def start_torcs_process(self): if self.torcs_proc is not None: os.killpg(os.getpgid(self.torcs_proc.pid), signal.SIGKILL) time.sleep(0.5) self.torcs_proc = None self.test_torcs_server_port() if self._config.traffic: self.traffic_manager = traffic.MadrasTrafficManager( self.torcs_server_port, 1, self._config.traffic) TorcsEnv.__init__(self, vision=self._config.vision, throttle=self._config.throttle, gear_change=self._config.gear_change, visualise=self._config.visualise, no_of_visualisations=self._config.no_of_visualisations, torcs_server_port=self.torcs_server_port) command = None rank = MPI.COMM_WORLD.Get_rank() self.torcs_server_config.generate_torcs_server_config() self.madras_agent_port = self.torcs_server_port + self.torcs_server_config.num_traffic_cars if rank < self._config.no_of_visualisations and self._config.visualise: command = 'export TORCS_PORT={} && vglrun torcs -t 10000000 -nolaptime'.format(self.torcs_server_port) else: command = 'export TORCS_PORT={} && torcs -t 10000000 -r ~/.torcs/config/raceman/quickrace.xml -nolaptime'.format(self.torcs_server_port) if self._config.vision is True: command += ' -vision' if self._config.noisy_observations: command += ' -noisy' self.torcs_proc = subprocess.Popen([command], shell=True, preexec_fn=os.setsid) time.sleep(1)
def __init__(self, vision=False, throttle=True, gear_change=False, port=60934, pid_assist=False, CLIENT_MAX_STEPS=np.inf, visualise=True, no_of_visualisations=1): # If `visualise` is set to False torcs simulator will run in headless mode """Init Method.""" self.torcs_proc = None self.pid_assist = pid_assist if self.pid_assist: self.action_dim = 2 # LanePos, Velocity else: self.action_dim = 3 # Accel, Steer, Brake TorcsEnv.__init__(self, vision=False, throttle=True, gear_change=False, visualise=visualise, no_of_visualisations=no_of_visualisations) self.state_dim = 29 # No. of sensors input self.env_name = 'Madras_Env' self.port = port self.visualise = visualise self.no_of_visualisations = no_of_visualisations self.CLIENT_MAX_STEPS = CLIENT_MAX_STEPS self.client_type = 0 # Snakeoil client type self.initial_reset = True self.early_stop = True if self.pid_assist: self.PID_latency = 10 else: self.PID_latency = 1 self.accel_PID = PID(np.array([10.5, 0.05, 2.8])) # accel PID self.steer_PID = PID(np.array([5.1, 0.001, 0.000001])) # steer PID self.prev_lane = 0 self.prev_angle = 0 self.prev_vel = 0 self.prev_dist = 0 self.ob = None self.track_len = 7014.6 self.seed() self.start_torcs_process()
def __init__(self, port, cfg, name='MadrasTraffic'): self.cfg = cfg self.name = name self.steer = 0.0 self.accel = 0.0 self.brake = 0.0 self.env = TorcsEnv( vision=(cfg["vision"] if "vision" in cfg else False), throttle=(cfg["throttle"] if "throttle" in cfg else True), gear_change=(cfg["gear_change"] if "gear_change" in cfg else False), visualise=(self.cfg["visualise"] if "visualise" in self.cfg else False), name=self.name) self.PID_controller = PIDController(cfg["pid_settings"]) self.port = port self.min_safe_dist = 0.005 * ( cfg["min_safe_dist"] if "min_safe_dist" in cfg else 1) # 1 meter
def step_pid(self, desire): """Execute single step with lane_pos, velocity controls.""" lane_pos_scale = self._config.track_limits[ 'high'] - self._config.track_limits['low'] desire[ 0] = self._config.track_limits['low'] + lane_pos_scale * desire[0] if self._config.normalize_actions: # [-1, 1] should correspond to [-self._config.target_speed, # self._config.target_speed] speed_scale = self._config.target_speed desire[1] *= speed_scale # Now in m/s # convert to km/hr desire[1] *= 3600 / 1000 # Now in km/hr # Normalize to gym_torcs specs desire[1] /= self.default_speed reward = 0.0 for PID_step in range(self._config.pid_settings['pid_latency']): a_t = self.PID_controller.get_action(desire) try: self.ob, r, done, info = TorcsEnv.step(self, PID_step, self.client, a_t, self._config.early_stop) except Exception as e: logging.debug("Exception {} caught at port {}".format( str(e), self.torcs_server_port)) self.wait_for_observation() game_state = { "torcs_reward": r, "torcs_done": done, "distance_traversed": self.client.S.d["distRaced"], "angle": self.client.S.d["angle"], "damage": self.client.S.d["damage"], "trackPos": self.client.S.d["trackPos"], "racePos": self.client.S.d["racePos"], "track": self.client.S.d["track"] } reward += self.reward_handler.get_reward(self._config, game_state) if self._config.pid_assist: self.PID_controller.update(self.ob) done = self.done_handler.get_done_signal(self._config, game_state) if done: self.client.R.d["meta"] = True # Terminate the episode logging.info('Terminating PID {}'.format( self.client.serverPID)) break next_obs = self.observation_handler.get_obs(self.ob, self._config) info["distRaced"] = self.client.S.d["distRaced"] info["racePos"] = self.client.S.d["racePos"] return next_obs, reward, done, info
def reset(self, prev_step_info=None): """Reset Method. To be called at the end of each episode""" if self.initial_reset: while self.ob is None: try: self.client = snakeoil3.Client(p=self.port, vision=self.vision, visualise=self.visualise) # Open new UDP in vtorcs self.client.MAX_STEPS = self.CLIENT_MAX_STEPS self.client.get_servers_input(step=0) # Get the initial input from torcs raw_ob = self.client.S.d # Get the current full-observation self.ob = self.make_observation(raw_ob) except: pass self.initial_reset = False else: try: self.ob, self.client = TorcsEnv.reset(self, client=self.client, relaunch=True) except Exception as e: self.ob = None while self.ob is None: try: print("Hard Reset") # self.end(self.client) self.client = snakeoil3.Client(p=self.port, vision=self.vision) # Open new UDP in vtorcs self.client.MAX_STEPS = self.CLIENT_MAX_STEPS self.client.get_servers_input(step=0) # Get the initial input from torcs raw_ob = self.client.S.d # Get the current full-observation from torcs self.ob = self.make_observation(raw_ob) except: pass self.distance_traversed = 0 s_t = np.hstack((self.ob.angle, self.ob.track, self.ob.trackPos, self.ob.speedX, self.ob.speedY, self.ob.speedZ, self.ob.wheelSpinVel / 100.0, self.ob.rpm)) self.prev_angle = 0.0 self.prev_dist = 0.0 self.prev_lane = 0.0 self.accel_PID.reset_pid() self.steer_PID.reset_pid() return s_t
def step_vanilla(self, action): """Execute single step with steer, acceleration, brake controls.""" if self._config.normalize_actions: # action[1] = (action[1] + 1) / 2.0 # acceleration back to [0, 1] # action[2] = (action[2] + 1) / 2.0 # brake back to [0, 1] action[0] = self.clip(action[0], -1, 1) action[1] = self.clip(action[1], 0, 1) action[2] = self.clip(action[2], 0, 1) # print(action) r = 0.0 try: self.ob, r, done, info = TorcsEnv.step(self, 0, self.client, action, self._config.early_stop) except Exception as e: logging.debug("Exception {} caught at port {}".format( str(e), self.torcs_server_port)) self.wait_for_observation() if done: print('torce_done is True') game_state = { "torcs_reward": r, "torcs_done": done, "distance_traversed": self.client.S.d['distRaced'], "angle": self.client.S.d["angle"], "damage": self.client.S.d["damage"], "trackPos": self.client.S.d["trackPos"], "racePos": self.client.S.d["racePos"], "track": self.client.S.d["track"] } reward = self.reward_handler.get_reward(self._config, game_state, action) done = self.done_handler.get_done_signal(self._config, game_state) if done: if self._config.traffic: self.traffic_manager.kill_all_traffic_agents() self.client.R.d["meta"] = True # Terminate the episode logging.info('Terminating PID {}'.format(self.client.serverPID)) # print(self.ob) next_obs = self.observation_handler.get_obs(self.ob, self._config) info["distRaced"] = self.client.S.d["distRaced"] info["racePos"] = self.client.S.d["racePos"] return next_obs, reward, done, info
def reset(self): """Reset Method to be called at the end of each episode.""" self.step_num = 0 if not self.initial_reset: self.torcs_server_config.generate_torcs_server_config() self.madras_agent_port = self.torcs_server_port + self.torcs_server_config.num_traffic_cars self.client.port = self.madras_agent_port # This is very bad code! But we wont need it any way in v2 logging.info("Num traffic cars in server {}".format( self.torcs_server_config.num_traffic_cars)) if self._config.traffic: self.traffic_manager.reset( self.torcs_server_config.num_traffic_cars) self._config.track_len = self.torcs_server_config.track_length if self.initial_reset: self.wait_for_observation() self.initial_reset = False else: while True: try: self.ob, self.client = TorcsEnv.reset(self, client=self.client, relaunch=True) except Exception: self.wait_for_observation() if not np.any(np.asarray(self.ob.track) < 0): break else: logging.info( "Reset: Reset failed as agent started off track. Retrying..." ) self.distance_traversed = 0 s_t = self.observation_handler.get_obs(self.ob, self._config) if self._config.pid_assist: self.PID_controller.reset() self.reward_handler.reset() self.done_handler.reset() logging.info("Reset: Starting new episode") if np.any(np.asarray(self.ob.track) < 0): logging.info("Reset produced bad track values.") return s_t
def playTraffic(port=3101, target_vel=50.0, angle=0.0, sleep=0): """Traffic Play function.""" env = TorcsEnv(vision=False, throttle=True, gear_change=False) ob = None while ob is None: try: client = snakeoil3.Client(p=port, vision=False) client.MAX_STEPS = np.inf client.get_servers_input(step=0) obs = client.S.d ob = env.make_observation(obs) except: pass episode_count = cfg['traffic']['max_eps'] max_steps = cfg['traffic']['max_steps_eps'] early_stop = 0 velocity_i = target_vel / 300.0 accel_pid = PID(np.array([10.5, 0.05, 2.8])) steer_pid = PID(np.array([5.1, 0.001, 0.000001])) steer = 0.0 accel = 0.0 brake = 0 A = cfg['traffic']['amplitude'] / 300.0 T = cfg['traffic']['time_period'] # print(velocity_i) for i in range(episode_count): info = {'termination_cause': 0} steer = 0.0 accel = 0.0 brake = 0 S = 0.0 for step in range(max_steps): a_t = np.asarray([steer, accel, brake]) # [steer, accel, brake] try: ob, r_t, done, info = env.step(step, client, a_t, early_stop) if done: pass except Exception as e: print("Exception caught at point A at port " + str(i) + str(e)) ob = None while ob is None: try: client = snakeoil3.Client(p=port, vision=False) client.MAX_STEPS = np.inf client.get_servers_input(step=0) obs = client.S.d ob = env.make_observation(obs) except: pass continue if (step <= sleep): print("WAIT" + str(port)) continue velocity = velocity_i + A * math.sin(step / T) opp = ob.opponents front = np.array([opp[15], opp[16], opp[17], opp[18], opp[19]]) closest_front = np.min(front) if (step % T == 0): print("VEL_CHANGE: ", velocity * 300.0) vel_error = velocity - ob.speedX angle_error = -(ob.trackPos - angle) / 10 + ob.angle steer_pid.update_error(angle_error) accel_pid.update_error(vel_error) accel = accel_pid.output() steer = steer_pid.output() if accel < 0: brake = 1 else: brake = 0 if closest_front < ((float(0.5 * ob.speedX * 100) + 10.0) / 200.0): brake = 1 else: brake = 0 try: if 'termination_cause' in info.keys() and info['termination_cause'] == 'hardReset': print('Hard reset by some agent') ob, client = env.reset(client=client, relaunch=True) except Exception as e: print("Exception caught at point B at port " + str(i) + str(e) ) ob = None while ob is None: try: client = snakeoil3.Client(p=port, vision=False) # Open new UDP in vtorcs client.MAX_STEPS = np.inf client.get_servers_input(0) # Get the initial input from torcs obs = client.S.d # Get the current full-observation from torcs ob = env.make_observation(obs) except: print("Exception caught at at point C at port " + str(i) + str(e))
def step(self, desire): """Step method to be called at each time step.""" r_t = 0 for PID_step in range(self.PID_latency): # Implement the desired trackpos and velocity using PID if self.pid_assist: self.accel_PID.update_error((desire[1] - self.prev_vel)) self.steer_PID.update_error( (-(self.prev_lane - desire[0]) / 10 + self.prev_angle)) if self.accel_PID.output() < 0.0: brake = 1 else: brake = 0 a_t = np.asarray( [self.steer_PID.output(), self.accel_PID.output(), brake]) else: a_t = desire try: self.ob, r, done, info = TorcsEnv.step(self, PID_step, self.client, a_t, self.early_stop) except Exception as e: print(("Exception caught at port " + str(e))) self.ob = None while self.ob is None: try: self.client = snakeoil3.Client(p=self.port, vision=self.vision) # Open new UDP in vtorcs self.client.MAX_STEPS = self.CLIENT_MAX_STEPS self.client.get_servers_input(0) # Get the initial input from torcs raw_ob = self.client.S.d # Get the current full-observation from torcs self.ob = self.make_observation(raw_ob) except: pass continue self.prev_vel = self.ob.speedX self.prev_angle = self.ob.angle self.prev_lane = self.ob.trackPos if (math.isnan(r)): r = 0.0 r_t += r # accumulate rewards over all the time steps self.distance_traversed = self.client.S.d['distRaced'] r_t += (self.distance_traversed - self.prev_dist) /\ self.track_len self.prev_dist = deepcopy(self.distance_traversed) if self.distance_traversed >= self.track_len: done = True if done: # self.reset() break s_t1 = np.hstack((self.ob.angle, self.ob.track, self.ob.trackPos, self.ob.speedX, self.ob.speedY, self.ob.speedZ, self.ob.wheelSpinVel / 100.0, self.ob.rpm)) return s_t1, r_t, done, info
class MadrasTrafficAgent(object): def __init__(self, port, cfg, name='MadrasTraffic'): self.cfg = cfg self.name = name self.steer = 0.0 self.accel = 0.0 self.brake = 0.0 self.env = TorcsEnv( vision=(cfg["vision"] if "vision" in cfg else False), throttle=(cfg["throttle"] if "throttle" in cfg else True), gear_change=(cfg["gear_change"] if "gear_change" in cfg else False), visualise=(self.cfg["visualise"] if "visualise" in self.cfg else False), name=self.name) self.PID_controller = PIDController(cfg["pid_settings"]) self.port = port self.min_safe_dist = 0.005 * ( cfg["min_safe_dist"] if "min_safe_dist" in cfg else 1) # 1 meter def wait_for_observation(self): """Refresh client and wait for a valid observation to come in.""" self.ob = None while self.ob is None: logging.debug("{} Still waiting for observation at {}".format( self.name, self.port)) try: self.client = snakeoil3.Client( p=self.port, vision=(self.cfg["vision"] if "vision" in self.cfg else False), visualise=(self.cfg["visualise"] if "visualise" in self.cfg else False), name=self.name) # Open new UDP in vtorcs self.client.MAX_STEPS = self.cfg[ "client_max_steps"] if "client_max_steps" in self.cfg else np.inf self.client.get_servers_input(0) # Get the initial input from torcs raw_ob = self.client.S.d # Get the current full-observation from torcs self.ob = self.env.make_observation(raw_ob) except: pass def get_action(self): raise NotImplementedError( "Successor classes must implement this method") def flag_off(self, random_seed=0): del random_seed self.wait_for_observation() logging.debug("[{}]: My server is PID: {}".format( self.name, self.client.serverPID)) self.is_alive = True while True: if self.is_alive: action = self.get_action() try: self.ob, _, done, info = self.env.step( 0, self.client, action) except Exception as e: logging.debug( "Exception {} caught by {} traffic agent at port {}". format(str(e), self.name, self.port)) self.wait_for_observation() self.detect_and_prevent_imminent_crash_out_of_track() self.PID_controller.update(self.ob) if done: self.is_alive = False logging.debug("{} died.".format(self.name)) def get_front_opponents(self): return np.array([ self.ob.opponents[16], self.ob.opponents[17], self.ob.opponents[18], ]) def detect_and_prevent_imminent_crash_out_of_track(self): while True: min_dist_from_track = np.min(self.ob.track) if min_dist_from_track <= self.min_safe_dist: closest_dist_sensor_id = np.argmin(self.ob.track) if closest_dist_sensor_id < 9: action = [1, 0, 1] elif closest_dist_sensor_id > 9: action = [-1, 0, 1] else: action = [0, 0, 1] self.ob, _, _, _ = self.env.step(0, self.client, action) else: break def get_collision_cone_radius(self): speed = self.ob.speedX * self.env.default_speed * (1000.0 / 3600.0 ) # speed in m/sec collision_time_window = self.cfg[ "collision_time_window"] if "collision_time_window" in self.cfg else 1 collision_cone_radius = collision_time_window * speed return collision_cone_radius / 200.0 # Normalizing def avoid_impending_collision(self): # If the opponent in front is too close, brake opponents_in_front = self.get_front_opponents() closest_front = np.min(opponents_in_front) frontal_distance_threshold = self.get_collision_cone_radius() if closest_front < frontal_distance_threshold: self.brake = 1 else: self.brake = 0