def reset(self):
if self._done:
self._episode += 1
self._done = False
# print(f'Episode: {self._episode} done!')
if self._is_running:
self.sim.finishing_touch(self._start_time)
if self._episode % self._save_res_every_ep == 0:
self.sim.save_result(RESULTS,
self._worker_id,
unique_name=False)
if self._config['plot_queue_len']:
self.sim.plot_pass_queue_len(mode='taxi',
suffix=self._worker_id)
self.sim.plot_pass_wait_time(mode='taxi',
suffix=self._worker_id)
self._is_running = False
self.curr_time = 0
self._step = 0
self.graph = Graph()
self.graph.import_graph(graph_file)
self.sim = Simulator(self.graph)
self.sim.import_arrival_rate(unit=(1, 'sec'))
self.sim.import_vehicle_attribute(file_name=vehicle_file)
self.sim.set_running_time(start_time=self._config['start_time'],
time_horizon=self._config['time_horizon'],
unit='hour')
self.sim.routing.set_routing_method('simplex')
self.sim.initialize(seed=0)
self._total_vehicle = self.sim.vehicle_attri['taxi']['total']
self._travel_time = np.zeros((self._num_nodes, self._num_nodes))
for i, node in enumerate(self.graph.graph_top):
for j, road in enumerate(self.graph.graph_top):
if i != j:
self._travel_time[
i,
j] = self.graph.graph_top[node]['node'].road[road].dist
self._travel_time /= np.linalg.norm(self._travel_time, ord=np.inf)
self._pre_action = np.zeros((self._num_neighbors, self._num_nodes))
with open(vehicle_file, 'r') as v_file:
vehicle_dist = json.load(v_file)
vehicle_dist = vehicle_dist['taxi']['distrib']
vehicle_dist = np.array([vehicle_dist[x] for x in vehicle_dist])
return np.zeros((self._num_nodes, )), vehicle_dist
def __init__(self, config):
self._config = config
self.curr_time = 0
self.graph = Graph()
self.graph.import_graph(graph_file)
self.sim = Simulator(self.graph)
self.max_vehicle = self._config['max_vehicle']
self.reb_interval = self._config['reb_interval']
self.max_travel_t = self._config['max_travel_time']
self.max_lookback_steps = int(
np.ceil(self.max_travel_t / self.reb_interval))
self.max_passenger = self._config['max_passenger']
self._num_nodes = len(self._config['nodes_list'])
self._nodes = tuple(self._config['nodes_list'])
self._num_neighbors = self._config['near_neighbor']
self._neighbor_map = self._get_neighbors()
self._dispatch_rate = self._config['dispatch_rate']
self.action_space = MultiDiscrete([(self._num_neighbors + 1) * 5] *
self._num_nodes)
self.observation_space = Tuple((Box(0,
self.max_passenger,
shape=(self._num_nodes, ),
dtype=np.int64),
Box(0,
self.max_vehicle,
shape=(self._num_nodes, ),
dtype=np.int64)))
self._is_running = False
self._done = False
self._start_time = time.time()
self._alpha = self._config['alpha']
self._beta = self._config['beta']
self._step = 0
self._total_vehicle = None
self._travel_time = None
self._pre_action = None
self._episode = 0
self._worker_id = str(hash(time.time()))
self._save_res_every_ep = int(self._config['save_res_every_ep'])
self._vehicle_speed = self._config['veh_speed']
def __init__(self, config):
self._config = config
self.curr_time = 0
self.graph = Graph()
self.graph.import_graph(graph_file)
self.sim = Simulator(self.graph)
self.max_vehicle = self._config['max_vehicle']
self.reb_interval = self._config['reb_interval']
self.max_travel_t = self._config['max_travel_time']
self.max_lookback_steps = int(
np.ceil(self.max_travel_t / self.reb_interval))
self.max_passenger = self._config['max_passenger']
self.num_nodes = len(self._config['nodes_list'])
self.near_neighbor = self._config['near_neighbor']
self.action_space = Box(low=0,
high=1,
shape=((self.near_neighbor + 1) *
self.num_nodes, ))
self.observation_space = Tuple((Box(0,
self.max_passenger,
shape=(self.num_nodes, ),
dtype=np.int64),
Box(0,
self.max_vehicle,
shape=(self.num_nodes, ),
dtype=np.int64)))
self._is_running = False
self._done = False
self._start_time = time.time()
self._alpha = 0
self._step = 0
self._total_vehicle = None
self._travel_time = None
self._pre_action = None
self._episode = 0