class CarlaEnv(gym.Env):
def __init__(self, config=ENV_CONFIG):
self.config = config
# print('>>>>>>>>>>>>>>>>>>>>>>>>>>>>>'*200)
self.command = {
"stop": 1,
"lane_keep": 2,
"turn_right": 3,
"turn_left": 4,
}
# change action space
self.action_space = Box(-1.0,
1.0,
shape=(ENV_CONFIG["action_dim"], ),
dtype=np.float32)
if ENV_CONFIG["image_mode"] == "encode":
framestack = 7
elif ENV_CONFIG["image_mode"] == "stack":
framestack = 3
else:
framestack = 3
image_space = Box(0,
255,
shape=(config["y_res"], config["x_res"], framestack),
dtype=np.float32)
self.observation_space = image_space
# environment config
self._spec = lambda: None
self._spec.id = "Carla_v0"
# experiment config
self.num_steps = 0
self.total_reward = 0
self.episode_id = None
self.measurements_file = None
self.weather = None
self.feature_map = None
# actors
self.actor_list = [
] # save actor list for destroying them after finish
self.vehicle = None
self.collision_sensor = None
self.camera_rgb1 = None
self.camera_rgb2 = None
self.invasion_sensor = None
# states and data
self._history_info = [] # info history
self._history_collision = [] # collision history
self._history_invasion = [] # invasion history
self._image_rgb1 = [] # save a list of rgb image
self._image_rgb2 = [] # save a list of rgb image
self._history_waypoint = []
self._obs_collect = []
self._global_step = 0
# # self._d_collect = []
# # initialize our world
# self._carla_server = ServerManagerBinary()
# self.server_port = random.randint(1000, 60000)
# self.world = None
#
# # start a new carla service
# self._carla_server.reset(self.config["host"], self.server_port)
# self._carla_server.wait_until_ready()
self.server_process = None
self.server_port = None
self.world = None
# self.init_server()
self._error_rest_test = 0
def __del__(self):
cleanup()
def init_server(self):
print("Initializing new Carla server...")
# Create a new server process and start the client.
self.server_port = 2000
self.server_process = subprocess.Popen([
"/home/sdc/Desktop/carla94/CarlaUE4.sh",
"/Game/Carla/Maps/Town01",
"-benchmark",
'-fps=20'
"-ResX=1024",
"-ResY=768",
"-host = 127.0.0.1",
"-carla-port=2000",
],
preexec_fn=os.setsid,
stdout=open(os.devnull, "w"))
live_carla_processes.add(self.server_process.pid)
# print(live_carla_processes)
# live_carla_processes.add(os.getpgid(self.server_process.pid))
try:
pre_pid = np.loadtxt(PID_FILE_NAME, ndmin=1)
pre_pid = pre_pid.astype(int)
if len(pre_pid) > 5:
pre_pid = np.delete(pre_pid, range(0, len(pre_pid - 5)))
except:
pre_pid = []
pid = np.array([x for x in live_carla_processes])
np.savetxt(PID_FILE_NAME, np.concatenate([pre_pid, pid]), fmt='%d')
# with open('/tmp/_carla_pid.txt', 'w') as f:
# f.write(str(self.server_process.pid))
# f.write(str(os.getpgid(self.server_process.pid))) # write carla server pid into file
time.sleep(20) # wait for world get ready
# @set_timeout(10)
def _restart(self):
"""restart world and add sensors"""
# self.init_server()
connect_fail_times = 0
self.world = None
while self.world is None:
try:
self.client = carla.Client(self.config["host"],
self.server_port)
self.client.set_timeout(2.0)
self.world = self.client.get_world()
self.map = self.world.get_map()
except Exception as e:
connect_fail_times += 1
print("Error connecting: {}, attempt {}".format(
e, connect_fail_times))
time.sleep(2)
if connect_fail_times > 5:
break
world = self.world
self._global_step = 0
# actors
self.actor_list = [
] # save actor list for destroying them after finish
self.vehicle = None
self.collision_sensor = None
self.invasion_sensor = None
self._history_info = [] # info history
self._history_collision = [] # collision history
self._history_invasion = [] # invasion history
self._image_rgb1 = [] # save a list of rgb image
self._image_rgb2 = []
self._history_waypoint = []
self.other_actors_list = [] #save other actors
for a in self.world.get_actors().filter('vehicle.*'):
# print(a)
try:
a.destroy()
time.sleep(2)
except:
pass
# for b in self.world.get_actors().filter('sensor.*'):
# try:
# b.destroy()
# time.sleep(2)
# except:
# pass
try:
#setup ego_vehicle & other_actor
self.scenario_name = 'VehicleTurningLeft' #the name of scenario
bp_library = self.world.get_blueprint_library()
# setup vehicle
scenario_config_file = find_scenario_config(self.scenario_name)
self.scenario_configurations = parse_scenario_configuration(
scenario_config_file, self.scenario_name)
for config in self.scenario_configurations:
print(config)
# Prepare scenario
print("Preparing scenario: " + config.name)
scenario_class = ScenarioRunner.get_scenario_class_or_fail(
config.type)
try:
# init ego_vehicle
# spawn_point of ego_vehicle
spawn_point = config.ego_vehicle.transform
# model of ego_vehicle
bp_vehicle = config.ego_vehicle.model
blueprint = random.choice(bp_library.filter(bp_vehicle))
blueprint.set_attribute('role_name', 'hero')
# set ego_vehicle
self.vehicle = self.world.try_spawn_actor(
blueprint, spawn_point)
self.actor_list.append(self.vehicle)
# init other_actor
for actor in config.other_actors:
# spawn_point of other actor
actor_point = actor.transform
# model of other actor
actor_bp_vehicle = actor.model
actor_blueprint = random.choice(
bp_library.filter(actor_bp_vehicle))
actor_blueprint.set_attribute('role_name', 'scenario')
self.other_actor = self.world.try_spawn_actor(
actor_blueprint, actor_point)
#set other actor
self.other_actors_list.append(self.other_actor)
self.actor_list.append(self.other_actors_list)
#input parameter of scenario
self.scenario = scenario_class(self.world, self.vehicle,
self.other_actors_list,
config.town, False, False)
except Exception as exception:
print("The scenario cannot be loaded")
traceback.print_exc()
print(exception)
self.cleanup()
#setup sensor
camera_transform = carla.Transform(carla.Location(x=1, y=0, z=2))
camera_rgb1 = bp_library.find('sensor.camera.rgb')
camera_rgb1.set_attribute('fov', '120')
camera_rgb1.set_attribute('image_size_x', str(ENV_CONFIG["x_res"]))
camera_rgb1.set_attribute('image_size_y', str(ENV_CONFIG["y_res"]))
# here is the bug, carla will throw bad_weak_ptr() and block the process
self.camera_rgb1 = world.spawn_actor(
camera_rgb1, camera_transform,
attach_to=self.vehicle) # 32 !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
self.actor_list.append(self.camera_rgb1)
bp = bp_library.find('sensor.other.collision')
self.collision_sensor = world.try_spawn_actor(
bp, carla.Transform(), attach_to=self.vehicle)
self.actor_list.append(self.collision_sensor)
bp = bp_library.find('sensor.other.lane_detector')
self.invasion_sensor = world.try_spawn_actor(
bp, carla.Transform(), attach_to=self.vehicle)
self.actor_list.append(
self.invasion_sensor
) # 39 steps for first time 42 steps for reset
except Exception as e:
print("spawn fail, sad news", e)
def reset(self):
error = None
for _ in range(100):
try:
if len(live_carla_processes) == 0:
self.init_server()
self._restart() # bugggggggggg!!!!!!!!!!!!!!!!!!!!!!!!
obs = self._reset()
return obs
except Exception as e:
with open(
"/home/gu/error_log %s.txt" %
str(datetime.datetime.now()), "w") as f:
f.write('============Error====================, %s' %
str(e))
print("<<<<<<<<<<Error during reset in env>>>>>>>>>>")
cleanup()
self.init_server()
error = e
raise error
# @set_timeout(10)
def _reset(self):
# self._error_rest_test += 1
# if self._error_rest_test < 3:
# print(1/0)
# else:
# print("+++++++++++++++++++++++++++++++++++++++++++++++")
weak_self = weakref.ref(self)
# set invasion sensor
self.invasion_sensor.listen(
lambda event: self._parse_invasion(weak_self, event))
# set collision sensor
self.collision_sensor.listen(
lambda event: self._parse_collision(weak_self, event))
# set rgb camera sensor
self.camera_rgb1.listen(
lambda image: self._parse_image1(weak_self, image, cc.Raw, 'rgb'))
while len(self._image_rgb1) < 4:
print("resetting rgb")
time.sleep(0.001)
if ENV_CONFIG[
"image_mode"] == "encode": # stack gray depth segmentation
obs = np.concatenate([
self._image_rgb1[-1], self._image_rgb1[-2],
np.zeros([ENV_CONFIG['x_res'], ENV_CONFIG['y_res'], 1])
],
axis=2)
else:
obs = self._image_rgb1[-1]
t = self.vehicle.get_transform()
v = self.vehicle.get_velocity()
c = self.vehicle.get_control()
acceleration = self.vehicle.get_acceleration()
if len(self._history_invasion) > 0:
invasion = self._history_invasion[-1]
else:
invasion = []
self.planner()
distance = ((self._history_waypoint[-1].transform.location.x -
self.vehicle.get_location().x)**2 +
(self._history_waypoint[-1].transform.location.y -
self.vehicle.get_location().y)**2)**0.5
info = {
"speed":
math.sqrt(v.x**2 + v.y**2 + v.z**2), # m/s
"acceleration":
math.sqrt(acceleration.x**2 + acceleration.y**2 +
acceleration.z**2),
"location_x":
t.location.x,
"location_y":
t.location.y,
"Throttle":
c.throttle,
"Steer":
c.steer,
"Brake":
c.brake,
"command":
self.planner(),
"distance":
distance,
"lane_invasion":
invasion,
"traffic_light":
str(self.vehicle.get_traffic_light_state()
), # Red Yellow Green Off Unknown
"is_at_traffic_light":
self.vehicle.is_at_traffic_light(), # True False
"collision":
len(self._history_collision)
}
self._history_info.append(info)
self._obs_collect.append(obs[:, :, 0:3])
if len(self._obs_collect) > 32:
self._obs_collect.pop(0)
mask = self._compute_mask()
# define how many channel we want play with
if ENV_CONFIG["attention_mode"] == "soft":
obs[:, :,
0:ENV_CONFIG["attention_channel"]] = obs[:, :, 0:ENV_CONFIG[
"attention_channel"]] + mask
else:
obs[:, :,
0:ENV_CONFIG["attention_channel"]] = obs[:, :, 0:ENV_CONFIG[
"attention_channel"]] * mask
self._obs_collect.append(np.clip(obs, 0,
255)) # clip in case we want render
if len(self._obs_collect) > 32:
self._obs_collect.pop(0)
return self._obs_collect[-1]
@staticmethod
def _generate_point_list():
"""
generate the Cartesian coordinates for every pixel in the picture, because attention point is represented in
Cartesian coordinates(e.g. (-48, -48) (0, 0) (48, 48)) but the position of pixel is represented by index(e.g.
[95, 0] [47, 47] [0 95])
:return: Cartesian coordinates for pixels
"""
r = int(ENV_CONFIG["x_res"] / 2)
point_list = []
for i in range(r, -r, -1):
for j in range(-r, r, 1):
point_list.append((j, i))
return point_list
@staticmethod
def _compute_distance_transform(d,
action=np.zeros(ENV_CONFIG["action_dim"])):
"""compute the variance for attention mask when we adding noise
if we specify attention mode to soft we will use this function """
if ENV_CONFIG["action_dim"] == 5:
# in care our poor agent see nothing we set threshold equal to 5
# in other word if action[4] = 0 then action[4] will be set to 5
# action[4] belong to range(-1, 1) we project it to [0, 70]
r = 35 * (1 + action[4]) if 35 * (1 + action[4]) > 5 else 5
else:
r = 25
if ENV_CONFIG["attention_mode"] == "soft":
# d is the threshold of distance between attention point
# if the distance is greater then d we add noise on image
# the strength of noise is linear to distance
d = 0 if d < r else 2 * d
elif ENV_CONFIG["attention_mode"] == "hard":
# it behave like mask(i.e. 0 for totally dark)
d = 1 if d < r else (r / d)**2.5
# d = -24 + 2*d
return d
def _compute_mask(self, action=np.zeros(ENV_CONFIG["action_dim"])):
""""compute mask for attention"""
if ENV_CONFIG["action_dim"] == 4 or ENV_CONFIG["action_dim"] == 5:
mu_1 = int(ENV_CONFIG["x_res"] * action[2] * 0.5)
mu_2 = int(ENV_CONFIG["y_res"] * action[3] * 0.5)
elif ENV_CONFIG["action_dim"] == 2:
mu_1 = 0
mu_2 = 0
d_list = []
point_list = self._generate_point_list()
for p in point_list:
d = np.sqrt((mu_1 - p[0])**2 + (mu_2 - p[1])**2)
if ENV_CONFIG["attention_mode"] == "soft":
# self._d_collect.append(d)
p_mask = float(
self._compute_distance_transform(d, action) *
np.random.randn(1))
elif ENV_CONFIG["attention_mode"] == "hard":
p_mask = float(self._compute_distance_transform(d, action))
else: # if we want use raw rgb
p_mask = 1
d_list.append(p_mask)
mask = np.reshape(d_list, [ENV_CONFIG["x_res"], ENV_CONFIG["y_res"]])
return mask[:, :, np.newaxis]
@staticmethod
def _parse_image1(weak_self, image, cc, use):
"""convert BGRA to RGB"""
self = weak_self()
if not self:
return
def convert(cc):
image.convert(cc)
array = np.frombuffer(image.raw_data, dtype=np.dtype("uint8"))
array = np.reshape(array, (image.height, image.width, 4))
array = array[:, :, -2:-5:-1]
array = array.astype(np.float32)
return array
if use == 'rgb':
array = convert(cc)
self._image_rgb1.append(array)
if len(self._image_rgb1) > 32:
self._image_rgb1.pop(0)
@staticmethod
def _parse_image2(weak_self, image, cc, use):
"""convert BGRA to RGB"""
self = weak_self()
if not self:
return
def convert(cc):
image.convert(cc)
array = np.frombuffer(image.raw_data, dtype=np.dtype("uint8"))
array = np.reshape(array, (image.height, image.width, 4))
array = array[:, :, -2:-5:-1]
array = array.astype(np.float32)
return array
if use == 'rgb':
array = convert(cc)
self._image_rgb2.append(array)
if len(self._image_rgb2) > 32:
self._image_rgb2.pop(0)
@staticmethod
def _parse_collision(weak_self, event):
self = weak_self()
if not self:
return
impulse = event.normal_impulse
intensity = math.sqrt(impulse.x**2 + impulse.y**2 + impulse.z**2)
self._history_collision.append((event.frame_number, intensity))
if len(self._history_collision) > 32:
self._history_collision.pop(0)
@staticmethod
def _parse_invasion(weak_self, event):
self = weak_self()
if not self:
return
# print(str(event.crossed_lane_markings)) [carla.libcarla.LaneMarking.Solid]
text = [
'%r' % str(x).split()[-1] for x in set(event.crossed_lane_markings)
]
# S for Solid B for Broken
self._history_invasion.append(text[0][1])
if len(self._history_invasion) > 32:
self._history_invasion.pop(0)
def step(self, action):
try:
obs = self._step(action)
return obs
except Exception as e:
print("Error during step, terminating episode early")
print(e)
return self._obs_collect[-1], 0, True, self._history_info[-1]
# @set_timeout(10)
def _step(self, action):
self._global_step += 1
def compute_reward(info, prev_info):
reward = 0.0
reward += np.clip(info["speed"], 0, 15) / 3
reward += info['distance']
if info["collision"] == 1:
reward -= 70
elif 2 <= info["collision"] < 5:
reward -= info['speed'] * 2
elif info["collision"] > 5:
reward -= info['speed'] * 1
print(self._global_step, "current speed", info["speed"],
"collision", info['collision'])
new_invasion = list(
set(info["lane_invasion"]) - set(prev_info["lane_invasion"]))
if 'S' in new_invasion: # go across solid lane
reward -= info["speed"]
elif 'B' in new_invasion: # go across broken lane
reward -= 0.4 * info["speed"]
return reward
throttle = float(np.clip(action[0], 0, 1))
brake = float(np.abs(np.clip(action[0], -1, 0)))
steer = float(np.clip(action[1], -1, 1))
distance_before_act = (
(self._history_waypoint[-1].transform.location.x -
self.vehicle.get_location().x)**2 +
(self._history_waypoint[-1].transform.location.y -
self.vehicle.get_location().y)**2)**0.5
self.vehicle.apply_control(
carla.VehicleControl(throttle=throttle, brake=brake, steer=steer))
# sleep a little waiting for the responding from simulator
if ENV_CONFIG[
"attention_mode"] == "None": # or ENV_CONFIG["attention_mode"] == "hard":
time.sleep(0.04)
t = self.vehicle.get_transform()
v = self.vehicle.get_velocity()
c = self.vehicle.get_control()
acceleration = self.vehicle.get_acceleration()
if len(self._history_invasion) > 0:
invasion = self._history_invasion[-1]
else:
invasion = []
command = self.planner()
distance_after_act = (
(self._history_waypoint[-2].transform.location.x -
self.vehicle.get_location().x)**2 +
(self._history_waypoint[-2].transform.location.y -
self.vehicle.get_location().y)**2)**0.5
info = {
"speed":
math.sqrt(v.x**2 + v.y**2 + v.z**2), # m/s
"acceleration":
math.sqrt(acceleration.x**2 + acceleration.y**2 +
acceleration.z**2),
"location_x":
t.location.x,
"location_y":
t.location.y,
"Throttle":
c.throttle,
"Steer":
c.steer,
"Brake":
c.brake,
"command":
command,
"distance":
distance_before_act - distance_after_act, # distance to waypoint
"lane_invasion":
invasion,
"traffic_light":
str(self.vehicle.get_traffic_light_state()
), # Red Yellow Green Off Unknown
"is_at_traffic_light":
self.vehicle.is_at_traffic_light(), # True False
"collision":
len(self._history_collision)
}
self._history_info.append(info)
reward = compute_reward(self._history_info[-1], self._history_info[-2])
# print(self._history_info[-1]["speed"], self._history_info[-1]["collision"])
# early stop
done = False
if ENV_CONFIG["early_stop"]:
if len(self._history_collision) > 0 and self._global_step > 60:
# print("collisin length", len(self._history_collision))
done = True
# self.destroy_actor()
# elif reward < -100:
# done = True
if ENV_CONFIG[
"image_mode"] == "encode": # stack gray depth segmentation
obs = np.concatenate([
self._image_rgb1[-1], self._image_rgb1[-2],
self.encode_measurement(info)
],
axis=2)
else:
obs = self._image_rgb1[-1]
mask = self._compute_mask(action)
if ENV_CONFIG["attention_mode"] == "soft":
obs[:, :,
0:ENV_CONFIG["attention_channel"]] = obs[:, :, 0:ENV_CONFIG[
"attention_channel"]] + mask
else:
obs[:, :,
0:ENV_CONFIG["attention_channel"]] = obs[:, :, 0:ENV_CONFIG[
"attention_channel"]] * mask
self._obs_collect.append(np.clip(obs, 0,
255)) # clip in case we want render
if len(self._obs_collect) > 32:
self._obs_collect.pop(0)
return self._obs_collect[-1], reward, done, self._history_info[-1]
def render(self):
display = pygame.display.set_mode(
(ENV_CONFIG["x_res"], ENV_CONFIG["y_res"]),
pygame.HWSURFACE | pygame.DOUBLEBUF)
# surface = pygame.surfarray.make_surface(env._image_rgb1[-1].swapaxes(0, 1))
surface = pygame.surfarray.make_surface(
env._obs_collect[-1][:, :, 0:3].swapaxes(0, 1))
display.blit(surface, (0, 0))
time.sleep(0.01)
pygame.display.flip()
def planner(self):
waypoint = self.map.get_waypoint(self.vehicle.get_location())
waypoint = random.choice(waypoint.next(12.0))
self._history_waypoint.append(waypoint)
yaw = waypoint.transform.rotation.yaw
if yaw > -90 or yaw < 60:
command = "turn_right"
elif yaw > 60 and yaw < 120:
command = "lane_keep"
elif yaw > 120 or yaw < -90:
command = "turn_left"
return self.command[command]
@staticmethod
def encode_measurement(py_measurements):
"""encode measurements into another channel"""
feature_map = np.zeros([4, 4])
feature_map[0, :] = (py_measurements["command"]) * 60.0
feature_map[1, :] = (py_measurements["speed"]) * 4.0
feature_map[2, :] = (py_measurements["command"]) * 60.0
feature_map[3, :] = (py_measurements["Steer"] + 1) * 120.0
stack = int(ENV_CONFIG["x_res"] / 4)
feature_map = np.tile(feature_map, (stack, stack))
feature_map = feature_map.astype(np.float32)
return feature_map[:, :, np.newaxis]
# load the scenario
def load_scenario(self):
self.manager = ScenarioManager(self.world, False)
self.manager.load_scenario(self.scenario)
# run the scenario
def run_scenario(self):
self.manager.run_scenario()
# analyse the result of env in the scenario
def analyse_scenario(self):
for config in self.scenario_configurations:
current_time = str(datetime.now().strftime('%Y-%m-%d-%H-%M-%S'))
junit_filename = None
if False:
junit_filename = config.name + current_time + ".xml"
filename = None
if False:
filename = config.name + current_time + ".txt"
if not self.manager.analyze_scenario(False, filename,
junit_filename):
print(
"==================================================Success!==================================================\n\n"
)
self.score = 'success'
self.final_score(self.score)
time.sleep(1)
else:
print(
"==================================================Failure!==================================================\n\n"
)
self.score = 'failure'
self.final_score(self.score)
time.sleep(1)
# input the final score
def final_score(self, score):
self.total_score = []
self.total_score.append(self.score)
return self.total_score
# write the result into local txt
def write_result(self, times):
current_time = str(datetime.now().strftime('%Y-%m-%d-%H-%M-%S'))
filename = self.scenario_name + '_training_result' + ".txt"
if times == 1:
with open(filename, "a+") as fd:
fd.write('========== Start tarning ! ' + current_time +
'==========\n')
fd.write(str(times) + ': ' + str(self.total_score) + '\n')
else:
with open(filename, "a+") as fd:
fd.write(str(times) + ': ' + str(self.total_score) + '\n')
class ScenarioRunner(object):
"""
This is the core scenario runner module. It is responsible for
running (and repeating) a single scenario or a list of scenarios.
Usage:
scenario_runner = ScenarioRunner(args)
scenario_runner.run()
del scenario_runner
"""
ego_vehicles = []
# Tunable parameters
client_timeout = 10.0 # in seconds
wait_for_world = 20.0 # in seconds
frame_rate = 10.0 # in Hz
# CARLA world and scenario handlers
world = None
manager = None
additional_scenario_module = None
agent_instance = None
module_agent = None
def __init__(self, args):
"""
Setup CARLA client and world
Setup ScenarioManager
"""
self._args = args
if args.timeout:
self.client_timeout = float(args.timeout)
# First of all, we need to create the client that will send the requests
# to the simulator. Here we'll assume the simulator is accepting
# requests in the localhost at port 2000.
self.client = carla.Client(args.host, int(args.port))
self.client.set_timeout(self.client_timeout)
self.traffic_manager = self.client.get_trafficmanager(int(self._args.trafficManagerPort))
dist = pkg_resources.get_distribution("carla")
if LooseVersion(dist.version) < LooseVersion('0.9.10'):
raise ImportError("CARLA version 0.9.10 or newer required. CARLA version found: {}".format(dist))
# Load agent if requested via command line args
# If something goes wrong an exception will be thrown by importlib (ok here)
if self._args.agent is not None:
module_name = os.path.basename(args.agent).split('.')[0]
sys.path.insert(0, os.path.dirname(args.agent))
self.module_agent = importlib.import_module(module_name)
# Create the ScenarioManager
self.manager = ScenarioManager(self._args.debug, self._args.sync, self._args.timeout)
# Create signal handler for SIGINT
self._shutdown_requested = False
if sys.platform != 'win32':
signal.signal(signal.SIGHUP, self._signal_handler)
signal.signal(signal.SIGINT, self._signal_handler)
signal.signal(signal.SIGTERM, self._signal_handler)
self._start_wall_time = datetime.now()
def destroy(self):
"""
Cleanup and delete actors, ScenarioManager and CARLA world
"""
self._cleanup()
if self.manager is not None:
del self.manager
if self.world is not None:
del self.world
if self.client is not None:
del self.client
def _signal_handler(self, signum, frame):
"""
Terminate scenario ticking when receiving a signal interrupt
"""
self._shutdown_requested = True
if self.manager:
self.manager.stop_scenario()
self._cleanup()
if not self.manager.get_running_status():
raise RuntimeError("Timeout occured during scenario execution")
def _get_scenario_class_or_fail(self, scenario):
"""
Get scenario class by scenario name
If scenario is not supported or not found, exit script
"""
# Path of all scenario at "srunner/scenarios" folder + the path of the additional scenario argument
scenarios_list = glob.glob("{}/srunner/scenarios/*.py".format(os.getenv('SCENARIO_RUNNER_ROOT', "./")))
scenarios_list.append(self._args.additionalScenario)
for scenario_file in scenarios_list:
# Get their module
module_name = os.path.basename(scenario_file).split('.')[0]
sys.path.insert(0, os.path.dirname(scenario_file))
scenario_module = importlib.import_module(module_name)
# And their members of type class
for member in inspect.getmembers(scenario_module, inspect.isclass):
if scenario in member:
return member[1]
# Remove unused Python paths
sys.path.pop(0)
print("Scenario '{}' not supported ... Exiting".format(scenario))
sys.exit(-1)
def _cleanup(self):
"""
Remove and destroy all actors
"""
# Simulation still running and in synchronous mode?
if self.world is not None and self._args.sync:
try:
# Reset to asynchronous mode
settings = self.world.get_settings()
settings.synchronous_mode = False
settings.fixed_delta_seconds = None
self.world.apply_settings(settings)
except RuntimeError:
sys.exit(-1)
self.manager.cleanup()
CarlaDataProvider.cleanup()
for i, _ in enumerate(self.ego_vehicles):
if self.ego_vehicles[i]:
if not self._args.waitForEgo:
print("Destroying ego vehicle {}".format(self.ego_vehicles[i].id))
self.ego_vehicles[i].destroy()
self.ego_vehicles[i] = None
self.ego_vehicles = []
if self.agent_instance:
self.agent_instance.destroy()
self.agent_instance = None
def _prepare_ego_vehicles(self, ego_vehicles):
"""
Spawn or update the ego vehicles
"""
if not self._args.waitForEgo:
for vehicle in ego_vehicles:
self.ego_vehicles.append(CarlaDataProvider.request_new_actor(vehicle.model,
vehicle.transform,
vehicle.rolename,
color=vehicle.color,
actor_category=vehicle.category))
else:
ego_vehicle_missing = True
while ego_vehicle_missing:
self.ego_vehicles = []
ego_vehicle_missing = False
for ego_vehicle in ego_vehicles:
ego_vehicle_found = False
carla_vehicles = CarlaDataProvider.get_world().get_actors().filter('vehicle.*')
for carla_vehicle in carla_vehicles:
if carla_vehicle.attributes['role_name'] == ego_vehicle.rolename:
ego_vehicle_found = True
self.ego_vehicles.append(carla_vehicle)
break
if not ego_vehicle_found:
ego_vehicle_missing = True
break
for i, _ in enumerate(self.ego_vehicles):
self.ego_vehicles[i].set_transform(ego_vehicles[i].transform)
CarlaDataProvider.register_actor(self.ego_vehicles[i])
# sync state
if CarlaDataProvider.is_sync_mode():
self.world.tick()
else:
self.world.wait_for_tick()
def _analyze_scenario(self, config):
"""
Provide feedback about success/failure of a scenario
"""
# Create the filename
current_time = str(datetime.now().strftime('%Y-%m-%d-%H-%M-%S'))
junit_filename = None
json_filename = None
config_name = config.name
if self._args.outputDir != '':
config_name = os.path.join(self._args.outputDir, config_name)
if self._args.junit:
junit_filename = config_name + current_time + ".xml"
if self._args.json:
json_filename = config_name + current_time + ".json"
filename = None
if self._args.file:
filename = config_name + current_time + ".txt"
if not self.manager.analyze_scenario(self._args.output, filename, junit_filename, json_filename):
print("All scenario tests were passed successfully!")
else:
print("Not all scenario tests were successful")
if not (self._args.output or filename or junit_filename):
print("Please run with --output for further information")
def _record_criteria(self, criteria, name):
"""
Filter the JSON serializable attributes of the criterias and
dumps them into a file. This will be used by the metrics manager,
in case the user wants specific information about the criterias.
"""
file_name = name[:-4] + ".json"
# Filter the attributes that aren't JSON serializable
with open('temp.json', 'w') as fp:
criteria_dict = {}
for criterion in criteria:
criterion_dict = criterion.__dict__
criteria_dict[criterion.name] = {}
for key in criterion_dict:
if key != "name":
try:
key_dict = {key: criterion_dict[key]}
json.dump(key_dict, fp, sort_keys=False, indent=4)
criteria_dict[criterion.name].update(key_dict)
except TypeError:
pass
os.remove('temp.json')
# Save the criteria dictionary into a .json file
with open(file_name, 'w') as fp:
json.dump(criteria_dict, fp, sort_keys=False, indent=4)
def _load_and_wait_for_world(self, town, ego_vehicles=None):
"""
Load a new CARLA world and provide data to CarlaDataProvider
"""
if self._args.reloadWorld:
self.world = self.client.load_world(town)
else:
# if the world should not be reloaded, wait at least until all ego vehicles are ready
ego_vehicle_found = False
if self._args.waitForEgo:
while not ego_vehicle_found and not self._shutdown_requested:
vehicles = self.client.get_world().get_actors().filter('vehicle.*')
for ego_vehicle in ego_vehicles:
ego_vehicle_found = False
for vehicle in vehicles:
if vehicle.attributes['role_name'] == ego_vehicle.rolename:
ego_vehicle_found = True
break
if not ego_vehicle_found:
print("Not all ego vehicles ready. Waiting ... ")
time.sleep(1)
break
self.world = self.client.get_world()
if self._args.sync:
settings = self.world.get_settings()
settings.synchronous_mode = True
settings.fixed_delta_seconds = 1.0 / self.frame_rate
self.world.apply_settings(settings)
self.traffic_manager.set_synchronous_mode(True)
self.traffic_manager.set_random_device_seed(int(self._args.trafficManagerSeed))
CarlaDataProvider.set_client(self.client)
CarlaDataProvider.set_world(self.world)
CarlaDataProvider.set_traffic_manager_port(int(self._args.trafficManagerPort))
# Wait for the world to be ready
if CarlaDataProvider.is_sync_mode():
self.world.tick()
else:
self.world.wait_for_tick()
if CarlaDataProvider.get_map().name != town and CarlaDataProvider.get_map().name != "OpenDriveMap":
print("The CARLA server uses the wrong map: {}".format(CarlaDataProvider.get_map().name))
print("This scenario requires to use map: {}".format(town))
return False
return True
def _load_and_run_scenario(self, config):
"""
Load and run the scenario given by config
"""
result = False
if not self._load_and_wait_for_world(config.town, config.ego_vehicles):
self._cleanup()
return False
if self._args.agent:
agent_class_name = self.module_agent.__name__.title().replace('_', '')
try:
self.agent_instance = getattr(self.module_agent, agent_class_name)(self._args.agentConfig)
config.agent = self.agent_instance
except Exception as e: # pylint: disable=broad-except
traceback.print_exc()
print("Could not setup required agent due to {}".format(e))
self._cleanup()
return False
# Prepare scenario
print("Preparing scenario: " + config.name)
try:
self._prepare_ego_vehicles(config.ego_vehicles)
if self._args.openscenario:
scenario = OpenScenario(world=self.world,
ego_vehicles=self.ego_vehicles,
config=config,
config_file=self._args.openscenario,
timeout=100000)
elif self._args.route:
scenario = RouteScenario(world=self.world,
config=config,
debug_mode=self._args.debug)
else:
scenario_class = self._get_scenario_class_or_fail(config.type)
scenario = scenario_class(self.world,
self.ego_vehicles,
config,
self._args.randomize,
self._args.debug)
except Exception as exception: # pylint: disable=broad-except
print("The scenario cannot be loaded")
traceback.print_exc()
print(exception)
self._cleanup()
return False
try:
if self._args.record:
recorder_name = "{}/{}/{}.log".format(
os.getenv('SCENARIO_RUNNER_ROOT', "./"), self._args.record, config.name)
self.client.start_recorder(recorder_name, True)
# Load scenario and run it
self.manager.load_scenario(scenario, self.agent_instance)
self.manager.run_scenario()
# Provide outputs if required
self._analyze_scenario(config)
# Remove all actors, stop the recorder and save all criterias (if needed)
scenario.remove_all_actors()
if self._args.record:
self.client.stop_recorder()
self._record_criteria(self.manager.scenario.get_criteria(), recorder_name)
result = True
except Exception as e: # pylint: disable=broad-except
traceback.print_exc()
print(e)
result = False
self._cleanup()
return result
def _run_scenarios(self):
"""
Run conventional scenarios (e.g. implemented using the Python API of ScenarioRunner)
"""
result = False
# Load the scenario configurations provided in the config file
scenario_configurations = ScenarioConfigurationParser.parse_scenario_configuration(
self._args.scenario,
self._args.configFile)
if not scenario_configurations:
print("Configuration for scenario {} cannot be found!".format(self._args.scenario))
return result
# Execute each configuration
for config in scenario_configurations:
for _ in range(self._args.repetitions):
result = self._load_and_run_scenario(config)
self._cleanup()
return result
def _run_route(self):
"""
Run the route scenario
"""
result = False
if self._args.route:
routes = self._args.route[0]
scenario_file = self._args.route[1]
single_route = None
if len(self._args.route) > 2:
single_route = self._args.route[2]
# retrieve routes
route_configurations = RouteParser.parse_routes_file(routes, scenario_file, single_route)
for config in route_configurations:
for _ in range(self._args.repetitions):
result = self._load_and_run_scenario(config)
self._cleanup()
return result
def _run_openscenario(self):
"""
Run a scenario based on OpenSCENARIO
"""
# Load the scenario configurations provided in the config file
if not os.path.isfile(self._args.openscenario):
print("File does not exist")
self._cleanup()
return False
config = OpenScenarioConfiguration(self._args.openscenario, self.client)
result = self._load_and_run_scenario(config)
self._cleanup()
return result
def run(self):
"""
Run all scenarios according to provided commandline args
"""
result = True
if self._args.openscenario:
result = self._run_openscenario()
elif self._args.route:
result = self._run_route()
else:
result = self._run_scenarios()
print("No more scenarios .... Exiting")
return result
class ScenarioRunner(object):
"""
This is the core scenario runner module. It is responsible for
running (and repeating) a single scenario or a list of scenarios.
Usage:
scenario_runner = ScenarioRunner(args)
scenario_runner.run()
del scenario_runner
"""
ego_vehicles = []
# Tunable parameters
client_timeout = 10.0 # in seconds
wait_for_world = 20.0 # in seconds
frame_rate = 20.0 # in Hz
# CARLA world and scenario handlers
world = None
manager = None
additional_scenario_module = None
agent_instance = None
module_agent = None
def __init__(self, args):
"""
Setup CARLA client and world
Setup ScenarioManager
"""
self._args = args
if args.timeout:
self.client_timeout = float(args.timeout)
# First of all, we need to create the client that will send the requests
# to the simulator. Here we'll assume the simulator is accepting
# requests in the localhost at port 2000.
self.client = carla.Client(args.host, int(args.port))
self.client.set_timeout(self.client_timeout)
dist = pkg_resources.get_distribution("carla")
if LooseVersion(dist.version) < LooseVersion('0.9.8'):
raise ImportError(
"CARLA version 0.9.8 or newer required. CARLA version found: {}"
.format(dist))
# Load additional scenario definitions, if there are any
# If something goes wrong an exception will be thrown by importlib (ok here)
if self._args.additionalScenario != '':
module_name = os.path.basename(
args.additionalScenario).split('.')[0]
sys.path.insert(0, os.path.dirname(args.additionalScenario))
self.additional_scenario_module = importlib.import_module(
module_name)
# Load agent if requested via command line args
# If something goes wrong an exception will be thrown by importlib (ok here)
if self._args.agent is not None:
module_name = os.path.basename(args.agent).split('.')[0]
sys.path.insert(0, os.path.dirname(args.agent))
self.module_agent = importlib.import_module(module_name)
# Create the ScenarioManager
self.manager = ScenarioManager(self._args.debug, self._args.challenge,
self._args.timeout)
# Create signal handler for SIGINT
self._shutdown_requested = False
signal.signal(signal.SIGHUP, self._signal_handler)
signal.signal(signal.SIGINT, self._signal_handler)
signal.signal(signal.SIGTERM, self._signal_handler)
self._start_wall_time = datetime.now()
def destroy(self):
"""
Cleanup and delete actors, ScenarioManager and CARLA world
"""
self._cleanup()
if self.manager is not None:
del self.manager
if self.world is not None:
del self.world
if self.client is not None:
del self.client
def _signal_handler(self, signum, frame):
"""
Terminate scenario ticking when receiving a signal interrupt
"""
self._shutdown_requested = True
if self.manager:
self.manager.stop_scenario()
self._cleanup()
if not self.manager.get_running_status():
raise RuntimeError("Timeout occured during scenario execution")
def _within_available_time(self):
"""
Check if the elapsed runtime is within the remaining user time budget
Only relevant when running in challenge mode
"""
current_time = datetime.now()
elapsed_seconds = (current_time - self._start_wall_time).seconds
return elapsed_seconds < os.getenv('CHALLENGE_TIME_AVAILABLE',
'1080000')
def _get_scenario_class_or_fail(self, scenario):
"""
Get scenario class by scenario name
If scenario is not supported or not found, exit script
"""
if scenario in globals():
return globals()[scenario]
for member in inspect.getmembers(self.additional_scenario_module):
if scenario in member and inspect.isclass(member[1]):
return member[1]
print("Scenario '{}' not supported ... Exiting".format(scenario))
sys.exit(-1)
def _cleanup(self):
"""
Remove and destroy all actors
"""
if self.world is not None and self.manager is not None \
and self._args.agent and self.manager.get_running_status():
# Reset to asynchronous mode
settings = self.world.get_settings()
settings.synchronous_mode = False
settings.fixed_delta_seconds = None
self.world.apply_settings(settings)
self.client.stop_recorder()
self.manager.cleanup()
CarlaDataProvider.cleanup()
CarlaActorPool.cleanup()
for i, _ in enumerate(self.ego_vehicles):
if self.ego_vehicles[i]:
if not self._args.waitForEgo:
print("Destroying ego vehicle {}".format(
self.ego_vehicles[i].id))
self.ego_vehicles[i].destroy()
self.ego_vehicles[i] = None
self.ego_vehicles = []
if self.agent_instance:
self.agent_instance.destroy()
self.agent_instance = None
def _prepare_ego_vehicles(self, ego_vehicles):
"""
Spawn or update the ego vehicles
"""
if not self._args.waitForEgo:
for vehicle in ego_vehicles:
self.ego_vehicles.append(
CarlaActorPool.setup_actor(
vehicle.model,
vehicle.transform,
vehicle.rolename,
True,
color=vehicle.color,
actor_category=vehicle.category))
else:
ego_vehicle_missing = True
while ego_vehicle_missing:
self.ego_vehicles = []
ego_vehicle_missing = False
for ego_vehicle in ego_vehicles:
ego_vehicle_found = False
carla_vehicles = CarlaDataProvider.get_world().get_actors(
).filter('vehicle.*')
for carla_vehicle in carla_vehicles:
if carla_vehicle.attributes[
'role_name'] == ego_vehicle.rolename:
ego_vehicle_found = True
self.ego_vehicles.append(carla_vehicle)
break
if not ego_vehicle_found:
ego_vehicle_missing = True
break
for i, _ in enumerate(self.ego_vehicles):
self.ego_vehicles[i].set_transform(ego_vehicles[i].transform)
# sync state
CarlaDataProvider.perform_carla_tick()
def _analyze_scenario(self, config):
"""
Provide feedback about success/failure of a scenario
"""
current_time = str(datetime.now().strftime('%Y-%m-%d-%H-%M-%S'))
junit_filename = None
config_name = config.name
if self._args.outputDir != '':
config_name = os.path.join(self._args.outputDir, config_name)
if self._args.junit:
junit_filename = config_name + current_time + ".xml"
filename = None
if self._args.file:
filename = config_name + current_time + ".txt"
if not self.manager.analyze_scenario(self._args.output, filename,
junit_filename):
print("All scenario tests were passed successfully!")
else:
print("Not all scenario tests were successful")
if not (self._args.output or filename or junit_filename):
print("Please run with --output for further information")
def _load_and_wait_for_world(self, town, ego_vehicles=None):
"""
Load a new CARLA world and provide data to CarlaActorPool and CarlaDataProvider
"""
if self._args.reloadWorld:
self.world = self.client.load_world(town)
else:
# if the world should not be reloaded, wait at least until all ego vehicles are ready
ego_vehicle_found = False
if self._args.waitForEgo:
while not ego_vehicle_found and not self._shutdown_requested:
vehicles = self.client.get_world().get_actors().filter(
'vehicle.*')
for ego_vehicle in ego_vehicles:
ego_vehicle_found = False
for vehicle in vehicles:
if vehicle.attributes[
'role_name'] == ego_vehicle.rolename:
ego_vehicle_found = True
break
if not ego_vehicle_found:
print("Not all ego vehicles ready. Waiting ... ")
time.sleep(1)
break
self.world = self.client.get_world()
CarlaActorPool.set_client(self.client)
CarlaActorPool.set_world(self.world)
CarlaDataProvider.set_world(self.world)
settings = self.world.get_settings()
settings.fixed_delta_seconds = 1.0 / self.frame_rate
self.world.apply_settings(settings)
if self._args.agent:
settings = self.world.get_settings()
settings.synchronous_mode = True
self.world.apply_settings(settings)
# Wait for the world to be ready
if self.world.get_settings().synchronous_mode:
CarlaDataProvider.perform_carla_tick()
else:
self.world.wait_for_tick()
if CarlaDataProvider.get_map(
).name != town and CarlaDataProvider.get_map().name != "OpenDriveMap":
print("The CARLA server uses the wrong map: {}".format(
CarlaDataProvider.get_map().name))
print("This scenario requires to use map: {}".format(town))
return False
return True
def _load_and_run_scenario(self, config):
"""
Load and run the scenario given by config
"""
result = False
if not self._load_and_wait_for_world(config.town, config.ego_vehicles):
self._cleanup()
return False
if self._args.agent:
agent_class_name = self.module_agent.__name__.title().replace(
'_', '')
try:
self.agent_instance = getattr(self.module_agent,
agent_class_name)(
self._args.agentConfig)
config.agent = self.agent_instance
except Exception as e: # pylint: disable=broad-except
traceback.print_exc()
print("Could not setup required agent due to {}".format(e))
self._cleanup()
return False
# Prepare scenario
print("Preparing scenario: " + config.name)
try:
self._prepare_ego_vehicles(config.ego_vehicles)
if self._args.openscenario:
scenario = OpenScenario(world=self.world,
ego_vehicles=self.ego_vehicles,
config=config,
config_file=self._args.openscenario,
timeout=100000)
elif self._args.route:
scenario = RouteScenario(world=self.world,
config=config,
debug_mode=self._args.debug)
else:
scenario_class = self._get_scenario_class_or_fail(config.type)
scenario = scenario_class(self.world, self.ego_vehicles,
config, self._args.randomize,
self._args.debug)
except Exception as exception: # pylint: disable=broad-except
print("The scenario cannot be loaded")
traceback.print_exc()
print(exception)
self._cleanup()
return False
# Set the appropriate weather conditions
self.world.set_weather(config.weather)
# Set the appropriate road friction
if config.friction is not None:
friction_bp = self.world.get_blueprint_library().find(
'static.trigger.friction')
extent = carla.Location(1000000.0, 1000000.0, 1000000.0)
friction_bp.set_attribute('friction', str(config.friction))
friction_bp.set_attribute('extent_x', str(extent.x))
friction_bp.set_attribute('extent_y', str(extent.y))
friction_bp.set_attribute('extent_z', str(extent.z))
# Spawn Trigger Friction
transform = carla.Transform()
transform.location = carla.Location(-10000.0, -10000.0, 0.0)
self.world.spawn_actor(friction_bp, transform)
try:
# Load scenario and run it
if self._args.record:
self.client.start_recorder("{}/{}.log".format(
os.getenv('ROOT_SCENARIO_RUNNER', "./"), config.name))
self.manager.load_scenario(scenario, self.agent_instance)
self.manager.run_scenario()
# Provide outputs if required
self._analyze_scenario(config)
# Remove all actors
scenario.remove_all_actors()
result = True
except SensorConfigurationInvalid as e:
self._cleanup()
ChallengeStatisticsManager.record_fatal_error(e)
sys.exit(-1)
except Exception as e: # pylint: disable=broad-except
traceback.print_exc()
if self._args.challenge:
ChallengeStatisticsManager.set_error_message(
traceback.format_exc())
print(e)
result = False
self._cleanup()
return result
def _run_scenarios(self):
"""
Run conventional scenarios (e.g. implemented using the Python API of ScenarioRunner)
"""
result = False
# Setup and run the scenarios for repetition times
for _ in range(int(self._args.repetitions)):
# Load the scenario configurations provided in the config file
scenario_configurations = None
scenario_config_file = ScenarioConfigurationParser.find_scenario_config(
self._args.scenario, self._args.configFile)
if scenario_config_file is None:
print("Configuration for scenario {} cannot be found!".format(
self._args.scenario))
continue
scenario_configurations = ScenarioConfigurationParser.parse_scenario_configuration(
scenario_config_file, self._args.scenario)
# Execute each configuration
for config in scenario_configurations:
result = self._load_and_run_scenario(config)
self._cleanup()
return result
def _run_challenge(self):
"""
Run the challenge mode
"""
result = False
phase_codename = os.getenv('CHALLENGE_PHASE_CODENAME', 'dev_track_3')
phase = phase_codename.split("_")[0]
repetitions = self._args.repetitions
if self._args.challenge:
weather_profiles = CarlaDataProvider.find_weather_presets()
scenario_runner_root = os.getenv('ROOT_SCENARIO_RUNNER', "./")
if phase == 'dev':
routes = '{}/srunner/challenge/routes_devtest.xml'.format(
scenario_runner_root)
repetitions = 1
elif phase == 'validation':
routes = '{}/srunner/challenge/routes_testprep.xml'.format(
scenario_runner_root)
repetitions = 3
elif phase == 'test':
routes = '{}/srunner/challenge/routes_testchallenge.xml'.format(
scenario_runner_root)
repetitions = 3
else:
# debug mode
routes = '{}/srunner/challenge/routes_debug.xml'.format(
scenario_runner_root)
repetitions = 1
if self._args.route:
routes = self._args.route[0]
scenario_file = self._args.route[1]
single_route = None
if len(self._args.route) > 2:
single_route = self._args.route[2]
# retrieve routes
route_descriptions_list = RouteParser.parse_routes_file(
routes, single_route)
# find and filter potential scenarios for each of the evaluated routes
# For each of the routes and corresponding possible scenarios to be evaluated.
if self._args.challenge:
n_routes = len(route_descriptions_list) * repetitions
ChallengeStatisticsManager.set_number_of_scenarios(n_routes)
for _, route_description in enumerate(route_descriptions_list):
for repetition in range(repetitions):
if self._args.challenge and not self._within_available_time():
error_message = 'Not enough simulation time available to continue'
print(error_message)
ChallengeStatisticsManager.record_fatal_error(
error_message)
self._cleanup()
return False
config = RouteScenarioConfiguration(route_description,
scenario_file)
if self._args.challenge:
profile = weather_profiles[repetition %
len(weather_profiles)]
config.weather = profile[0]
config.weather.sun_azimuth_angle = -1
config.weather.sun_altitude_angle = -1
result = self._load_and_run_scenario(config)
self._cleanup()
return result
def _run_openscenario(self):
"""
Run a scenario based on OpenSCENARIO
"""
# Load the scenario configurations provided in the config file
if not os.path.isfile(self._args.openscenario):
print("File does not exist")
self._cleanup()
return False
config = OpenScenarioConfiguration(self._args.openscenario,
self.client)
result = self._load_and_run_scenario(config)
self._cleanup()
return result
def run(self):
"""
Run all scenarios according to provided commandline args
"""
result = True
if self._args.openscenario:
result = self._run_openscenario()
elif self._args.route or self._args.challenge:
result = self._run_challenge()
else:
result = self._run_scenarios()
print("No more scenarios .... Exiting")
return result
class ScenarioRunner(object):
"""
This is the core scenario runner module. It is responsible for
running (and repeating) a single scenario or a list of scenarios.
Usage:
scenario_runner = ScenarioRunner(args)
scenario_runner.run(args)
del scenario_runner
"""
ego_vehicle = None
actors = []
# Tunable parameters
client_timeout = 10.0 # in seconds
wait_for_world = 10.0 # in seconds
# CARLA world and scenario handlers
world = None
manager = None
def __init__(self, args):
"""
Setup CARLA client and world
Setup ScenarioManager
"""
# First of all, we need to create the client that will send the requests
# to the simulator. Here we'll assume the simulator is accepting
# requests in the localhost at port 2000.
client = carla.Client(args.host, int(args.port))
client.set_timeout(self.client_timeout)
# Once we have a client we can retrieve the world that is currently
# running.
self.world = client.get_world()
# Wait for the world to be ready
self.world.wait_for_tick(self.wait_for_world)
# Create scenario manager
self.manager = ScenarioManager(self.world, args.debug)
def __del__(self):
"""
Cleanup and delete actors, ScenarioManager and CARLA world
"""
self.cleanup(True)
if self.manager is not None:
del self.manager
if self.world is not None:
del self.world
@staticmethod
def get_scenario_class_or_fail(scenario):
"""
Get scenario class by scenario name
If scenario is not supported or not found, exit script
"""
for scenarios in SCENARIOS.values():
if scenario in scenarios:
if scenario in globals():
return globals()[scenario]
print("Scenario '{}' not supported ... Exiting".format(scenario))
sys.exit(-1)
def cleanup(self, ego=False):
"""
Remove and destroy all actors
"""
# We need enumerate here, otherwise the actors are not properly removed
for i, _ in enumerate(self.actors):
if self.actors[i] is not None:
self.actors[i].destroy()
self.actors[i] = None
self.actors = []
if ego and self.ego_vehicle is not None:
self.ego_vehicle.destroy()
self.ego_vehicle = None
def setup_vehicle(self, model, spawn_point, hero=False):
"""
Function to setup the most relevant vehicle parameters,
incl. spawn point and vehicle model.
"""
blueprint_library = self.world.get_blueprint_library()
# Get vehicle by model
blueprint = random.choice(blueprint_library.filter(model))
if hero:
blueprint.set_attribute('role_name', 'hero')
else:
blueprint.set_attribute('role_name', 'scenario')
vehicle = self.world.try_spawn_actor(blueprint, spawn_point)
if vehicle is None:
raise Exception(
"Error: Unable to spawn vehicle {} at {}".format(model, spawn_point))
else:
# Let's deactivate the autopilot of the vehicle
vehicle.set_autopilot(False)
return vehicle
def prepare_actors(self, config):
"""
Spawn or update all scenario actors according to
their parameters provided in config
"""
# If ego_vehicle already exists, just update location
# Otherwise spawn ego vehicle
if self.ego_vehicle is None:
self.ego_vehicle = self.setup_vehicle(config.ego_vehicle.model, config.ego_vehicle.transform, True)
else:
self.ego_vehicle.set_transform(config.ego_vehicle.transform)
# spawn all other actors
for actor in config.other_actors:
new_actor = self.setup_vehicle(actor.model, actor.transform)
self.actors.append(new_actor)
def analyze_scenario(self, args, config):
"""
Provide feedback about success/failure of a scenario
"""
current_time = str(datetime.now().strftime('%Y-%m-%d-%H-%M-%S'))
junit_filename = None
if args.junit:
junit_filename = config.name + current_time + ".xml"
filename = None
if args.file:
filename = config.name + current_time + ".txt"
if not self.manager.analyze_scenario(args.output, filename, junit_filename):
print("Success!")
else:
print("Failure!")
def run(self, args):
"""
Run all scenarios according to provided commandline args
"""
# Setup and run the scenarios for repetition times
for _ in range(int(args.repetitions)):
# Load the scenario configurations provided in the config file
scenario_configurations = None
if args.scenario.startswith("group:"):
scenario_configurations = parse_scenario_configuration(args.scenario, args.scenario)
else:
scenario_config_file = find_scenario_config(args.scenario)
if scenario_config_file is None:
print("Configuration for scenario {} cannot be found!".format(args.scenario))
continue
scenario_configurations = parse_scenario_configuration(scenario_config_file, args.scenario)
# Execute each configuration
for config in scenario_configurations:
# Prepare scenario
print("Preparing scenario: " + config.name)
scenario_class = ScenarioRunner.get_scenario_class_or_fail(config.type)
try:
self.prepare_actors(config)
scenario = scenario_class(self.world,
self.ego_vehicle,
self.actors,
config.town,
args.randomize,
args.debug)
except Exception as exception:
print("The scenario cannot be loaded")
traceback.print_exc()
print(exception)
self.cleanup()
continue
# Load scenario and run it
self.manager.load_scenario(scenario)
self.manager.run_scenario()
# Provide outputs if required
self.analyze_scenario(args, config)
# Stop scenario and cleanup
self.manager.stop_scenario()
del scenario
self.cleanup()
print("No more scenarios .... Exiting")
