def init_price(self, match_commands):
m_commands = []
for c in match_commands:
vehicle = VehicleRepository.get(c["vehicle_id"])
# vehicle.state.status = status_codes.V_ASSIGNED
if vehicle is None:
print("Invalid Vehicle id")
continue
customer = CustomerRepository.get(c["customer_id"])
if customer is None:
print("Invalid Customer id")
continue
triptime = c["duration"]
# if FLAGS.enable_pricing:
dist_for_pickup = c["distance"]
dist_till_dropoff = great_circle_distance(
customer.get_origin()[0],
customer.get_origin()[1],
customer.get_destination()[0],
customer.get_destination()[1])
total_trip_dist = dist_for_pickup + dist_till_dropoff
[travel_price, wait_price] = vehicle.get_price_rates()
# v_cap = vehicle.state.current_capacity
initial_price = calculate_price(total_trip_dist, triptime,
vehicle.state.mileage,
travel_price, wait_price,
vehicle.state.gas_price,
vehicle.state.driver_base_per_trip)
c["init_price"] = initial_price
m_commands.append(c)
# print(c)
return m_commands
def dispatch_vehicles(self, commands):
# print("D: ", commands)
od_pairs = []
vehicles = []
# Comamnd is a dictionary created in dummy_agent
for command in commands:
vehicle = VehicleRepository.get(command["vehicle_id"])
if vehicle is None:
self.logger.warning("Invalid Vehicle id")
continue
if "offduty" in command:
off_duration = self.sample_off_duration() # Rand time to rest
vehicle.take_rest(off_duration)
elif "cache_key" in command:
l, a = command["cache_key"]
route, triptime = self.routing_engine.get_route_cache(l, a)
vehicle.cruise(route, triptime)
else:
vehicles.append(vehicle)
od_pairs.append(
(vehicle.get_location(), command["destination"]))
routes = self.routing_engine.route(od_pairs)
for vehicle, (route, triptime) in zip(vehicles, routes):
if triptime == 0:
continue
vehicle.cruise(route, triptime)
def predict_best_action(self, vehicle_id, vehicle_state):
if vehicle_state.idle_duration >= MIN_DISPATCH_CYCLE and FLAGS.offduty_probability > np.random.random(
):
a, offduty = (0, 0), 1
elif self.q_network is None:
a, offduty = (0, 0), 0
else:
x, y = mesh.convert_lonlat_to_xy(vehicle_state.lon,
vehicle_state.lat)
if (x, y) in self.q_cache:
actions, Q, amax = self.q_cache[(x, y)]
else:
# Get state features and action features
s, actions = self.feature_constructor.construct_current_features(
x, y)
# print("A: ", actions, len(actions))
# print("S: ", s)
# Calculate Q values based on state features
Q = self.q_network.compute_q_values(s)
# print("Q values: ", Q)
# only considers actions whose values are greater than wait action value
wait_action_value = Q[0]
actions = [
a for a, q in zip(actions, Q) if q >= wait_action_value
]
Q = Q[Q >= wait_action_value]
# print("Q ba: ", Q)
amax = np.argmax(Q) # Get the index of the max value
# print("Q max, val, max: ", amax, Q[amax], max(Q))
self.q_cache[(x, y)] = actions, Q, amax # Save in cache
# if actions[amax] == (0, 0):
# aidx = amax
# else:
aidx = self.q_network.get_action(
Q, amax) # Get action with max Q value
a = actions[aidx]
offduty = 1 if Q[aidx] < FLAGS.offduty_threshold else 0
# print("Chosen A: ", a)
vehicle = VehicleRepository.get(vehicle_id)
# tmp_q_action = {a:q for a, q in zip(actions, Q)}
q_action = {(x + ax, y + ay): q for (ax, ay), q in zip(actions, Q)}
vehicle.q_action_dict = q_action
vehicle.epsilon = int(len(vehicle.q_action_dict) * 0.05)
# print("Loc: ", x, " , ", y)
# print("Act: ", tmp_q_action)
# print("Added:", vehicle.q_action_dict)
return a, offduty
def init_price(self, match_commands):
m_commands = []
for c in match_commands:
vehicle = VehicleRepository.get(c["vehicle_id"])
# vehicle.state.status = status_codes.V_ASSIGNED
if vehicle is None:
print("Invalid Vehicle id")
continue
customer = CustomerRepository.get(c["customer_id"])
if customer is None:
print("Invalid Customer id")
continue
triptime = c["duration"]
# if FLAGS.enable_pricing:
dist_for_pickup = c["distance"]
od_route = self.routing_engine.route_time([
(customer.get_origin(), customer.get_destination())
])
# dist_dropoff = great_circle_distance(customer.get_origin()[0], customer.get_origin()[1],
# customer.get_destination()[0], customer.get_destination()[1])
route, time = od_route[0]
lats, lons = zip(*route)
distance = geoutils.great_circle_distance(
lats[:-1], lons[:-1], lats[1:], lons[1:]) # Distance in meters
dist_till_dropoff = sum(distance)
# print(dist_dropoff, dist_till_dropoff)
total_trip_dist = dist_for_pickup + dist_till_dropoff
[travel_price, wait_price] = vehicle.get_price_rates()
# v_cap = vehicle.state.current_capacity
initial_price = calculate_price(total_trip_dist, triptime,
vehicle.state.mileage,
travel_price, wait_price,
vehicle.state.gas_price,
vehicle.state.driver_base_per_trip)
c["init_price"] = initial_price
m_commands.append(c)
# print(c)
return m_commands
def startup_dispatch(self, current_time, vehicles):
self.dispatch_policy.update_state(current_time, vehicles)
if FLAGS.train:
self.dispatch_policy.give_rewards(vehicles)
dispatch_commands = self.dispatch_policy.get_dispatch_decisions(vehicles)
self.dispatch_policy.record_dispatch(vehicles.index, current_time)
for vid in vehicles.index:
vehicle = VehicleRepository.get(vid)
vehicle.first_dispatched = 1
######### Only with the DQN agent not the dummy #############
if FLAGS.train:
self.dispatch_policy.backup_supply_demand()
# If size exceeded, run training
if len(self.dispatch_policy.supply_demand_history) > INITIAL_MEMORY_SIZE:
average_loss, average_q_max = self.dispatch_policy.train_network(FLAGS.batch_size)
# print("iterations : {}, average_loss : {:.3f}, average_q_max : {:.3f}".format(
# self.q_network.n_steps, average_loss, average_q_max), flush=True)
self.dispatch_policy.q_network.write_summary(average_loss, average_q_max)
return dispatch_commands
def give_rewards(self, vehicles):
for vehicle_id, row in vehicles.iterrows():
vehicle = VehicleRepository.get(vehicle_id)
earnings = row.earnings - self.last_earnings.get(vehicle_id, 0)
cost = vehicle.compute_fuel_consumption()
if earnings > 0:
cost -= self.last_cost.get(vehicle_id, 0)
profit = earnings - cost
else:
profit = earnings
# print("Earnings: ", earnings, "Cost: ", cost, "Profit: ", profit)
self.rewards[vehicle_id] += (
12 * profit
) - 5 * row.pickup_time + 10 * settings.STATE_REWARD_TABLE[
row.status]
# self.rewards[vehicle_id] += earnings + settings.STATE_REWARD_TABLE[row.status]
self.last_earnings[vehicle_id] = row.earnings
if earnings > 0:
self.last_cost[vehicle_id] = vehicle.compute_fuel_consumption()
if row.status == status_codes.V_OFF_DUTY:
self.last_state_actions[vehicle_id] = None
def match_vehicles(self, commands, dqn_agent, dummy_agent):
# print("M: ", commands)
vehicle_list = []
rejected_requests = []
accepted_commands = []
num_accepted = 0
# reject_count = 0
vehicle_accepted_cust = defaultdict(list)
# od_accepted_pairs = []
# Comamnd is a dictionary created in dummy_agent
# print("########################################################")
for command in commands:
rejected_flag = 0
# print(command["vehicle_id"], command["customer_id"])
vehicle = VehicleRepository.get(command["vehicle_id"])
vid = command["vehicle_id"]
# print("V_Loc: ", vehicle.get_location())
# vehicle.state.status = status_codes.V_ASSIGNED
if vehicle is None:
self.logger.warning("Invalid Vehicle id")
continue
# print("Vid: ", vid, "Plan: ", vehicle.current_plan)
# vehicle_cust_price_time = dict()
if (vehicle.state.status == status_codes.V_OCCUPIED
) & vehicle.state.accept_new_request:
# print(vid, "Update", vehicle.current_plan, vehicle.get_destination())
if (len(vehicle.current_plan)
== 0) & (vehicle.state.destination_lat is not None):
# print(vid, "Dest: ", vehicle.get_destination())
vehicle.current_plan = [vehicle.get_destination()]
vehicle.current_plan_routes = [
(vehicle.get_route(),
vehicle.state.time_to_destination)
]
elif (len(vehicle.current_plan)
== 0) & (vehicle.state.destination_lat is None):
vehicle.change_to_idle()
vehicle.reset_plan()
elif (len(vehicle.current_plan) != 0) & (
vehicle.get_destination() != vehicle.current_plan[0]):
# print(vid, ": ", vehicle.get_destination(), vehicle.current_plan[0])
if vehicle.state.destination_lat is not None:
plan = [vehicle.get_destination()]
plan.extend(vehicle.current_plan)
vehicle.current_plan = np.copy(plan).tolist()
if len(vehicle.get_route()) == 0:
# print(vid, "Empty Route!!", vehicle.get_destination())
# print(vehicle.current_plan)
# print(vehicle.pickup_flags)
# print(vehicle.ordered_pickups_dropoffs_ids)
# print(vehicle.current_plan_routes)
od_routes = self.routing_engine.route_time([
(vehicle.get_location(),
vehicle.get_destination())
])
routes = [od_routes[0]]
else:
routes = [[
vehicle.get_route(),
vehicle.state.time_to_destination
]]
routes.extend(vehicle.current_plan_routes)
vehicle.current_plan_routes = np.copy(routes).tolist()
# if len(vehicle.get_route()) == 0:
# print("R: ", vehicle.current_plan_routes)
if len(vehicle.current_plan) != len(vehicle.current_plan_routes) != len(\
vehicle.ordered_pickups_dropoffs_ids) != len(vehicle.pickup_flags):
print("ERROR!")
prev_cost = 0
# For each vehicle
# Need to calculate route (and order customer list) before heading to customer
for index in range(len(command["customer_id"])):
customer = CustomerRepository.get(
command["customer_id"][index])
if customer is None:
self.logger.warning("Invalid Customer id")
continue
prev_plan = np.copy(vehicle.current_plan)
prev_flags = np.copy(vehicle.pickup_flags)
prev_ids = np.copy(vehicle.ordered_pickups_dropoffs_ids)
prev_routes = np.copy(vehicle.current_plan_routes)
vehicle_accepted_cust[vid].append(
command["customer_id"][index])
insertion_cost, waiting_time = self.generate_plan(
vehicle, vehicle_accepted_cust[vid], customer)
if len(vehicle_accepted_cust[vid]) > 1:
# print("prev: ", prev_cost, insertion_cost)
insertion_cost = abs(insertion_cost - prev_cost)
if insertion_cost == float(0):
insertion_cost = command["init_price"][index]
# print("L: ", len(vehicle_accepted_cust[vid]))
# print("C: ", insertion_cost)
[travel_price, wait_price] = vehicle.get_price_rates()
init_price = calculate_price(
insertion_cost, waiting_time, vehicle.state.mileage,
travel_price, wait_price, vehicle.state.gas_price,
vehicle.state.driver_base_per_trip)
# print("P: ", init_price, command["init_price"][index])
command["duration"][index] = waiting_time
command["init_price"][index] = init_price
# print("A: ", command)
if FLAGS.enable_pricing:
# For DQN
if vehicle.state.agent_type == agent_codes.dummy_agent:
price_response = dummy_agent.get_price_decision(
vehicle, init_price, customer.get_request())
elif vehicle.state.agent_type == agent_codes.dqn_agent:
price_response = dqn_agent.get_price_decision(
vehicle, init_price, customer.get_request())
# price_response = initial_price
# print("Diff: ", (price_response-initial_price))
# Now, customer needs to calculate reward and accept or reject
if customer.accpet_reject_ride(
price_response, vehicle.state,
waiting_time): # If customer accepts
num_accepted += 1
# if not FLAGS.enable_pooling:
# vehicle.head_for_customer(customer.get_origin(), waiting_time, customer.get_id(), command["distance"][index])
vehicle.accepted_customers.append(
command["customer_id"][index])
# vehicle.accepted_customers.append([customer, triptime, price_response, command["distance"][index]])
customer.wait_for_vehicle(waiting_time)
prev_cost = insertion_cost
# vehicle_accepted_cust[vid].append(command["customer_id"][index])
# vehicle.state.current_capacity += 1
accepted_commands.append(command)
# print("Accepted, cust: ", customer.get_id(), " ", vehicle.current_plan)
else:
# rejected_flag = 1
# reject_count += 1
customer.go_to_nxt_timestep = 1
rejected_requests.append(customer.get_request())
# if len(prev_plan) == 0:
# print("Should be Empty!")
vehicle.current_plan = prev_plan.tolist()
vehicle.pickup_flags = prev_flags.tolist()
vehicle.ordered_pickups_dropoffs_ids = prev_ids.tolist(
)
vehicle.current_plan_routes = prev_routes.tolist()
# print("B: ", vehicle.accepted_customers, vehicle_accepted_cust[vid])
# print("Reject: ", vid, " ", customer.get_id())
vehicle_accepted_cust[vid].pop()
# vehicle.accepted_customers.pop(0)
# print("A: ", vehicle_accepted_cust[vid], len(vehicle_accepted_cust[vid]), vehicle.accepted_customers)
# print("Rejected, cust: ", customer.get_id(), " ", vehicle.current_plan)
else:
customer.accepted_price = init_price
# if not FLAGS.enable_pooling:
# vehicle.head_for_customer(customer.get_origin(), triptime, customer.get_id(), command["distance"][index])
vehicle.accepted_customers.append(
command["customer_id"][index])
# vehicle.accepted_customers.append([customer, triptime, price_response, command["distance"][index]])
customer.wait_for_vehicle(waiting_time)
prev_cost = insertion_cost
accepted_commands = commands
# od_accepted_pairs = pairs
# vehicle.state.status = status_codes.V_ASSIGNED
if FLAGS.enable_pooling:
# print("vid: ", vehicle.get_id(), "Accepted: ", len(vehicle_accepted_cust[vid]))
vehicle.tmp_capacity = vehicle.state.current_capacity
# if vid not in vehicle_list and len(vehicle_accepted_cust[vid]) != 0:
# vehicle_list.append(vid)
if len(vehicle.current_plan) == 0:
# print(vid, "EMPTYYYYYY!")
continue
else:
route, triptime = vehicle.current_plan_routes.pop(0)
vehicle.nxt_stop = vehicle.current_plan.pop(0)
if len(route) == 0:
# print("B: ", triptime, len(vehicle.current_plan), len(vehicle.ordered_pickups_dropoffs_ids),
# len(vehicle.current_plan_routes))
r2 = self.routing_engine.route_time([
(vehicle.get_location(), vehicle.nxt_stop)
])
route, triptime = r2[0]
# print("Updated: ", triptime, len(route))
# print("Loc: ", vehicle.get_location(), "Nxt: ", vehicle.nxt_stop)
cust_id = vehicle.ordered_pickups_dropoffs_ids[0]
if triptime == 0.0:
# vehicle.current_plan.pop(0)
pick_drop = vehicle.pickup_flags.pop(0)
cust_id = vehicle.ordered_pickups_dropoffs_ids.pop(0)
# print("routes: ", routes)
vehicle.state.assigned_customer_id = cust_id
if pick_drop == 1:
vehicle.state.lat, vehicle.state.lon = CustomerRepository.get(
cust_id).get_origin()
vehicle.pickup(CustomerRepository.get(cust_id))
else:
vehicle.state.lat, vehicle.state.lon = CustomerRepository.get(
cust_id).get_destination()
vehicle.dropoff(CustomerRepository.get(cust_id))
else:
vehicle.head_for_customer(triptime, cust_id, route)
# vehicle.nxt_stop = vehicle.current_plan[0]
vehicle.change_to_assigned()
return rejected_requests, accepted_commands, num_accepted
# print("B: ", len(requests), len(r_df))
requests = requests.append(r_df, ignore_index=True)
sum_requests += len(requests)
requests = requests.set_index("id")
# print("R After: ", len(requests))
current_time = Sim_experiment.simulator.get_current_time()
# For DQN
if FLAGS.enable_pricing:
# print("All: ", len(vehicles), m)
if len(vehicles) > 0:
new_vehicles = vehicles.loc[[
vehicle_id for vehicle_id in vehicles.index
if VehicleRepository.get(
vehicle_id).first_dispatched == 0
]]
startup_dispatch = Sim_experiment.dqn_agent.startup_dispatch(
current_time, new_vehicles)
Sim_experiment.simulator.dispatch_vehicles(
startup_dispatch)
# print("Done", len(new_vehicles))
if len(vehicles) == 0:
continue
else:
# print("V1: ", len(vehicles))
m_commands, vehicles = Sim_experiment.central_agent.get_match_commands(
current_time, vehicles, requests)
# print("V2: ", len(vehicles))
def match_vehicles(self, commands, dqn_agent, dummy_agent):
# print("M: ", commands)
vehicle_list = []
rejected_requests = []
accepted_commands = {}
reject_count = 0
# Comamnd is a dictionary created in dummy_agent
# print("########################################################")
for command in commands:
rejected_flag = 0
# print(command["vehicle_id"], command["customer_id"])
vehicle = VehicleRepository.get(command["vehicle_id"])
# vehicle.state.status = status_codes.V_ASSIGNED
if vehicle is None:
self.logger.warning("Invalid Vehicle id")
continue
customer = CustomerRepository.get(command["customer_id"])
if customer is None:
self.logger.warning("Invalid Customer id")
continue
triptime = command["duration"]
vid = command["vehicle_id"]
# print("Maching: Vehicle " + vehicle.to_string() + " ---> " + customer.to_string())
price_response = command["init_price"]
if FLAGS.enable_pricing:
# For DQN
if vehicle.state.agent_type == agent_codes.dummy_agent:
price_response = dummy_agent.get_price_decision(
vehicle, command["init_price"], customer.get_request())
elif vehicle.state.agent_type == agent_codes.dqn_agent:
price_response = dqn_agent.get_price_decision(
vehicle, command["init_price"], customer.get_request())
# price_response = initial_price
# print("Diff: ", (price_response-initial_price))
# Now, customer needs to calculate reward and accpet or reject
if customer.accpet_reject_ride(
price_response, vehicle.state,
triptime): # If customer accepts
vehicle.head_for_customer(customer.get_origin(), triptime,
customer.get_id(),
command["distance"])
customer.wait_for_vehicle(triptime)
v = VehicleRepository.get(vid)
v.state.current_capacity += 1
accepted_commands[reject_count] = command
# print(command)
# print(accepted_commands)
reject_count += 1
# print(len(accepted_commands))
else: # base case: request drops
rejected_flag = 1
customer.go_to_nxt_timestep = 1
rejected_requests.append(customer.get_request())
else:
customer.accepted_price = command["init_price"]
vehicle.head_for_customer(customer.get_origin(), triptime,
customer.get_id(),
command["distance"])
customer.wait_for_vehicle(triptime)
v = VehicleRepository.get(vid)
v.state.current_capacity += 1
accepted_commands = commands
# vehicle.state.status = status_codes.V_ASSIGNED
if FLAGS.enable_pooling:
if vid not in vehicle_list and not rejected_flag:
vehicle_list.append(vid)
if FLAGS.enable_pooling:
for vi in vehicle_list:
vehicle = VehicleRepository.get(vi)
# vehicle.print_vehicle()
vehicle.change_to_assigned()
return rejected_requests, accepted_commands
def init_price(self, match_commands, charging_commands):
m_commands = []
for m in match_commands:
vehicle = VehicleRepository.get(m["vehicle_id"])
# vehicle.state.status = status_codes.V_ASSIGNED
if vehicle is None:
print("Invalid Vehicle id")
continue
customer = CustomerRepository.get(m["customer_id"])
if customer is None:
print("Invalid Customer id")
continue
triptime = m["duration"]
# if FLAGS.enable_pricing:
dist_for_pickup = m["distance"]
dist_till_dropoff = great_circle_distance(
customer.get_origin()[0],
customer.get_origin()[1],
customer.get_destination()[0],
customer.get_destination()[1])
total_trip_dist = dist_for_pickup + dist_till_dropoff
[travel_price, wait_price] = vehicle.get_price_rates()
# v_cap = vehicle.state.current_capacity
initial_price = calculate_price(total_trip_dist, triptime,
vehicle.state.mileage,
travel_price, wait_price,
vehicle.state.gas_price,
vehicle.state.driver_base_per_trip)
m["init_price"] = initial_price
m_commands.append(m)
# matching_charging_station
c_commands = [] # charging command
for c in charging_commands:
vehicle = VehicleRepository.get(c["vehicle_id"])
if vehicle is None:
print("Invalid Vehicle id")
continue
charging_pile = ChargingRepository.get_charging_station(
c["customer_id"])
# charging_pile = df_charging_piles["customer_id"] # return to that row
if charging_pile is None:
print("Invalid Customer id")
continue
charging_incentives = 0 # charging_pile.get_incentive()
triptime = c["duration"]
# if FLAGS.enable_pricing:
dist_to_cs = c["distance"]
total_trip_dist = dist_to_cs
[travel_price, wait_price] = vehicle.get_price_rates()
# v_cap = vehicle.state.current_capacity
initial_price = calculate_price(total_trip_dist, triptime,
vehicle.state.mile_of_range,
travel_price, wait_price,
vehicle.state.full_charge_price,
vehicle.state.driver_base_per_trip)
c["init_price"] = initial_price + charging_incentives
c_commands.append(c)
return m_commands, c_commands
def match_RS(self, current_time, vehicles, requests):
# print("SA: Inside GreedyMatching Match ", "V:", len(vehicles), "R:", len(requests))
commands = []
requestAssigned = defaultdict(list)
vehicles, cap_list = self.find_available_vehicles_RS(vehicles)
n_vehicles = len(vehicles)
# nV = 4 * len(requests)
nV = sum(cap_list) ######### Updated based on capacity
# print(nV)
if (n_vehicles > nV):
vehicles = vehicles.iloc[range(nV), :]
# print("SA: Inside GreedyMatching Match ", "V:", len(vehicles), "R:", len(requests))
if n_vehicles == 0:
return commands
# print("Available Vehicles and grid locations")
v_latlon = vehicles[["lat", "lon"]]
V = defaultdict(list)
vid2coord = {}
all_candidate_vids = []
# all_candidate_vidx = {}
# vcnt = 0
for vid, row in v_latlon.iterrows():
# print("AAAA")
# print(vehicles.loc[vid])
# print(vid, row.lon, row.lat)
coord = self.get_coord(row.lon, row.lat)
vid2coord[vid] = coord
# print(vid, coord)
V[coord].append(vid)
all_candidate_vids.append(vid)
# all_candidate_vidx[vid] = vcnt
# vcnt = vcnt+1
# print("Requests and Grid locations")
r_latlon = requests[["origin_lat", "origin_lon"]]
R = defaultdict(list)
all_target_rids = []
for rid, row in r_latlon.iterrows():
coord = self.get_coord(row.origin_lon, row.origin_lat)
# print(rid, coord)
R[coord].append(rid)
all_target_rids.append(rid)
# print("Candidate IDs: ", all_candidate_vids)
# print("Target IDs: ", all_target_rids)
# Dictionary of vehicle IDs and their index in the candidate list
all_candidate_vidx = dict(
zip(all_candidate_vids, range(len(all_candidate_vids))))
# print("All Candidates: ", all_candidate_vidx, len(all_candidate_vids))
all_target_ridx = dict(
zip(all_target_rids, range(len(all_target_rids))))
# print("All targets: ", all_target_ridx, len(all_target_rids))
target_ridx = [all_target_ridx[r] for r in all_target_rids]
reject_range = int(
self.reject_distance / self.unit_length / self.k) + 1
d_latlon = requests[["destination_lon", "destination_lat"]]
candidate_latlon = v_latlon.loc[all_candidate_vids]
# print("Cand List: ", len(candidate_latlon))
all_target_latlon = r_latlon.loc[all_target_rids]
# print("Target List: ", len(all_target_latlon))
all_destination_latlon = r_latlon.loc[all_target_rids]
T, dist = self.eta_matrix(candidate_latlon, all_target_latlon)
# print("match_D: ", dist, dist.shape)
TRR, Dist_RR = self.eta_matrix(all_target_latlon, all_target_latlon)
TDD, Dist_DD = self.eta_matrix(all_destination_latlon,
all_destination_latlon)
# for vid, row in vehicles.iterrows():
# row.earnings = 10
# print(type(row))
# print(vehicles[["id"]])
# print(vid, row.earnings, row.lon, row.lat, row.status)
for coord in self.coord_iter():
# print("SA: Inside COORD")
# print(dist.shape)
# print(T.shape)
if not R[coord]:
# print(coord, "does not exist")
continue
# print(coord, "exists")
# for i in range(int(np.ceil(len(R[coord]) / self.max_locations))):
# target_rids = R[coord][i * self.max_locations : (i + 1) * self.max_locations]
# for i in range(int(np.ceil(len(R[coord]) / self.max_locations))):
target_rids = R[coord]
# print("TR: ", target_rids)
candidate_vids = self.find_candidates(coord, len(target_rids), V,
reject_range)
# print("Cand. Vehicles: ", len(candidate_vids))
if len(candidate_vids) == 0:
continue
target_latlon = r_latlon.loc[target_rids]
candidate_vids = self.filter_candidates(
v_latlon.loc[candidate_vids], target_latlon)
# print("Filtered Vehicles: ", len(candidate_vids))
if len(candidate_vids) == 0:
continue
requestAssigned = defaultdict(list)
# All candiaidate vehicles that can pickup this specific customer
candidate_vidx = [all_candidate_vidx[v] for v in candidate_vids]
assignments = self.assign_nearest_vehicle_RideShare(
target_rids, all_target_ridx, requestAssigned, candidate_vids,
candidate_vidx, T.T, TRR, TDD, dist.T, Dist_RR, Dist_DD)
for vid, rid, tt, d in assignments:
commands.append(self.create_matching_dict(vid, rid, tt, d))
# vehicles[vid].current_capacity = vehicles[vid].current_capacity +1
# print("COORD:", coord, "V ", vid, "assigned to R", rid)
vehicle = VehicleRepository.get(vid)
# vehicle.state.current_capacity += 1
# vehicle.print_vehicle()
# print(vehicle)
# vehicles[vid].update_capacity()
# if vid in V[vid2coord[vid]]:
# V[vid2coord[vid]].remove(vid)
if vehicle.state.current_capacity >= vehicle.state.max_capacity and vid in V[
vid2coord[vid]]:
V[vid2coord[vid]].remove(vid)
return commands
def assign_nearest_vehicle_RideShare(self, request_ids, all_target_ridx,
requestAssigned, vehicle_ids,
vehicle_idx, T, TRR, TDD, dist, d_RR,
d_DD):
assignments = []
# for ri, rid in enumerate(request_ids):
# vi = T[ri,vehicle_idx].argmin()
# tt = T[ri,vehicle_idx][vi]
# for rid in request_ids:
# print(len(request_ids), type(request_ids))
# print(len(all_target_ridx), len(vehicle_ids), len(vehicle_idx))
# for ri, rid in enumerate(request_ids):
for rid in request_ids:
ri = all_target_ridx[rid]
# For this request ri, pick the min from all candidate vehicles
vi = T[ri, vehicle_idx].argmin()
tt = T[ri, vehicle_idx][vi]
# print("D: ", dist, "shape: ", dist.shape)
# print("Ri:", ri, "Vi: ", vehicle_idx, len(vehicle_idx))
# print("Filtered: ", dist[ri, vehicle_idx])
# print(type(dist))
di = dist[ri, vehicle_idx].argmin()
dd = dist[ri, vehicle_idx][di]
# else:
# dd = dist
# print(T[ri])
# print(vehicle_idx)
# print(T[ri,vehicle_idx])
# print("RTT","Ri",ri,"Vi",vi,vehicle_ids,tt)
if tt > self.reject_wait_time:
continue
vid = vehicle_ids[vi]
vi = vehicle_idx[vi]
# print("RTT","VID",vid,"Vix",vi)
vehicle = VehicleRepository.get(vid)
if (vehicle.reachedCapacity() == False):
if (len(requestAssigned[vid]) == 0):
requestAssigned[vid].append(rid)
# vehicle.state.current_capacity += 1
# print("1: ", dd)
assignments.append((vid, rid, tt, dd))
# print("TT",T[:, vi])
# print("TRR",TRR[:, ri])
T[:, vi] = T[:, vi] + TRR[:, ri]
dist[:, vi] = d_RR[:, ri]
# T[ri, vi] = T[ri, vi] + tt
# print("TTA",T[:, vi])
else:
ll = list(requestAssigned[vid])
# print("LL",ll)
ll.append(rid)
# print("RS",requestAssigned[vid])
ll_x = [all_target_ridx[r] for r in ll]
maxdd = TDD[ll_x][:, ll_x].max()
# extra_d = d_DD[ll_x][:, ll_x].max()
# print("LLAfter",ll, "Max Time",maxdd,flush=True)
if (maxdd <= self.reject_wait_time):
requestAssigned[vid].append(rid)
# vehicle.increaseCapacity()
assignments.append((vid, rid, tt, dd))
# print("Nxt: ", dd)
# print("TT",T[:, vi])
T[:, vi] = T[:, vi] + TRR[:, ri]
dist[:, vi] = d_RR[:, ri]
# T[ri, vi] = T[ri, vi] + tt
# print("TTA",T[:, vi])
else:
T[:, vi] = float('inf')
dist[:, vi] = float('inf')
return assignments