56 ++++++++++++ behavior_metrics/configs/__init__.py | 0 .../configs/default_carla_test_suite.yml | 72 +++++++++++++++ .../configs/test_suites/Town02_two_turns.py | 91 +++++++++++++++++++ 6 files changed, 230 insertions(+), 31 deletions(-) create mode 100644 behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_imitation_learning_template.launch create mode 100644 behavior_metrics/configs/__init__.py create mode 100644 behavior_metrics/configs/default_carla_test_suite.yml create mode 100644 behavior_metrics/configs/test_suites/Town02_two_turns.py diff --git a/behavior_metrics/brains/CARLA/brain_carla_segmentation_based_imitation_learning.py b/behavior_metrics/brains/CARLA/brain_carla_segmentation_based_imitation_learning.py index 72fd7917..e264446a 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_segmentation_based_imitation_learning.py +++ b/behavior_metrics/brains/CARLA/brain_carla_segmentation_based_imitation_learning.py @@ -3,6 +3,7 @@ from brains.CARLA.utils.pilotnet_onehot import PilotNetOneHot from brains.CARLA.utils.test_utils import traffic_light_to_int, model_control from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH +from brains.CARLA.utils.high_level_command import HighLevelCommandLoader from os import path import numpy as np @@ -29,7 +30,7 @@ def __init__(self, sensors, actuators, model=None, handler=None, config=None): self.device = torch.device('cuda' if (torch.cuda.is_available() and self.gpu_inference) else 'cpu') client = carla.Client('localhost', 2000) - client.set_timeout(10.0) + client.set_timeout(100.0) world = client.get_world() self.map = world.get_map() @@ -57,7 +58,7 @@ def __init__(self, sensors, actuators, model=None, handler=None, config=None): self.net.load_state_dict(torch.load(PRETRAINED_MODELS + model,map_location=self.device)) self.net.eval() - self.prev_hlc = 0 + self.hlc_loader = HighLevelCommandLoader(self.vehicle, self.map) def update_frame(self, frame_id, data): @@ -91,38 +92,14 @@ def execute(self): self.update_frame('frame_0', rgb_image) self.update_frame('frame_1', seg_image) + start_time = time.time() try: # calculate speed speed_m_s = self.vehicle.get_velocity() speed = 3.6 * math.sqrt(speed_m_s.x**2 + speed_m_s.y**2 + speed_m_s.z**2) # randomly choose high-level command if at junction - vehicle_location = self.vehicle.get_transform().location - vehicle_waypoint = self.map.get_waypoint(vehicle_location) - next_to_junction = False - for j in range(1, 11): - next_waypoint = vehicle_waypoint.next(j * 1.0)[0] - if next_waypoint.is_junction: - next_to_junction = True - next_waypoints = vehicle_waypoint.next(j * 1.0) - break - if vehicle_waypoint.is_junction or next_to_junction: - if self.prev_hlc == 0: - valid_turns = [] - for next_wp in next_waypoints: - yaw_diff = next_wp.transform.rotation.yaw - vehicle_waypoint.transform.rotation.yaw - yaw_diff = (yaw_diff + 180) % 360 - 180 - if -15 < yaw_diff < 15: - valid_turns.append(3) # Go Straight - elif 15 < yaw_diff < 165: - valid_turns.append(1) # Turn Left - elif -165 < yaw_diff < -15: - valid_turns.append(2) # Turn Right - hlc = np.random.choice(valid_turns) - else: - hlc = self.prev_hlc - else: - hlc = 0 + hlc = self.hlc_loader.get_random_hlc() # get traffic light status light_status = -1 @@ -131,7 +108,7 @@ def execute(self): light_status = traffic_light.get_state() print(f'hlc: {hlc}') - print(f'light: {light_status}') + #print(f'light: {light_status}') frame_data = { 'hlc': hlc, 'measurements': speed, @@ -145,6 +122,9 @@ def execute(self): ignore_traffic_light=False, device=self.device, combined_control=False) + + self.inference_times.append(time.time() - start_time) + self.motors.sendThrottle(throttle) self.motors.sendSteer(steer) self.motors.sendBrake(brake) diff --git a/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_imitation_learning.launch b/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_imitation_learning.launch index bbdac71d..59f42fe2 100644 --- a/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_imitation_learning.launch +++ b/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_imitation_learning.launch @@ -38,12 +38,12 @@ - + - + diff --git a/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_imitation_learning_template.launch b/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_imitation_learning_template.launch new file mode 100644 index 00000000..8e1996cb --- /dev/null +++ b/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_imitation_learning_template.launch @@ -0,0 +1,56 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/behavior_metrics/configs/__init__.py b/behavior_metrics/configs/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/behavior_metrics/configs/default_carla_test_suite.yml b/behavior_metrics/configs/default_carla_test_suite.yml new file mode 100644 index 00000000..7b06d9dd --- /dev/null +++ b/behavior_metrics/configs/default_carla_test_suite.yml @@ -0,0 +1,72 @@ +Behaviors: + Robot: + Sensors: + Cameras: + Camera_0: + Name: 'camera_0' + Topic: '/carla/ego_vehicle/rgb_front/image' + Camera_1: + Name: 'camera_1' + Topic: '/carla/ego_vehicle/rgb_view/image' + Camera_2: + Name: 'camera_2' + Topic: '/carla/ego_vehicle/semantic_segmentation_front/image' + Camera_3: + Name: 'camera_3' + Topic: '/carla/ego_vehicle/dvs_front/image' + Pose3D: + Pose3D_0: + Name: 'pose3d_0' + Topic: '/carla/ego_vehicle/odometry' + BirdEyeView: + BirdEyeView_0: + Name: 'bird_eye_view_0' + Topic: '' + Speedometer: + Speedometer_0: + Name: 'speedometer_0' + Topic: '/carla/ego_vehicle/speedometer' + Actuators: + CARLA_Motors: + Motors_0: + Name: 'motors_0' + Topic: '/carla/ego_vehicle/vehicle_control_cmd' + MaxV: 3 + MaxW: 0.3 + BrainPath: 'brains/CARLA/brain_carla_segmentation_based_imitation_learning.py' + PilotTimeCycle: 50 + AsyncMode: False + Parameters: + Model: 'pilotnet_v8.0.pth' + ImageCropped: False + ImageSize: [ 100,50 ] + ImageNormalized: True + PredictionsNormalized: True + GPU: True + UseOptimized: False + ImageTranform: '' + Type: 'CARLA' + Simulation: + Task: "follow_route" + WorldTemplate: configs/CARLA_launch_files/town_02_anticlockwise_imitation_learning_template.launch + TestSuite: configs/test_suites/Town02_two_turns.py + RandomSpawnPoint: False + NumberOfVehicle: 50 + NumberOfWalker: 0 + PercentagePedestriansRunning: 0.5 + PercentagePedestriansCrossing: 0.5 + Dataset: + In: '/tmp/my_bag.bag' + Out: '' + Stats: + Out: './' + PerfectLap: './perfect_bags/lap-simple-circuit.bag' + Layout: + Frame_0: + Name: frame_0 + Geometry: [0, 1, 1, 2] + Data: rgbimage + Frame_1: + Name: frame_1 + Geometry: [1, 1, 1, 2] + Data: rgbimage \ No newline at end of file diff --git a/behavior_metrics/configs/test_suites/Town02_two_turns.py b/behavior_metrics/configs/test_suites/Town02_two_turns.py new file mode 100644 index 00000000..715e7cf6 --- /dev/null +++ b/behavior_metrics/configs/test_suites/Town02_two_turns.py @@ -0,0 +1,91 @@ +TEST_ROUTES = [ + { + "map": "Town02", + "start": "-3.68, -288.22, 0.5, 0.0, 0.0, -90.0", + "end": "41.39, -212.98, 0.5, 0.0, 0.0, 90.0", + "distance": 158, + "commands": ["Right", "Right"] + }, + { + "map": "Town02", + "start": "45.24, -225.59, 0.5, 0.0, 0.0, -90", + "end": "-7.53, -270.73, 0.5, 0.0, 0.0, 90.0", + "distance": 166, + "commands": ["Left", "Left"] + }, + { + "map": "Town02", + "start":"136.11, -302.57, 0.5, 0.0, 0.0, -180.0", + "end":"45.89, -216.26, 0.5, 0.0, 0.0, -90.0", + "distance": 174, + "commands": ["Right", "Straight"] + }, + { + "map": "Town02", + "start": "41.39, -203.90, 0.5, 0.0, 0.0, 90.0", + "end": "136.11, -306.42, 0.5, 0.0, 0.0, 0.0", + "distance": 193, + "commands": ["Straight", "Left"] + }, + { + "map": "Town02", + "start": "59.71, -241.28, 0.5, 0.0, 0.0, 0.0", + "end": "166.91, -191.77, 0.5, 0.0, 0.0, 0.0", + "distance": 148, + "commands": ["Left", "Right"] + }, + { + "map": "Town02", + "start": "165.09, -187.12, 0.5, 0.0, 0.0, -180.0", + "end": "71.04, -237.43, 0.5, 0.0, 0.0, -180.0", + "distance": 136, + "commands": ["Left", "Right"] + }, + { + "map": "Town02", + "start": "59.60, -306.42, 0.5, 0.0, 0.0, 0.0", + "end": "165.09, -187.12, 0.5, 0.0, 0.0, -180.0", + "distance": 272, + "commands": ["Straight", "Left"] + }, + { + "map": "Town02", + "start": "166.91, -191.77, 0.5, 0.0, 0.0, 0.0", + "end": "71.53, -302.57, 0.5, 0.0, 0.0, -180.0", + "distance": 245, + "commands": ["Right", "Straight"] + }, + { + "map": "Town02", + "start": "92.34, -187.92, 0.5, 0.0, 0.0, -180.0", + "end": "84.41, -109.30, 0.5, 0.0, 0.0, 0.0", + "distance": 255, + "commands": ["Straight", "Right"] + }, + { + "map": "Town02", + "start": "84.41, -105.55, 0.5, 0.0, 0.0, -180.0", + "end": "92.34, -191.77, 0.5, 0.0, 0.0, 0.0", + "distance": 269, + "commands": ["Left", "Straight"] + }, + { + "map": "Town02", + "start": "135.88, -226.05, 0.5, 0.0, 0.0, -90.0", + "end": "193.78, -121.21, 0.5, 0.0, 0.0, -90.0", + "distance": 155, + "commands": ["Right", "Left"] + }, + { + "map": "Town02", + "start": "189.93, -121.21, 0.5, 0.0, 0.0, 90.0", + "end": "132.03, -211.0, 0.5, 0.0, 0.0, 90.0", + "distance": 140, + "commands": ["Right", "Left"] + } +] + +if __name__ == "__main__": + # Quick test to see if the routes are loaded correctly + for route in TEST_ROUTES: + print(route) \ No newline at end of file From 2427b400a21bad3120f3db83eebe4582708c85cd Mon Sep 17 00:00:00 2001 From: Qi Date: Mon, 18 Sep 2023 06:57:15 -0400 Subject: [PATCH 04/11] updated test suite --- ...tion_learning_template.launch => test_suite_template.launch} | 0 behavior_metrics/configs/default_carla_test_suite.yml | 2 +- 2 files changed, 1 insertion(+), 1 deletion(-) rename behavior_metrics/configs/CARLA_launch_files/{town_02_anticlockwise_imitation_learning_template.launch => test_suite_template.launch} (100%) diff --git a/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_imitation_learning_template.launch b/behavior_metrics/configs/CARLA_launch_files/test_suite_template.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_imitation_learning_template.launch rename to behavior_metrics/configs/CARLA_launch_files/test_suite_template.launch diff --git a/behavior_metrics/configs/default_carla_test_suite.yml b/behavior_metrics/configs/default_carla_test_suite.yml index 7b06d9dd..dd7b355e 100644 --- a/behavior_metrics/configs/default_carla_test_suite.yml +++ b/behavior_metrics/configs/default_carla_test_suite.yml @@ -48,7 +48,7 @@ Behaviors: Type: 'CARLA' Simulation: Task: "follow_route" - WorldTemplate: configs/CARLA_launch_files/town_02_anticlockwise_imitation_learning_template.launch + World: configs/CARLA_launch_files/test_suite_template.launch TestSuite: configs/test_suites/Town02_two_turns.py RandomSpawnPoint: False NumberOfVehicle: 50 From bfea716b3ec4bafcd6d0b5d30002ca8c668f7e21 Mon Sep 17 00:00:00 2001 From: Qi Date: Mon, 25 Sep 2023 04:11:38 -0400 Subject: [PATCH 05/11] restructured configs --- behavior_metrics/.gitignore | 1 + .../test_suite_template.launch | 0 ...02_anticlockwise_imitation_learning.launch | 0 .../{ => CARLA}/default_carla_test_suite.yml | 13 +- .../test_suites/Town02_two_turns.py | 34 ++-- .../main_car_custom_camera.json | 163 ----------------- behavior_metrics/configs/__init__.py | 0 behavior_metrics/driver_carla.py | 137 ++++++++++----- behavior_metrics/test_suite_manager_carla.py | 165 ++++++++++++++++++ behavior_metrics/utils/configuration.py | 27 ++- behavior_metrics/utils/environment.py | 16 +- 11 files changed, 325 insertions(+), 231 deletions(-) rename behavior_metrics/configs/{ => CARLA}/CARLA_launch_files/test_suite_template.launch (100%) rename behavior_metrics/configs/{ => CARLA}/CARLA_launch_files/town_02_anticlockwise_imitation_learning.launch (100%) rename behavior_metrics/configs/{ => CARLA}/default_carla_test_suite.yml (82%) rename behavior_metrics/configs/{ => CARLA}/test_suites/Town02_two_turns.py (64%) delete mode 100644 behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/main_car_custom_camera.json delete mode 100644 behavior_metrics/configs/__init__.py create mode 100644 behavior_metrics/test_suite_manager_carla.py diff --git a/behavior_metrics/.gitignore b/behavior_metrics/.gitignore index d6c9882c..af96b108 100644 --- a/behavior_metrics/.gitignore +++ b/behavior_metrics/.gitignore @@ -9,6 +9,7 @@ bag_analysis/ core tmp_* +carla_birdeye_view/ ### Python ### diff --git a/behavior_metrics/configs/CARLA_launch_files/test_suite_template.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/test_suite_template.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/test_suite_template.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/test_suite_template.launch diff --git a/behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_imitation_learning.launch b/behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_imitation_learning.launch similarity index 100% rename from behavior_metrics/configs/CARLA_launch_files/town_02_anticlockwise_imitation_learning.launch rename to behavior_metrics/configs/CARLA/CARLA_launch_files/town_02_anticlockwise_imitation_learning.launch diff --git a/behavior_metrics/configs/default_carla_test_suite.yml b/behavior_metrics/configs/CARLA/default_carla_test_suite.yml similarity index 82% rename from behavior_metrics/configs/default_carla_test_suite.yml rename to behavior_metrics/configs/CARLA/default_carla_test_suite.yml index dd7b355e..c0ee08f4 100644 --- a/behavior_metrics/configs/default_carla_test_suite.yml +++ b/behavior_metrics/configs/CARLA/default_carla_test_suite.yml @@ -33,11 +33,11 @@ Behaviors: Topic: '/carla/ego_vehicle/vehicle_control_cmd' MaxV: 3 MaxW: 0.3 - BrainPath: 'brains/CARLA/brain_carla_segmentation_based_imitation_learning.py' + BrainPath: ['brains/CARLA/brain_carla_segmentation_based_imitation_learning.py'] PilotTimeCycle: 50 AsyncMode: False Parameters: - Model: 'pilotnet_v8.0.pth' + Model: ['pilotnet_v8.0.pth'] ImageCropped: False ImageSize: [ 100,50 ] ImageNormalized: True @@ -46,10 +46,17 @@ Behaviors: UseOptimized: False ImageTranform: '' Type: 'CARLA' + Experiment: + Name: "Carla Town02 Test Suite" + Description: "Testing model in Town02 with each route consisting of two turns." + UseWorldTimeouts: False + Timeout: [10] # for each world! Simulation: Task: "follow_route" - World: configs/CARLA_launch_files/test_suite_template.launch + World: [configs/CARLA_launch_files/test_suite_template.launch] TestSuite: configs/test_suites/Town02_two_turns.py + RandomizeRoutes: False + NumRoutes: 12 RandomSpawnPoint: False NumberOfVehicle: 50 NumberOfWalker: 0 diff --git a/behavior_metrics/configs/test_suites/Town02_two_turns.py b/behavior_metrics/configs/CARLA/test_suites/Town02_two_turns.py similarity index 64% rename from behavior_metrics/configs/test_suites/Town02_two_turns.py rename to behavior_metrics/configs/CARLA/test_suites/Town02_two_turns.py index 715e7cf6..99c3ee93 100644 --- a/behavior_metrics/configs/test_suites/Town02_two_turns.py +++ b/behavior_metrics/configs/CARLA/test_suites/Town02_two_turns.py @@ -1,28 +1,28 @@ TEST_ROUTES = [ { "map": "Town02", - "start": "-3.68, -288.22, 0.5, 0.0, 0.0, -90.0", - "end": "41.39, -212.98, 0.5, 0.0, 0.0, 90.0", + "start": "-3.68, -288.22, 0.5, 0.0, 0.0, 90.0", + "end": "41.39, -212.98, 0.5, 0.0, 0.0, -90.0", "distance": 158, "commands": ["Right", "Right"] }, { "map": "Town02", - "start": "45.24, -225.59, 0.5, 0.0, 0.0, -90", - "end": "-7.53, -270.73, 0.5, 0.0, 0.0, 90.0", + "start": "45.24, -225.59, 0.5, 0.0, 0.0, 90", + "end": "-7.53, -270.73, 0.5, 0.0, 0.0, -90.0", "distance": 166, "commands": ["Left", "Left"] }, { "map": "Town02", - "start":"136.11, -302.57, 0.5, 0.0, 0.0, -180.0", - "end":"45.89, -216.26, 0.5, 0.0, 0.0, -90.0", + "start":"136.11, -302.57, 0.5, 0.0, 0.0, 180.0", + "end":"45.89, -216.26, 0.5, 0.0, 0.0, 90.0", "distance": 174, "commands": ["Right", "Straight"] }, { "map": "Town02", - "start": "41.39, -203.90, 0.5, 0.0, 0.0, 90.0", + "start": "41.39, -203.90, 0.5, 0.0, 0.0, -90.0", "end": "136.11, -306.42, 0.5, 0.0, 0.0, 0.0", "distance": 193, "commands": ["Straight", "Left"] @@ -36,50 +36,50 @@ }, { "map": "Town02", - "start": "165.09, -187.12, 0.5, 0.0, 0.0, -180.0", - "end": "71.04, -237.43, 0.5, 0.0, 0.0, -180.0", + "start": "165.09, -187.12, 0.5, 0.0, 0.0, 180.0", + "end": "71.04, -237.43, 0.5, 0.0, 0.0, 180.0", "distance": 136, "commands": ["Left", "Right"] }, { "map": "Town02", "start": "59.60, -306.42, 0.5, 0.0, 0.0, 0.0", - "end": "165.09, -187.12, 0.5, 0.0, 0.0, -180.0", + "end": "165.09, -187.12, 0.5, 0.0, 0.0, 180.0", "distance": 272, "commands": ["Straight", "Left"] }, { "map": "Town02", "start": "166.91, -191.77, 0.5, 0.0, 0.0, 0.0", - "end": "71.53, -302.57, 0.5, 0.0, 0.0, -180.0", + "end": "71.53, -302.57, 0.5, 0.0, 0.0, 180.0", "distance": 245, "commands": ["Right", "Straight"] }, { "map": "Town02", - "start": "92.34, -187.92, 0.5, 0.0, 0.0, -180.0", + "start": "92.34, -187.92, 0.5, 0.0, 0.0, 180.0", "end": "84.41, -109.30, 0.5, 0.0, 0.0, 0.0", "distance": 255, "commands": ["Straight", "Right"] }, { "map": "Town02", - "start": "84.41, -105.55, 0.5, 0.0, 0.0, -180.0", + "start": "84.41, -105.55, 0.5, 0.0, 0.0, 180.0", "end": "92.34, -191.77, 0.5, 0.0, 0.0, 0.0", "distance": 269, "commands": ["Left", "Straight"] }, { "map": "Town02", - "start": "135.88, -226.05, 0.5, 0.0, 0.0, -90.0", - "end": "193.78, -121.21, 0.5, 0.0, 0.0, -90.0", + "start": "135.88, -226.05, 0.5, 0.0, 0.0, 90.0", + "end": "193.78, -121.21, 0.5, 0.0, 0.0, 90.0", "distance": 155, "commands": ["Right", "Left"] }, { "map": "Town02", - "start": "189.93, -121.21, 0.5, 0.0, 0.0, 90.0", - "end": "132.03, -211.0, 0.5, 0.0, 0.0, 90.0", + "start": "189.93, -121.21, 0.5, 0.0, 0.0, -90.0", + "end": "132.03, -211.0, 0.5, 0.0, 0.0, -90.0", "distance": 140, "commands": ["Right", "Left"] } diff --git a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/main_car_custom_camera.json b/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/main_car_custom_camera.json deleted file mode 100644 index 5054f0fd..00000000 --- a/behavior_metrics/configs/CARLA_launch_files/CARLA_object_files/main_car_custom_camera.json +++ /dev/null @@ -1,163 +0,0 @@ -{ - "objects": - [ - { - "type": "sensor.pseudo.traffic_lights", - "id": "traffic_lights" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.actor_list", - "id": "actor_list" - }, - { - "type": "sensor.pseudo.markers", - "id": "markers" - }, - { - "type": "sensor.pseudo.opendrive_map", - "id": "map" - }, - { - "type": "vehicle.tesla.model3", - "id": "ego_vehicle", - "sensors": - [ - { - "type": "sensor.camera.rgb", - "id": "rgb_front", - "spawn_point": {"x": 1.5, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 15.0, "yaw": 0.0}, - "image_size_x": 288, - "image_size_y": 200, - "fov": 90.0 - }, - { - "type": "sensor.camera.rgb", - "id": "rgb_view", - "spawn_point": {"x": -4.5, "y": 0.0, "z": 2.8, "roll": 0.0, "pitch": 20.0, "yaw": 0.0}, - "image_size_x": 800, - "image_size_y": 600, - "fov": 90.0, - "attached_objects": - [ - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - }, - { - "type": "sensor.lidar.ray_cast", - "id": "lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20, - "noise_stddev": 0.0 - }, - { - "type": "sensor.lidar.ray_cast_semantic", - "id": "semantic_lidar", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "range": 50, - "channels": 32, - "points_per_second": 320000, - "upper_fov": 2.0, - "lower_fov": -26.8, - "rotation_frequency": 20 - }, - { - "type": "sensor.other.radar", - "id": "radar_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "horizontal_fov": 30.0, - "vertical_fov": 10.0, - "points_per_second": 1500, - "range": 100.0 - }, - { - "type": "sensor.camera.semantic_segmentation", - "id": "semantic_segmentation_front", - "spawn_point": {"x": 1.5, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 15.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 288, - "image_size_y": 200 - }, - { - "type": "sensor.camera.depth", - "id": "depth_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70 - }, - { - "type": "sensor.camera.dvs", - "id": "dvs_front", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "fov": 90.0, - "image_size_x": 400, - "image_size_y": 70, - "positive_threshold": 0.3, - "negative_threshold": 0.3, - "sigma_positive_threshold": 0.0, - "sigma_negative_threshold": 0.0, - "use_log": true, - "log_eps": 0.001 - }, - { - "type": "sensor.other.gnss", - "id": "gnss", - "spawn_point": {"x": 1.0, "y": 0.0, "z": 2.0}, - "noise_alt_stddev": 0.0, "noise_lat_stddev": 0.0, "noise_lon_stddev": 0.0, - "noise_alt_bias": 0.0, "noise_lat_bias": 0.0, "noise_lon_bias": 0.0 - }, - { - "type": "sensor.other.imu", - "id": "imu", - "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, - "noise_accel_stddev_x": 0.0, "noise_accel_stddev_y": 0.0, "noise_accel_stddev_z": 0.0, - "noise_gyro_stddev_x": 0.0, "noise_gyro_stddev_y": 0.0, "noise_gyro_stddev_z": 0.0, - "noise_gyro_bias_x": 0.0, "noise_gyro_bias_y": 0.0, "noise_gyro_bias_z": 0.0 - }, - { - "type": "sensor.other.collision", - "id": "collision", - "spawn_point": {"x": 2.5, "y": 0.0, "z": 0.7} - }, - { - "type": "sensor.other.lane_invasion", - "id": "lane_invasion", - "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} - }, - { - "type": "sensor.pseudo.tf", - "id": "tf" - }, - { - "type": "sensor.pseudo.objects", - "id": "objects" - }, - { - "type": "sensor.pseudo.odom", - "id": "odometry" - }, - { - "type": "sensor.pseudo.speedometer", - "id": "speedometer" - }, - { - "type": "actor.pseudo.control", - "id": "control" - } - ] - } - ] -} - diff --git a/behavior_metrics/configs/__init__.py b/behavior_metrics/configs/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/behavior_metrics/driver_carla.py b/behavior_metrics/driver_carla.py index 088cd59e..c3c1687a 100644 --- a/behavior_metrics/driver_carla.py +++ b/behavior_metrics/driver_carla.py @@ -280,6 +280,9 @@ def main(): config_data = check_args(sys.argv) app_configuration = Config(config_data['config'][0]) if not config_data['script']: + if app_configuration.task != 'random_roam': + logger.info('Selected task does not support --gui. Try use --script instead. Killing program...') + sys.exit(-1) environment.launch_env(app_configuration.current_world, random_spawn_point=app_configuration.experiment_random_spawn_point, carla_simulator=True) controller = ControllerCarla() traffic_manager = TrafficManager(app_configuration.number_of_vehicle, @@ -305,53 +308,97 @@ def main(): environment.close_ros_and_simulators() else: if is_config_correct(app_configuration): - experiments_starting_time = time.time() - experiment_counter = 0 - experiments_elapsed_times = {'experiment_counter': [], 'elapsed_time': []} - experiments_information = {'world_counter': {}} - for world_counter, world in enumerate(app_configuration.current_world): - experiments_information['world_counter'][world_counter] = {'brain_counter': {}} - for brain_counter, brain in enumerate(app_configuration.brain_path): - experiments_information['world_counter'][world_counter]['brain_counter'][brain_counter] = {'repetition_counter': {}} - for repetition_counter in range(app_configuration.experiment_repetitions): - success = -1 - experiment_attempts = 0 - while success != 0: - experiments_information['world_counter'][world_counter]['brain_counter'][brain_counter]['repetition_counter'][repetition_counter] = experiment_attempts - logger.info("Launching: python3 script_manager_carla.py -c " + config_data['config'][0] + " -s -world_counter " + str(world_counter) + " -brain_counter " + str(brain_counter) + " -repetition_counter " + str(repetition_counter)) - logger.info("Experiment attempt: " + str(experiment_attempts+1)) - current_experiment_starting_time = time.time() - success = os.system("python3 script_manager_carla.py -c " + config_data['config'][0] + " -s -world_counter " + str(world_counter) + " -brain_counter " + str(brain_counter) + " -repetition_counter " + str(repetition_counter)) - if success != 0: - root = './' - folders = list(os.walk(root))[1:] - for folder in folders: - if len(folder[0].split('/')) == 2 and not folder[1] and not folder[2]: - logger.info("Removing empty folder: " + folder[0]) - os.rmdir(folder[0]) - if success == 2: - logger.info('KeyboardInterrupt called! Killing program...') - sys.exit(-1) - elif success != 0 and experiment_attempts < 5: - experiment_attempts += 1 - logger.info("Python process finished with error! Repeating experiment") - elif success != 0 and experiment_attempts >= 5: - success = 0 - logger.info("Too many failed attempts for this experiment.") - else: - experiments_elapsed_times['experiment_counter'].append(experiment_counter) - experiments_elapsed_times['elapsed_time'].append(time.time() - current_experiment_starting_time) - experiment_counter += 1 - logger.info("Python process finished.") - - logger.info('Experiments information: ') - logger.info(experiments_information) - logger.info('Last experiment folder: ') - logger.info(max(glob.glob(os.path.join('./', '*/')), key=os.path.getmtime)) - + if app_configuration.task == 'random_roam': + experiments_starting_time = time.time() + experiment_counter = 0 + experiments_elapsed_times = {'experiment_counter': [], 'elapsed_time': []} + experiments_information = {'world_counter': {}} + for world_counter, world in enumerate(app_configuration.current_world): + experiments_information['world_counter'][world_counter] = {'brain_counter': {}} + for brain_counter, brain in enumerate(app_configuration.brain_path): + experiments_information['world_counter'][world_counter]['brain_counter'][brain_counter] = {'repetition_counter': {}} + for repetition_counter in range(app_configuration.experiment_repetitions): + success = -1 + experiment_attempts = 0 + while success != 0: + experiments_information['world_counter'][world_counter]['brain_counter'][brain_counter]['repetition_counter'][repetition_counter] = experiment_attempts + logger.info("Launching: python3 script_manager_carla.py -c " + config_data['config'][0] + " -s -world_counter " + str(world_counter) + " -brain_counter " + str(brain_counter) + " -repetition_counter " + str(repetition_counter)) + logger.info("Experiment attempt: " + str(experiment_attempts+1)) + current_experiment_starting_time = time.time() + success = os.system("python3 script_manager_carla.py -c " + config_data['config'][0] + " -s -world_counter " + str(world_counter) + " -brain_counter " + str(brain_counter) + " -repetition_counter " + str(repetition_counter)) + if success != 0: + root = './' + folders = list(os.walk(root))[1:] + for folder in folders: + if len(folder[0].split('/')) == 2 and not folder[1] and not folder[2]: + logger.info("Removing empty folder: " + folder[0]) + os.rmdir(folder[0]) + if success == 2: + logger.info('KeyboardInterrupt called! Killing program...') + sys.exit(-1) + elif success != 0 and experiment_attempts < 5: + experiment_attempts += 1 + logger.info("Python process finished with error! Repeating experiment") + elif success != 0 and experiment_attempts >= 5: + success = 0 + logger.info("Too many failed attempts for this experiment.") + else: + experiments_elapsed_times['experiment_counter'].append(experiment_counter) + experiments_elapsed_times['elapsed_time'].append(time.time() - current_experiment_starting_time) + experiment_counter += 1 + logger.info("Python process finished.") + + logger.info('Experiments information: ') + logger.info(experiments_information) + logger.info('Last experiment folder: ') + logger.info(max(glob.glob(os.path.join('./', '*/')), key=os.path.getmtime)) + elif app_configuration.task == 'follow_route': + + experiments_starting_time = time.time() + experiment_counter = 0 + experiments_elapsed_times = {'experiment_counter': [], 'elapsed_time': []} + + for world_counter, world in enumerate(app_configuration.current_world): + for brain_counter, brain in enumerate(app_configuration.brain_path): + for route_counter in range(app_configuration.num_routes): + success = -1 + experiment_attempts = 0 + while success != 0: + logger.info("Launching: python3 test_suite_manager_carla.py -c " + config_data['config'][0]) + logger.info("Experiment attempt: " + str(experiment_attempts+1)) + current_experiment_starting_time = time.time() + success = os.system("python3 test_suite_manager_carla.py -c " + config_data['config'][0] + " -s -world_counter " + str(world_counter) + " -brain_counter " + str(brain_counter) + " -route_counter " + str(route_counter)) + + if success != 0: + root = './' + folders = list(os.walk(root))[1:] + for folder in folders: + if len(folder[0].split('/')) == 2 and not folder[1] and not folder[2]: + logger.info("Removing empty folder: " + folder[0]) + os.rmdir(folder[0]) + if success == 2: + logger.info('KeyboardInterrupt called! Killing program...') + sys.exit(-1) + elif success != 0 and experiment_attempts < 5: + experiment_attempts += 1 + logger.info("Python process finished with error! Repeating experiment") + elif success != 0 and experiment_attempts >= 5: + success = 0 + logger.info("Too many failed attempts for this experiment.") + else: + experiments_elapsed_times['experiment_counter'].append(experiment_counter) + experiments_elapsed_times['elapsed_time'].append(time.time() - current_experiment_starting_time) + experiment_counter += 1 + logger.info("Python process finished.") + + logger.info('Last experiment folder: ') + logger.info(max(glob.glob(os.path.join('./', '*/')), key=os.path.getmtime)) + else: + logger.info('Invalid task type. Try "follow_route" or "random_roam". Killing program...') + sys.exit(-1) experiments_elapsed_times['total_experiments_elapsed_time'] = time.time() - experiments_starting_time generate_agregated_experiments_metrics(experiments_starting_time, experiments_elapsed_times) - if app_configuration.experiment_random_spawn_point == True: + if app_configuration.experiment_random_spawn_point == True or app_configuration.task == 'follow_route': if os.path.isfile('tmp_circuit.launch'): os.remove('tmp_circuit.launch') logger.info('DONE! Bye, bye :)') diff --git a/behavior_metrics/test_suite_manager_carla.py b/behavior_metrics/test_suite_manager_carla.py new file mode 100644 index 00000000..28248ec9 --- /dev/null +++ b/behavior_metrics/test_suite_manager_carla.py @@ -0,0 +1,165 @@ +import argparse +import os +import sys +import threading +import time +import rospy +import importlib +import random + +from pilot_carla import PilotCarla +from utils import environment +from utils.colors import Colors +from utils.configuration import Config +from utils.controller_carla import ControllerCarla +from utils.logger import logger +from utils.constants import CARLA_TOWNS_TIMEOUTS +from utils.traffic import TrafficManager + +def check_args(argv): + parser = argparse.ArgumentParser(description='Testing suite runner.') + + parser.add_argument('-c', + '--config', + type=str, + action='append', + required=True, + help='{}Path to the configuration file in YML format.{}'.format( + Colors.OKBLUE, Colors.ENDC)) + + group = parser.add_mutually_exclusive_group(required=True) + group.add_argument('-g', + '--gui', + action='store_true', + help='{}Load the GUI (Graphic User Interface). Requires PyQt5 installed{}'.format( + Colors.OKBLUE, Colors.ENDC)) + + group.add_argument('-t', + '--tui', + action='store_true', + help='{}Load the TUI (Terminal User Interface). Requires npyscreen installed{}'.format( + Colors.OKBLUE, Colors.ENDC)) + + group.add_argument('-s', + '--script', + action='store_true', + help='{}Run Behavior Metrics as script{}'.format( + Colors.OKBLUE, Colors.ENDC)) + + parser.add_argument('-r', + '--random', + action='store_true', + help='{}Run Behavior Metrics F1 with random spawning{}'.format( + Colors.OKBLUE, Colors.ENDC)) + + parser.add_argument('-world_counter', + type=str, + action='append', + help='{}World counter{}'.format( + Colors.OKBLUE, Colors.ENDC)) + + parser.add_argument('-brain_counter', + type=str, + action='append', + help='{}Brain counter{}'.format( + Colors.OKBLUE, Colors.ENDC)) + + parser.add_argument('-route_counter', + type=str, + action='append', + help='{}Route counter{}'.format( + Colors.OKBLUE, Colors.ENDC)) + + args = parser.parse_args() + + config_data = {'config': None, 'gui': None, 'tui': None, 'script': None, 'random': False, 'world_counter': 0, 'brain_counter': 0, 'route_counter': 0} + if args.config: + config_data['config'] = [] + for config_file in args.config: + if not os.path.isfile(config_file): + parser.error('{}No such file {} {}'.format(Colors.FAIL, config_file, Colors.ENDC)) + + config_data['config'] = args.config + + if args.gui: + config_data['gui'] = args.gui + + if args.tui: + config_data['tui'] = args.tui + + if args.script: + config_data['script'] = args.script + + return config_data + +def main(): + config_data = check_args(sys.argv) + app_configuration = Config(config_data['config'][0]) + world_counter = int(config_data['world_counter']) + brain_counter = int(config_data['brain_counter']) + route_counter = int(config_data['route_counter']) + + logger.info(str(world_counter) + ' ' + str(brain_counter) + ' ' + str(route_counter)) + + world = app_configuration.current_world[world_counter] + brain = app_configuration.brain_path[brain_counter] + experiment_model = app_configuration.experiment_model[brain_counter] + + + if not os.path.exists(app_configuration.test_suite): + logger.info('Test suite file does not exist! Killing program...') + sys.exit(-1) + + module_dir = os.path.dirname(app_configuration.test_suite) + if module_dir not in sys.path: + sys.path.append(module_dir) + module_name = os.path.splitext(os.path.basename(app_configuration.test_suite))[0] + test_routes_module = importlib.import_module(module_name) + TEST_ROUTES = getattr(test_routes_module, 'TEST_ROUTES') + spawn_point = TEST_ROUTES[route_counter]['start'] + town = TEST_ROUTES[route_counter]['map'] + environment.launch_env(world, + random_spawn_point=False, + carla_simulator=True, + config_spawn_point=spawn_point, + config_town=town) + controller = ControllerCarla() + + # generate traffic + traffic_manager = TrafficManager(app_configuration.number_of_vehicle, + app_configuration.number_of_walker, + app_configuration.percentage_walker_running, + app_configuration.percentage_walker_crossing, + app_configuration.async_mode, + port=random.randint(8000, 9000)) + traffic_manager.generate_traffic() + + # Launch control + pilot = PilotCarla(app_configuration, controller, brain, experiment_model=experiment_model) + pilot.daemon = True + pilot.start() + logger.info('Executing app') + controller.resume_pilot() + controller.unpause_carla_simulation() + controller.record_metrics(app_configuration.stats_out, world_counter=world_counter, brain_counter=brain_counter, repetition_counter=route_counter) + if app_configuration.use_world_timeouts: + experiment_timeout = CARLA_TOWNS_TIMEOUTS[controller.carla_map.name] + else: + experiment_timeout = app_configuration.experiment_timeouts[world_counter] + + rospy.sleep(experiment_timeout) + controller.stop_recording_metrics() + controller.pilot.stop() + controller.stop_pilot() + controller.pause_carla_simulation() + + logger.info('closing all processes...') + controller.pilot.kill() + environment.close_ros_and_simulators() + while not controller.pilot.execution_completed: + time.sleep(1) + + +if __name__ == '__main__': + main() + sys.exit(0) \ No newline at end of file diff --git a/behavior_metrics/utils/configuration.py b/behavior_metrics/utils/configuration.py index 02adf75a..b07ee9f0 100644 --- a/behavior_metrics/utils/configuration.py +++ b/behavior_metrics/utils/configuration.py @@ -84,6 +84,11 @@ def initialize_empty_configuration(self): self.experiment_timeouts = None + self.task = None + self.test_suite = None + self.num_routes = None + self.randomize_routes = None + def initialize_configuration(self, config_data): """Initialize the configuration of the application based on a YAML profile file @@ -95,6 +100,25 @@ def initialize_configuration(self, config_data): self.robot_type = robot['Type'] self.pilot_time_cycle = robot['PilotTimeCycle'] self.current_world = config_data['Behaviors']['Simulation']['World'] + + if 'Task' in config_data['Behaviors']['Simulation']: + self.task = config_data['Behaviors']['Simulation']['Task'] + else: + self.task = 'random_roam' + + if self.task == 'follow_route' and 'TestSuite' in config_data['Behaviors']['Simulation']: + self.test_suite = config_data['Behaviors']['Simulation']['TestSuite'] + + if self.task == 'follow_route' and 'NumRoutes' in config_data['Behaviors']['Simulation']: + self.num_routes = config_data['Behaviors']['Simulation']['NumRoutes'] + else: + self.num_routes = 0 + + if self.task == 'follow_route' and 'RandomizeRoutes' in config_data['Behaviors']['Simulation']: + self.randomize_routes = config_data['Behaviors']['Simulation']['RandomizeRoutes'] + else: + self.randomize_routes = True + if 'WaypointPublisher' in config_data['Behaviors']['Simulation']: self.waypoint_publisher_path = config_data['Behaviors']['Simulation']['WaypointPublisher'] else: @@ -132,7 +156,8 @@ def initialize_configuration(self, config_data): if 'Timeout' in config_data['Behaviors']['Experiment']: self.experiment_timeouts = config_data['Behaviors']['Experiment']['Timeout'] self.use_world_timeouts = config_data['Behaviors']['Experiment']['UseWorldTimeouts'] - self.experiment_repetitions = config_data['Behaviors']['Experiment']['Repetitions'] + if 'Repetitions' in config_data['Behaviors']['Experiment']: + self.experiment_repetitions = config_data['Behaviors']['Experiment']['Repetitions'] if 'RandomSpawnPoint' in config_data['Behaviors']['Simulation']: self.experiment_random_spawn_point = config_data['Behaviors']['Simulation']['RandomSpawnPoint'] diff --git a/behavior_metrics/utils/environment.py b/behavior_metrics/utils/environment.py index 02bf0a71..3739c7aa 100644 --- a/behavior_metrics/utils/environment.py +++ b/behavior_metrics/utils/environment.py @@ -31,7 +31,7 @@ __license__ = 'GPLv3' -def launch_env(launch_file, random_spawn_point=False, carla_simulator=False, config_spawn_point=None): +def launch_env(launch_file, random_spawn_point=False, carla_simulator=False, config_spawn_point=None, config_town=None): """Launch the environmet specified by the launch_file given in command line at launch time. Arguments: launch_file {str} -- path of the launch file to be executed @@ -55,6 +55,18 @@ def launch_env(launch_file, random_spawn_point=False, carla_simulator=False, con else: spawn_point.attrib['default'] = random.choice(CARLA_TOWNS_SPAWN_POINTS[town.attrib['default']]) tree.write('tmp_circuit.launch') + elif config_spawn_point is not None and config_town is not None: + tree = ET.parse(ROOT_PATH + '/' + launch_file) + root = tree.getroot() + town = root.find(".//*[@name=\"town\"]") + if town is None: + town=root.find(".//*[@name='town']") + town.attrib['default'] = config_town + spawn_point = root.find(".//*[@name=\"spawn_point\"]") + if spawn_point is None: + spawn_point=root.find(".//*[@name='spawn_point']") + spawn_point.attrib['default'] = config_spawn_point + tree.write('tmp_circuit.launch') with open("/tmp/.carlalaunch_stdout.log", "w") as out, open("/tmp/.carlalaunch_stderr.log", "w") as err: tree = ET.parse(ROOT_PATH + '/' + launch_file) root = tree.getroot() @@ -67,7 +79,7 @@ def launch_env(launch_file, random_spawn_point=False, carla_simulator=False, con logger.info("SimulatorEnv: launching simulator server.") time.sleep(5) with open("/tmp/.roslaunch_stdout.log", "w") as out, open("/tmp/.roslaunch_stderr.log", "w") as err: - if random_spawn_point: + if random_spawn_point or (config_spawn_point is not None and config_town is not None): child = subprocess.Popen(["roslaunch", ROOT_PATH + '/tmp_circuit.launch'], stdout=out, stderr=err) else: child = subprocess.Popen(["roslaunch", ROOT_PATH + '/' + launch_file], stdout=out, stderr=err) From d0a6cbb2a3d5ab39aae48e6c28302e5487784824 Mon Sep 17 00:00:00 2001 From: Qi Date: Mon, 25 Sep 2023 04:13:30 -0400 Subject: [PATCH 06/11] added missing object file --- .../main_car_custom_camera.json | 163 ++++++++++++++++++ 1 file changed, 163 insertions(+) create mode 100644 behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/main_car_custom_camera.json diff --git a/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/main_car_custom_camera.json b/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/main_car_custom_camera.json new file mode 100644 index 00000000..5054f0fd --- /dev/null +++ b/behavior_metrics/configs/CARLA/CARLA_launch_files/CARLA_object_files/main_car_custom_camera.json @@ -0,0 +1,163 @@ +{ + "objects": + [ + { + "type": "sensor.pseudo.traffic_lights", + "id": "traffic_lights" + }, + { + "type": "sensor.pseudo.objects", + "id": "objects" + }, + { + "type": "sensor.pseudo.actor_list", + "id": "actor_list" + }, + { + "type": "sensor.pseudo.markers", + "id": "markers" + }, + { + "type": "sensor.pseudo.opendrive_map", + "id": "map" + }, + { + "type": "vehicle.tesla.model3", + "id": "ego_vehicle", + "sensors": + [ + { + "type": "sensor.camera.rgb", + "id": "rgb_front", + "spawn_point": {"x": 1.5, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 15.0, "yaw": 0.0}, + "image_size_x": 288, + "image_size_y": 200, + "fov": 90.0 + }, + { + "type": "sensor.camera.rgb", + "id": "rgb_view", + "spawn_point": {"x": -4.5, "y": 0.0, "z": 2.8, "roll": 0.0, "pitch": 20.0, "yaw": 0.0}, + "image_size_x": 800, + "image_size_y": 600, + "fov": 90.0, + "attached_objects": + [ + { + "type": "actor.pseudo.control", + "id": "control" + } + ] + }, + { + "type": "sensor.lidar.ray_cast", + "id": "lidar", + "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "range": 50, + "channels": 32, + "points_per_second": 320000, + "upper_fov": 2.0, + "lower_fov": -26.8, + "rotation_frequency": 20, + "noise_stddev": 0.0 + }, + { + "type": "sensor.lidar.ray_cast_semantic", + "id": "semantic_lidar", + "spawn_point": {"x": 0.0, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "range": 50, + "channels": 32, + "points_per_second": 320000, + "upper_fov": 2.0, + "lower_fov": -26.8, + "rotation_frequency": 20 + }, + { + "type": "sensor.other.radar", + "id": "radar_front", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "horizontal_fov": 30.0, + "vertical_fov": 10.0, + "points_per_second": 1500, + "range": 100.0 + }, + { + "type": "sensor.camera.semantic_segmentation", + "id": "semantic_segmentation_front", + "spawn_point": {"x": 1.5, "y": 0.0, "z": 2.4, "roll": 0.0, "pitch": 15.0, "yaw": 0.0}, + "fov": 90.0, + "image_size_x": 288, + "image_size_y": 200 + }, + { + "type": "sensor.camera.depth", + "id": "depth_front", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "fov": 90.0, + "image_size_x": 400, + "image_size_y": 70 + }, + { + "type": "sensor.camera.dvs", + "id": "dvs_front", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "fov": 90.0, + "image_size_x": 400, + "image_size_y": 70, + "positive_threshold": 0.3, + "negative_threshold": 0.3, + "sigma_positive_threshold": 0.0, + "sigma_negative_threshold": 0.0, + "use_log": true, + "log_eps": 0.001 + }, + { + "type": "sensor.other.gnss", + "id": "gnss", + "spawn_point": {"x": 1.0, "y": 0.0, "z": 2.0}, + "noise_alt_stddev": 0.0, "noise_lat_stddev": 0.0, "noise_lon_stddev": 0.0, + "noise_alt_bias": 0.0, "noise_lat_bias": 0.0, "noise_lon_bias": 0.0 + }, + { + "type": "sensor.other.imu", + "id": "imu", + "spawn_point": {"x": 2.0, "y": 0.0, "z": 2.0, "roll": 0.0, "pitch": 0.0, "yaw": 0.0}, + "noise_accel_stddev_x": 0.0, "noise_accel_stddev_y": 0.0, "noise_accel_stddev_z": 0.0, + "noise_gyro_stddev_x": 0.0, "noise_gyro_stddev_y": 0.0, "noise_gyro_stddev_z": 0.0, + "noise_gyro_bias_x": 0.0, "noise_gyro_bias_y": 0.0, "noise_gyro_bias_z": 0.0 + }, + { + "type": "sensor.other.collision", + "id": "collision", + "spawn_point": {"x": 2.5, "y": 0.0, "z": 0.7} + }, + { + "type": "sensor.other.lane_invasion", + "id": "lane_invasion", + "spawn_point": {"x": 0.0, "y": 0.0, "z": 0.0} + }, + { + "type": "sensor.pseudo.tf", + "id": "tf" + }, + { + "type": "sensor.pseudo.objects", + "id": "objects" + }, + { + "type": "sensor.pseudo.odom", + "id": "odometry" + }, + { + "type": "sensor.pseudo.speedometer", + "id": "speedometer" + }, + { + "type": "actor.pseudo.control", + "id": "control" + } + ] + } + ] +} + From 9a4cb9e062d3b7313ef2282f07cfdfa610ac3c4e Mon Sep 17 00:00:00 2001 From: Meiqi Zhao Date: Fri, 6 Oct 2023 14:31:06 +0000 Subject: [PATCH 07/11] implemented evaluation metrics; fixed bugs; --- ...a_segmentation_based_imitation_learning.py | 81 ++++++++++++++---- .../brains/CARLA/utils/high_level_command.py | 50 ++++++++++- .../brains/CARLA/utils/test_utils.py | 10 ++- .../default_carla_imitation_learning.yml | 70 +++++++++++++++ .../CARLA/default_carla_test_suite.yml | 8 +- .../CARLA/test_suites/Town02_two_turns.py | 14 +-- behavior_metrics/driver_carla.py | 2 +- .../il_models/pilotnet_combined_control.pth | Bin 1514699 -> 0 bytes .../models/il_models/pilotnet_v8.0.pth | Bin 1514763 -> 0 bytes behavior_metrics/test_suite_manager_carla.py | 53 +++++++++--- behavior_metrics/utils/constants.py | 10 +++ behavior_metrics/utils/controller_carla.py | 51 ++++++++++- behavior_metrics/utils/environment.py | 2 +- behavior_metrics/utils/metrics_carla.py | 4 +- 14 files changed, 308 insertions(+), 47 deletions(-) create mode 100644 behavior_metrics/configs/CARLA/default_carla_imitation_learning.yml delete mode 100644 behavior_metrics/models/il_models/pilotnet_combined_control.pth delete mode 100644 behavior_metrics/models/il_models/pilotnet_v8.0.pth diff --git a/behavior_metrics/brains/CARLA/brain_carla_segmentation_based_imitation_learning.py b/behavior_metrics/brains/CARLA/brain_carla_segmentation_based_imitation_learning.py index e264446a..345c922a 100644 --- a/behavior_metrics/brains/CARLA/brain_carla_segmentation_based_imitation_learning.py +++ b/behavior_metrics/brains/CARLA/brain_carla_segmentation_based_imitation_learning.py @@ -1,7 +1,5 @@ -from torchvision import transforms -from PIL import Image from brains.CARLA.utils.pilotnet_onehot import PilotNetOneHot -from brains.CARLA.utils.test_utils import traffic_light_to_int, model_control +from brains.CARLA.utils.test_utils import traffic_light_to_int, model_control, calculate_delta_yaw from utils.constants import PRETRAINED_MODELS_DIR, ROOT_PATH from brains.CARLA.utils.high_level_command import HighLevelCommandLoader from os import path @@ -9,14 +7,11 @@ import numpy as np import torch -import torchvision -import cv2 import time -import os import math import carla -PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'il_models/' +PRETRAINED_MODELS = ROOT_PATH + '/' + PRETRAINED_MODELS_DIR + 'CARLA/' class Brain: @@ -28,12 +23,14 @@ def __init__(self, sensors, actuators, model=None, handler=None, config=None): self.inference_times = [] self.gpu_inference = config['GPU'] self.device = torch.device('cuda' if (torch.cuda.is_available() and self.gpu_inference) else 'cpu') - + self.red_light_counter = 0 + self.running_light = False + client = carla.Client('localhost', 2000) client.set_timeout(100.0) world = client.get_world() self.map = world.get_map() - + weather = carla.WeatherParameters.ClearNoon world.set_weather(weather) @@ -58,8 +55,17 @@ def __init__(self, sensors, actuators, model=None, handler=None, config=None): self.net.load_state_dict(torch.load(PRETRAINED_MODELS + model,map_location=self.device)) self.net.eval() - self.hlc_loader = HighLevelCommandLoader(self.vehicle, self.map) + if 'Route' in config: + route = config['Route'] + print('route: ', route) + self.hlc_loader = HighLevelCommandLoader(self.vehicle, self.map, route=route) + self.prev_hlc = 0 + self.prev_yaw = None + self.delta_yaw = 0 + + self.target_point = None + self.termination_code = 0 # 0: not terminated; 1: arrived at target; 2: wrong turn def update_frame(self, frame_id, data): """Update the information to be shown in one of the GUI's frames. @@ -95,19 +101,54 @@ def execute(self): start_time = time.time() try: # calculate speed - speed_m_s = self.vehicle.get_velocity() - speed = 3.6 * math.sqrt(speed_m_s.x**2 + speed_m_s.y**2 + speed_m_s.z**2) + velocity = self.vehicle.get_velocity() + speed_m_s = np.sqrt(velocity.x**2 + velocity.y**2 + velocity.z**2) + speed = 3.6 * speed_m_s #m/s to km/h - # randomly choose high-level command if at junction - hlc = self.hlc_loader.get_random_hlc() + # read next high-level command or choose a random direction + hlc = self.hlc_loader.get_next_hlc() + if hlc != 0: + if self.prev_hlc == 0: + self.prev_yaw = self.vehicle.get_transform().rotation.yaw + else: + cur_yaw = self.vehicle.get_transform().rotation.yaw + self.delta_yaw += calculate_delta_yaw(self.prev_yaw, cur_yaw) + self.prev_yaw = cur_yaw + + # detect whether the vehicle made the correct turn + turning_infraction = False + if self.prev_hlc != 0 and hlc == 0: + print(f'turned {self.delta_yaw} degrees') + if 45 < np.abs(self.delta_yaw) < 180: + if self.delta_yaw < 0 and self.prev_hlc != 1: + turning_infraction = True + elif self.delta_yaw > 0 and self.prev_hlc != 2: + turning_infraction = True + elif self.prev_hlc != 3: + turning_infraction = True + if turning_infraction: + print('Wrong Turn!!!') + self.termination_code = 2 + self.delta_yaw = 0 + + self.prev_hlc = hlc # get traffic light status light_status = -1 + vehicle_location = self.vehicle.get_transform().location if self.vehicle.is_at_traffic_light(): traffic_light = self.vehicle.get_traffic_light() light_status = traffic_light.get_state() + traffic_light_location = traffic_light.get_transform().location + distance_to_traffic_light = np.sqrt((vehicle_location.x - traffic_light_location.x)**2 + (vehicle_location.y - traffic_light_location.y)**2) + if light_status == carla.libcarla.TrafficLightState.Red and distance_to_traffic_light < 6 and speed_m_s > 5: + if not self.running_light: + self.running_light = True + self.red_light_counter += 1 + else: + self.running_light = False - print(f'hlc: {hlc}') + print(f'high-level command: {hlc}') #print(f'light: {light_status}') frame_data = { 'hlc': hlc, @@ -128,5 +169,15 @@ def execute(self): self.motors.sendThrottle(throttle) self.motors.sendSteer(steer) self.motors.sendBrake(brake) + + # calculate distance to target point + # print(f'vehicle location: ({vehicle_location.x}, {-vehicle_location.y})') + # print(f'target point: ({self.target_point[0]}, {self.target_point[1]})') + distance_to_target = np.sqrt((self.target_point[0] - vehicle_location.x)**2 + (self.target_point[1] - (-vehicle_location.y))**2) + print(f'Euclidean distance to target: {distance_to_target}') + if distance_to_target < 1.5: + self.termination_code = 1 + + except Exception as err: print(err) \ No newline at end of file diff --git a/behavior_metrics/brains/CARLA/utils/high_level_command.py b/behavior_metrics/brains/CARLA/utils/high_level_command.py index abfc3a8f..e27fb0c0 100644 --- a/behavior_metrics/brains/CARLA/utils/high_level_command.py +++ b/behavior_metrics/brains/CARLA/utils/high_level_command.py @@ -2,12 +2,14 @@ import carla class HighLevelCommandLoader: - def __init__(self, vehicle, map): + def __init__(self, vehicle, map, route=None): self.vehicle = vehicle self.map = map self.prev_hlc = 0 - - def get_random_hlc(self): + self.route = route + + def _get_junction(self): + """determine whether vehicle is at junction""" junction = None vehicle_location = self.vehicle.get_transform().location vehicle_waypoint = self.map.get_waypoint(vehicle_location) @@ -20,6 +22,21 @@ def get_random_hlc(self): break if vehicle_waypoint.is_junction: junction = vehicle_waypoint.get_junction() + return junction + + def _command_to_int(self, command): + commands = { + 'Left': 1, + 'Right': 2, + 'Straight': 3 + } + return commands[command] + + def get_random_hlc(self): + """select a random turn at junction""" + junction = self._get_junction() + vehicle_location = self.vehicle.get_transform().location + vehicle_waypoint = self.map.get_waypoint(vehicle_location) # randomly select a turning direction if junction is not None: @@ -45,3 +62,30 @@ def get_random_hlc(self): return hlc + + def get_next_hlc(self): + if self.route is not None and len(self.route) > 0: + return self.load_next_hlc() + return self.get_random_hlc() + + def load_next_hlc(self): + """load the next high level command from pre-defined route""" + if self.prev_hlc is None: + return None + + junction = self._get_junction() + + if junction is not None: + if self.prev_hlc == 0: + if len(self.route) == 0: + hlc = None + hlc = self._command_to_int(self.route.pop(0)) + else: + hlc = self.prev_hlc + else: + hlc = 0 + + self.prev_hlc = hlc + + return hlc + \ No newline at end of file diff --git a/behavior_metrics/brains/CARLA/utils/test_utils.py b/behavior_metrics/brains/CARLA/utils/test_utils.py index 1c096138..f67f1af7 100644 --- a/behavior_metrics/brains/CARLA/utils/test_utils.py +++ b/behavior_metrics/brains/CARLA/utils/test_utils.py @@ -128,4 +128,12 @@ def traffic_light_to_int(light_status): carla.libcarla.TrafficLightState.Green: 2, carla.libcarla.TrafficLightState.Yellow: 3 } - return light_dict[light_status] \ No newline at end of file + return light_dict[light_status] + +def calculate_delta_yaw(prev_yaw, cur_yaw): + delta_yaw = cur_yaw - prev_yaw + if delta_yaw > 180: + delta_yaw -= 360 + elif delta_yaw < -180: + delta_yaw += 360 + return delta_yaw \ No newline at end of file diff --git a/behavior_metrics/configs/CARLA/default_carla_imitation_learning.yml b/behavior_metrics/configs/CARLA/default_carla_imitation_learning.yml new file mode 100644 index 00000000..612b4c10 --- /dev/null +++ b/behavior_metrics/configs/CARLA/default_carla_imitation_learning.yml @@ -0,0 +1,70 @@ +Behaviors: + Robot: + Sensors: + Cameras: + Camera_0: + Name: 'camera_0' + Topic: '/carla/ego_vehicle/rgb_front/image' + Camera_1: + Name: 'camera_1' + Topic: '/carla/ego_vehicle/rgb_view/image' + Camera_2: + Name: 'camera_2' + Topic: '/carla/ego_vehicle/semantic_segmentation_front/image' + Camera_3: + Name: 'camera_3' + Topic: '/carla/ego_vehicle/dvs_front/image' + Pose3D: + Pose3D_0: + Name: 'pose3d_0' + Topic: '/carla/ego_vehicle/odometry' + BirdEyeView: + BirdEyeView_0: + Name: 'bird_eye_view_0' + Topic: '' + Speedometer: + Speedometer_0: + Name: 'speedometer_0' + Topic: '/carla/ego_vehicle/speedometer' + Actuators: + CARLA_Motors: + Motors_0: + Name: 'motors_0' + Topic: '/carla/ego_vehicle/vehicle_control_cmd' + MaxV: 3 + MaxW: 0.3 + BrainPath: 'brains/CARLA/brain_carla_segmentation_based_imitation_learning.py' + PilotTimeCycle: 50 + AsyncMode: False + Parameters: + Model: 'pilotnet_v8.0.pth' + ImageCropped: False + ImageSize: [ 100,50 ] + ImageNormalized: True + PredictionsNormalized: True + GPU: True + UseOptimized: False + ImageTranform: '' + Type: 'CARLA' + Simulation: + World: configs/CARLA/CARLA_launch_files/town_02_anticlockwise_imitation_learning.launch + RandomSpawnPoint: False + NumberOfVehicle: 50 + NumberOfWalker: 0 + PercentagePedestriansRunning: 0.5 + PercentagePedestriansCrossing: 0.5 + Dataset: + In: '/tmp/my_bag.bag' + Out: '' + Stats: + Out: './' + PerfectLap: './perfect_bags/lap-simple-circuit.bag' + Layout: + Frame_0: + Name: frame_0 + Geometry: [0, 1, 1, 2] + Data: rgbimage + Frame_1: + Name: frame_1 + Geometry: [1, 1, 1, 2] + Data: rgbimage \ No newline at end of file diff --git a/behavior_metrics/configs/CARLA/default_carla_test_suite.yml b/behavior_metrics/configs/CARLA/default_carla_test_suite.yml index c0ee08f4..897b0f45 100644 --- a/behavior_metrics/configs/CARLA/default_carla_test_suite.yml +++ b/behavior_metrics/configs/CARLA/default_carla_test_suite.yml @@ -50,13 +50,13 @@ Behaviors: Name: "Carla Town02 Test Suite" Description: "Testing model in Town02 with each route consisting of two turns." UseWorldTimeouts: False - Timeout: [10] # for each world! + Timeout: [500] # for each world! Simulation: Task: "follow_route" - World: [configs/CARLA_launch_files/test_suite_template.launch] - TestSuite: configs/test_suites/Town02_two_turns.py + World: [configs/CARLA/CARLA_launch_files/test_suite_template.launch] + TestSuite: 'Town02_two_turns' RandomizeRoutes: False - NumRoutes: 12 + NumRoutes: 2 RandomSpawnPoint: False NumberOfVehicle: 50 NumberOfWalker: 0 diff --git a/behavior_metrics/configs/CARLA/test_suites/Town02_two_turns.py b/behavior_metrics/configs/CARLA/test_suites/Town02_two_turns.py index 99c3ee93..8ce91401 100644 --- a/behavior_metrics/configs/CARLA/test_suites/Town02_two_turns.py +++ b/behavior_metrics/configs/CARLA/test_suites/Town02_two_turns.py @@ -6,13 +6,6 @@ "distance": 158, "commands": ["Right", "Right"] }, - { - "map": "Town02", - "start": "45.24, -225.59, 0.5, 0.0, 0.0, 90", - "end": "-7.53, -270.73, 0.5, 0.0, 0.0, -90.0", - "distance": 166, - "commands": ["Left", "Left"] - }, { "map": "Town02", "start":"136.11, -302.57, 0.5, 0.0, 0.0, 180.0", @@ -20,6 +13,13 @@ "distance": 174, "commands": ["Right", "Straight"] }, + { + "map": "Town02", + "start": "45.24, -225.59, 0.5, 0.0, 0.0, 90", + "end": "-7.53, -270.73, 0.5, 0.0, 0.0, -90.0", + "distance": 166, + "commands": ["Left", "Left"] + }, { "map": "Town02", "start": "41.39, -203.90, 0.5, 0.0, 0.0, -90.0", diff --git a/behavior_metrics/driver_carla.py b/behavior_metrics/driver_carla.py index c3c1687a..7cdd5078 100644 --- a/behavior_metrics/driver_carla.py +++ b/behavior_metrics/driver_carla.py @@ -368,7 +368,7 @@ def main(): logger.info("Experiment attempt: " + str(experiment_attempts+1)) current_experiment_starting_time = time.time() success = os.system("python3 test_suite_manager_carla.py -c " + config_data['config'][0] + " -s -world_counter " + str(world_counter) + " -brain_counter " + str(brain_counter) + " -route_counter " + str(route_counter)) - + print('success: ', success) if success != 0: root = './' folders = list(os.walk(root))[1:] diff --git 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get_lane_invasions(experiment_metrics, lane_invasion_points, df_checkpoints): @@ -305,7 +308,6 @@ def get_position_deviation_and_effective_completed_distance(experiment_metrics, checkpoints_tuples_y.append(checkpoint_y) checkpoints_speeds.append(current_checkpoint[2]) checkpoints_tuples.append((checkpoint_x, checkpoint_y, current_checkpoint[2])) - min_dists = [] best_checkpoint_points_x = [] best_checkpoint_points_y = [] From edf3308bb06e0e177d16ad56d3a246267553cc21 Mon Sep 17 00:00:00 2001 From: Meiqi Zhao Date: Fri, 6 Oct 2023 14:52:04 +0000 Subject: [PATCH 08/11] relocated model files --- .../CARLA/pilotnet_combined_control.pth | Bin 0 -> 1514699 bytes .../models/CARLA/pilotnet_v8.0.pth | Bin 0 -> 1514763 bytes 2 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 behavior_metrics/models/CARLA/pilotnet_combined_control.pth create mode 100644 behavior_metrics/models/CARLA/pilotnet_v8.0.pth diff --git a/behavior_metrics/models/CARLA/pilotnet_combined_control.pth 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zP4CYy{_^;T5wQvjS@HKk8Ve%qjf11u;f=pte{~?gI&ELbAY?LrIVjut0{u(Ap z?VrQg{ymKQ_m2nuXQ$I;q5l7e&A@*N^B>*0)cLbAntk|B`)iz}$Nv)NKl?M=DN%mU zAiVAz636cE+m-tGy5D~vOMi=_y;$=fzhztD-{X`m)>5gL6A1pazxHS5l7ERa z`tNc4^t=}jXWz}A_SZO>q5l%c{_k-lek3(-U@`u*zs7M|`7d!C{vPK|wk@y3V*F`; zjU&J6U*b6aJ&xoMV~77aEdIJ19{ra%|1n(gyJmJ6v9A1Se+{Fy@t?c%AERY70j~T% z_onb)!u;o8#rMC_%C7pW2lav_&qzCeJ_97U&E;R z4*tho`9DVLe@`!e3*-0CVVwRx;Q#w9{ns!_np*$Z8|S}=`QNA7zwUoYga40V{`&+! z$wyXp6#F9nJcdYF{?`-s@1XyF_CG&UW&Z08buF#`_X+zPJAws*v- Date: Fri, 6 Oct 2023 14:56:30 +0000 Subject: [PATCH 09/11] fixed merge conflicts --- behavior_metrics/utils/controller_carla.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/behavior_metrics/utils/controller_carla.py b/behavior_metrics/utils/controller_carla.py index bd8976dd..ac35cdd3 100644 --- a/behavior_metrics/utils/controller_carla.py +++ b/behavior_metrics/utils/controller_carla.py @@ -345,7 +345,7 @@ def stop_recording_metrics(self, termination_code=None, route_length=None): self.experiment_metrics['experiment_total_real_time'] = end_time - self.pilot.pilot_start_time experiment_metrics_filename = self.metrics_record_dir_path + self.time_str + '/' + self.time_str - self.experiment_metrics = metrics_carla.get_metrics(self.experiment_metrics, self.experiment_metrics_bag_filename, self.map_waypoints, experiment_metrics_filename) + self.experiment_metrics = metrics_carla.get_metrics(self.experiment_metrics, self.experiment_metrics_bag_filename, self.map_waypoints, experiment_metrics_filename, self.pilot.configuration) self.experiment_metrics['collisions_vehicle'] = 0 self.experiment_metrics['collisions_walker'] = 0 self.experiment_metrics['collisions_static'] = 0 From 96401fd763aa6e7f2c6f2666b713a0ec02e4a2f7 Mon Sep 17 00:00:00 2001 From: Meiqi Zhao Date: Fri, 6 Oct 2023 15:00:36 +0000 Subject: [PATCH 10/11] fix merge conflict --- behavior_metrics/utils/controller_carla.py | 46 ---------------------- 1 file changed, 46 deletions(-) diff --git a/behavior_metrics/utils/controller_carla.py b/behavior_metrics/utils/controller_carla.py index ac35cdd3..cbca7d26 100644 --- a/behavior_metrics/utils/controller_carla.py +++ b/behavior_metrics/utils/controller_carla.py @@ -346,52 +346,6 @@ def stop_recording_metrics(self, termination_code=None, route_length=None): experiment_metrics_filename = self.metrics_record_dir_path + self.time_str + '/' + self.time_str self.experiment_metrics = metrics_carla.get_metrics(self.experiment_metrics, self.experiment_metrics_bag_filename, self.map_waypoints, experiment_metrics_filename, self.pilot.configuration) - self.experiment_metrics['collisions_vehicle'] = 0 - self.experiment_metrics['collisions_walker'] = 0 - self.experiment_metrics['collisions_static'] = 0 - - collision_actor_ids = self.experiment_metrics['collision_actor_ids'] - for actor_id in collision_actor_ids: - actor = self.world.get_actor(actor_id) - if actor: - actor_type = actor.type_id.split('.')[0] - if actor_type == 'vehicle': - self.experiment_metrics['collisions_vehicle'] += 1 - elif actor_type == 'walker': - self.experiment_metrics['collisions_walker'] += 1 - else: - self.experiment_metrics['collisions_static'] += 1 - else: - print(f"No actor found with ID {actor_id}") - - if hasattr(self.pilot.brains.active_brain, 'red_light_counter'): - self.experiment_metrics['traffic_light_infractions'] = self.pilot.brains.active_brain.red_light_counter - self.experiment_metrics['traffic_light_infractions_per_km'] = self.experiment_metrics['traffic_light_infractions'] / (self.experiment_metrics['effective_completed_distance']/1000) - - if route_length is not None: - self.experiment_metrics['route_completion'] = self.experiment_metrics['effective_completed_distance'] / route_length - - wrong_turn_counter = 0 - time_out_counter = 0 - if termination_code is not None: - if termination_code == 1: - self.experiment_metrics['termination cause'] = 'success' - elif termination_code == 2: - wrong_turn_counter += 1 - self.experiment_metrics['termination cause'] = 'wrong turn' - elif termination_code == 3: - time_out_counter += 1 - self.experiment_metrics['termination cause'] = 'time out' - - if 'route_completion' in self.experiment_metrics.keys() and 'traffic_light_infractions' in self.experiment_metrics.keys() and termination_code is not None: - self.experiment_metrics['driving score'] = self.experiment_metrics['route_completion'] * \ - CARLA_INFRACTION_PENALTIES['collision_vehicle']**self.experiment_metrics['collisions_vehicle'] * \ - CARLA_INFRACTION_PENALTIES['collision_static']**self.experiment_metrics['collisions_static'] * \ - CARLA_INFRACTION_PENALTIES['collision_walker']**self.experiment_metrics['collisions_walker'] * \ - CARLA_INFRACTION_PENALTIES['red_light']**self.experiment_metrics['traffic_light_infractions'] * \ - CARLA_INFRACTION_PENALTIES['wrong_turn']**wrong_turn_counter * \ - CARLA_INFRACTION_PENALTIES['time_out']**time_out_counter - self.save_metrics(first_images, last_images) for key, value in self.experiment_metrics.items(): From ff7d7ceee1c63ee056464f302002cc1fa970631c Mon Sep 17 00:00:00 2001 From: Meiqi Zhao Date: Fri, 6 Oct 2023 15:05:24 +0000 Subject: [PATCH 11/11] calculate driving score --- behavior_metrics/utils/controller_carla.py | 45 ++++++++++++++++++++++ 1 file changed, 45 insertions(+) diff --git a/behavior_metrics/utils/controller_carla.py b/behavior_metrics/utils/controller_carla.py index b3638551..f9643d44 100644 --- a/behavior_metrics/utils/controller_carla.py +++ b/behavior_metrics/utils/controller_carla.py @@ -354,6 +354,51 @@ def stop_recording_metrics(self, termination_code=None, route_length=None): experiment_metrics_filename = self.metrics_record_dir_path + self.time_str + '/' + self.time_str self.experiment_metrics = metrics_carla.get_metrics(self.experiment_metrics, self.experiment_metrics_bag_filename, self.map_waypoints, experiment_metrics_filename, self.pilot.configuration) + self.experiment_metrics['collisions_vehicle'] = 0 + self.experiment_metrics['collisions_walker'] = 0 + self.experiment_metrics['collisions_static'] = 0 + + collision_actor_ids = self.experiment_metrics['collision_actor_ids'] + for actor_id in collision_actor_ids: + actor = self.world.get_actor(actor_id) + if actor: + actor_type = actor.type_id.split('.')[0] + if actor_type == 'vehicle': + self.experiment_metrics['collisions_vehicle'] += 1 + elif actor_type == 'walker': + self.experiment_metrics['collisions_walker'] += 1 + else: + self.experiment_metrics['collisions_static'] += 1 + else: + print(f"No actor found with ID {actor_id}") + + if hasattr(self.pilot.brains.active_brain, 'red_light_counter'): + self.experiment_metrics['traffic_light_infractions'] = self.pilot.brains.active_brain.red_light_counter + self.experiment_metrics['traffic_light_infractions_per_km'] = self.experiment_metrics['traffic_light_infractions'] / (self.experiment_metrics['effective_completed_distance']/1000) + + if route_length is not None: + self.experiment_metrics['route_completion'] = self.experiment_metrics['effective_completed_distance'] / route_length + + wrong_turn_counter = 0 + time_out_counter = 0 + if termination_code is not None: + if termination_code == 1: + self.experiment_metrics['termination cause'] = 'success' + elif termination_code == 2: + wrong_turn_counter += 1 + self.experiment_metrics['termination cause'] = 'wrong turn' + elif termination_code == 3: + time_out_counter += 1 + self.experiment_metrics['termination cause'] = 'time out' + + if 'route_completion' in self.experiment_metrics.keys() and 'traffic_light_infractions' in self.experiment_metrics.keys() and termination_code is not None: + self.experiment_metrics['driving score'] = self.experiment_metrics['route_completion'] * \ + CARLA_INFRACTION_PENALTIES['collision_vehicle']**self.experiment_metrics['collisions_vehicle'] * \ + CARLA_INFRACTION_PENALTIES['collision_static']**self.experiment_metrics['collisions_static'] * \ + CARLA_INFRACTION_PENALTIES['collision_walker']**self.experiment_metrics['collisions_walker'] * \ + CARLA_INFRACTION_PENALTIES['red_light']**self.experiment_metrics['traffic_light_infractions'] * \ + CARLA_INFRACTION_PENALTIES['wrong_turn']**wrong_turn_counter * \ + CARLA_INFRACTION_PENALTIES['time_out']**time_out_counter self.save_metrics(first_images, last_images) for key, value in self.experiment_metrics.items():