class TravelRequestsSimulator(object):
def __init__(self):
self.mongodb_database_connection = MongodbDatabaseConnection(host=mongodb_host, port=mongodb_port)
log(module_name='travel_requests_simulator', log_type='DEBUG',
log_message='mongodb_database_connection: established')
def clear_travel_requests_collection(self):
"""
Clear all the documents of the TravelRequests collection.
:return: None
"""
self.mongodb_database_connection.clear_travel_request_documents_collection()
log(module_name='travel_requests_simulator', log_type='DEBUG',
log_message='clear_travel_request_documents_collection: ok')
def delete_travel_request_documents(self, object_ids=None, client_ids=None, bus_line_ids=None,
min_departure_datetime=None, max_departure_datetime=None):
"""
Delete multiple travel_request_documents.
:param object_ids: [ObjectId]
:param client_ids: [int]
:param bus_line_ids: [int]
:param min_departure_datetime: datetime
:param max_departure_datetime
:return: None
"""
self.mongodb_database_connection.delete_travel_request_documents(
object_ids=object_ids,
client_ids=client_ids,
bus_line_ids=bus_line_ids,
min_departure_datetime=min_departure_datetime,
max_departure_datetime=max_departure_datetime
)
log(module_name='travel_requests_simulator', log_type='DEBUG',
log_message='delete_travel_request_documents: ok')
def generate_random_travel_request_documents(self, initial_datetime, min_number_of_travel_request_documents,
max_number_of_travel_request_documents):
"""
Generate random number of travel_request_documents for each bus_line,
for a 24hour period starting from a selected datetime, and store them at the
corresponding collection of the System Database.
:param initial_datetime: datetime
:param min_number_of_travel_request_documents: int
:param max_number_of_travel_request_documents: int
:return: None
"""
bus_lines = self.mongodb_database_connection.find_bus_line_documents()
for bus_line in bus_lines:
number_of_travel_request_documents = random.randint(
min_number_of_travel_request_documents,
max_number_of_travel_request_documents
)
self.generate_travel_request_documents(
initial_datetime=initial_datetime,
number_of_travel_request_documents=number_of_travel_request_documents,
bus_line=bus_line
)
def generate_travel_request_documents(self, initial_datetime, number_of_travel_request_documents,
bus_line=None, bus_line_id=None):
"""
Generate a specific number of travel_request_documents, for the selected bus_line,
for a 24hour period starting from a selected datetime, and store them at the
corresponding collection of the System Database.
:param initial_datetime: datetime
:param number_of_travel_request_documents: int
:param bus_line: bus_line_document
:param bus_line_id: int
:return: None
"""
# 1: The inputs: initial_datetime, number_of_travel_request_documents, and (bus_line or bus_line_id)
# are provided to the Travel Requests Simulator, so as a specific number of travel_request_documents
# to be generated, for the selected bus_line, for a 24hour period starting from
# the selected datetime.
#
# 2: If the provided bus_line is None, then the Travel Requests Simulator retrieves from the System Database
# the bus_line which corresponds to the provided bus_line_id.
#
if bus_line is None and bus_line_id is None:
return None
elif bus_line is None:
bus_line = self.mongodb_database_connection.find_bus_line_document(bus_line_id=bus_line_id)
else:
pass
bus_stops = bus_line.get('bus_stops')
number_of_bus_stops = len(bus_stops)
# 3: The Travel Requests Simulator generates the travel_request_documents, taking into consideration
# the variation of transportation demand during the hours of the day.
#
# distribution_weighted_datetimes = [
# (initial_datetime + timedelta(hours=0), 1),
# (initial_datetime + timedelta(hours=1), 1),
# (initial_datetime + timedelta(hours=2), 1),
# (initial_datetime + timedelta(hours=3), 1),
# (initial_datetime + timedelta(hours=4), 1),
# (initial_datetime + timedelta(hours=5), 1),
# (initial_datetime + timedelta(hours=6), 1),
# (initial_datetime + timedelta(hours=7), 1),
# (initial_datetime + timedelta(hours=8), 1),
# (initial_datetime + timedelta(hours=9), 1),
# (initial_datetime + timedelta(hours=10), 1),
# (initial_datetime + timedelta(hours=11), 1),
# (initial_datetime + timedelta(hours=12), 1),
# (initial_datetime + timedelta(hours=13), 1),
# (initial_datetime + timedelta(hours=14), 1),
# (initial_datetime + timedelta(hours=15), 1),
# (initial_datetime + timedelta(hours=16), 1),
# (initial_datetime + timedelta(hours=17), 1),
# (initial_datetime + timedelta(hours=18), 1),
# (initial_datetime + timedelta(hours=19), 1),
# (initial_datetime + timedelta(hours=20), 1),
# (initial_datetime + timedelta(hours=21), 1),
# (initial_datetime + timedelta(hours=22), 1),
# (initial_datetime + timedelta(hours=23), 1)
# ]
distribution_weighted_datetimes = [
(initial_datetime + timedelta(hours=i),
travel_requests_simulator_datetime_distribution_weights[i]) for i in range(0, 24)
]
datetime_population = [val for val, cnt in distribution_weighted_datetimes for i in range(cnt)]
travel_request_documents = []
maximum_client_id = self.mongodb_database_connection.get_maximum_or_minimum(collection='travel_request')
for i in range(0, number_of_travel_request_documents):
client_id = maximum_client_id + 1
maximum_client_id = client_id
starting_bus_stop_index = random.randint(0, number_of_bus_stops - 2)
starting_bus_stop = bus_stops[starting_bus_stop_index]
ending_bus_stop_index = random.randint(starting_bus_stop_index + 1, number_of_bus_stops - 1)
ending_bus_stop = bus_stops[ending_bus_stop_index]
additional_departure_time_interval = random.randint(0, 59)
departure_datetime = (random.choice(datetime_population) +
timedelta(minutes=additional_departure_time_interval))
travel_request_document = {
'client_id': client_id,
'bus_line_id': bus_line_id,
'starting_bus_stop': starting_bus_stop,
'ending_bus_stop': ending_bus_stop,
'departure_datetime': departure_datetime,
'arrival_datetime': None,
'starting_timetable_entry_index': None,
'ending_timetable_entry_index': None
}
travel_request_documents.append(travel_request_document)
# 4: The generated travel_request_documents are stored at the
# TravelRequests collection of the System Database.
#
self.mongodb_database_connection.insert_travel_request_documents(
travel_request_documents=travel_request_documents
)
class LookAheadHandler(object):
def __init__(self):
self.mongodb_database_connection = MongodbDatabaseConnection(host=mongodb_host, port=mongodb_port)
log(module_name='look_ahead_handler', log_type='DEBUG',
log_message='mongodb_database_connection: established')
def generate_bus_line(self, bus_stop_names, bus_line_id=None):
"""
Generate a bus_line, consisted of a bus_line_id and a list of bus_stops, and store it to the corresponding
collection of the System Database. Moreover, identify all the possible waypoints between the bus_stops
of the bus_line, and populate the BusStopWaypoints collection.
:param bus_stop_names: [string]
:param bus_line_id: int
:return: None
"""
# 1: The inputs: bus_line_id and bus_stop_names are provided to the function, so as as a bus_line
# with the corresponding bus_line_id and bus_stops to be generated.
#
# 2: The Look Ahead connects to the System Database and retrieves the bus_stops which correspond to
# the provided bus_stop_names. The function returns None and the bus_line is not generated,
# in case there is a bus_stop_name which does not correspond to a stored bus_stop.
#
if bus_line_id is None:
maximum_bus_line_id = self.mongodb_database_connection.get_maximum_or_minimum(collection='bus_line')
bus_line_id = maximum_bus_line_id + 1
bus_stops = []
for bus_stop_name in bus_stop_names:
bus_stop_document = self.mongodb_database_connection.find_bus_stop_document(name=bus_stop_name)
if bus_stop_document is None:
log_message = 'find_bus_stop_document (mongodb_database) - name:', bus_stop_name, '- result: None'
log(module_name='look_ahead_handler', log_type='DEBUG', log_message=log_message)
return None
else:
bus_stops.append(bus_stop_document)
# 3: The intermediate waypoints of the bus_routes, which are generated while combining starting and
# ending bus_stops of the bus_line, should be stored as bus_stop_waypoints_documents at the System Database.
# The Look Ahead checks the existing bus_stop_waypoints_documents and communicates with the Route Generator
# in order to identify the waypoints of the bus_routes which are not already stored. The newly generated
# bus_stop_waypoints_documents are getting stored to the corresponding collection of the System Database.
# The function returns None and the bus_line is not generated, in case the Route Generator can not identify
# a possible route in order to connect the bus_stops of the bus_line.
#
number_of_bus_stops = len(bus_stops)
for i in range(0, number_of_bus_stops - 1):
starting_bus_stop = bus_stops[i]
ending_bus_stop = bus_stops[i + 1]
bus_stop_waypoints_document = self.mongodb_database_connection.find_bus_stop_waypoints_document(
starting_bus_stop=starting_bus_stop,
ending_bus_stop=ending_bus_stop
)
if bus_stop_waypoints_document is None:
route_generator_response = get_waypoints_between_two_bus_stops(
starting_bus_stop=starting_bus_stop,
ending_bus_stop=ending_bus_stop
)
if route_generator_response is None:
log(module_name='look_ahead_handler', log_type='DEBUG',
log_message='get_waypoints_between_two_bus_stops (route_generator): None')
return None
else:
waypoints = route_generator_response.get('waypoints')
if len(waypoints) == 0:
log(module_name='look_ahead_handler', log_type='DEBUG',
log_message='get_waypoints_between_two_bus_stops (route_generator): None')
return None
lists_of_edge_object_ids = []
for list_of_edges in waypoints:
list_of_edge_object_ids = []
for edge in list_of_edges:
edge_object_id = edge.get('_id')
list_of_edge_object_ids.append(edge_object_id)
lists_of_edge_object_ids.append(list_of_edge_object_ids)
# waypoints: [[edge_object_id]]
#
waypoints = lists_of_edge_object_ids
self.mongodb_database_connection.insert_bus_stop_waypoints_document(
starting_bus_stop=starting_bus_stop,
ending_bus_stop=ending_bus_stop,
waypoints=waypoints
)
# 4: The Look Ahead stores the newly generated bus_line_document, which is consisted of the bus_line_id
# and the list of bus_stops, to the corresponding collection of the System Database.
# In case there is an already existing bus_line_document, with the same bus_line_id,
# then the list of bus_stops gets updated.
#
bus_line_document = {'bus_line_id': bus_line_id, 'bus_stops': bus_stops}
self.mongodb_database_connection.insert_bus_line_document(bus_line_document=bus_line_document)
log(module_name='look_ahead_handler', log_type='DEBUG',
log_message='insert_bus_line_document (mongodb_database): ok')
def generate_timetables_for_bus_line(self, timetables_starting_datetime, timetables_ending_datetime,
requests_min_departure_datetime, requests_max_departure_datetime,
bus_line=None, bus_line_id=None):
"""
Generate timetables for a bus_line, for a selected datetime period,
evaluating travel_requests of a specific datetime period.
- The input: timetables_starting_datetime and input: timetables_ending_datetime
are provided to the function, so as timetables for the specific datetime period
to be generated.
- The input: requests_min_departure_datetime and input: requests_max_departure_datetime
are provided to the function, so as travel_requests with departure_datetime corresponding
to the the specific datetime period to be evaluated.
- The input: bus_line or input: bus_line_id is provided to the function,
so as timetables for the specific bus_line to be generated.
:param timetables_starting_datetime: datetime
:param timetables_ending_datetime: datetime
:param requests_min_departure_datetime: datetime
:param requests_max_departure_datetime: datetime
:param bus_line: bus_line_document
:param bus_line_id: int
:return: None
"""
maximum_timetable_id_in_database = self.mongodb_database_connection.get_maximum_or_minimum(
collection='timetable'
)
# 1: The list of bus_stops corresponding to the provided bus_line is retrieved.
#
# bus_stop_document: {
# '_id', 'osm_id', 'name', 'point': {'longitude', 'latitude'}
# }
# bus_stops: [bus_stop_document]
#
if bus_line is None and bus_line_id is None:
return None
elif bus_line is None:
bus_line = self.mongodb_database_connection.find_bus_line_document(bus_line_id=bus_line_id)
else:
bus_line_id = bus_line.get('bus_line_id')
bus_stops = bus_line.get('bus_stops')
# 2: The Look Ahead retrieves from the System Database the travel_requests with
# departure_datetime higher than requests_min_departure_datetime and
# lower than requests_max_departure_datetime.
#
# travel_request_document: {
# '_id', 'client_id', 'bus_line_id',
# 'starting_bus_stop': {'_id', 'osm_id', 'name', 'point': {'longitude', 'latitude'}},
# 'ending_bus_stop': {'_id', 'osm_id', 'name', 'point': {'longitude', 'latitude'}},
# 'departure_datetime', 'arrival_datetime'
# }
# travel_requests: [travel_request_document]
#
travel_requests = self.mongodb_database_connection.find_travel_request_documents(
bus_line_ids=[bus_line_id],
min_departure_datetime=requests_min_departure_datetime,
max_departure_datetime=requests_max_departure_datetime
)
# 3: (TimetableGenerator is initialized) The Look Ahead sends a request to the Route Generator so as
# to identify the less time-consuming bus_route between the bus_stops of bus_line,
# while taking into consideration the current levels of traffic density.
#
timetable_generator = TimetableGenerator(
maximum_timetable_id_in_database=maximum_timetable_id_in_database,
bus_line_id=bus_line_id,
bus_stops=bus_stops,
travel_requests=travel_requests
)
# The list of bus_stops of a bus_line might contain the same bus_stop_osm_ids more than once.
# For this reason, each travel_request needs to be related with the correct index in the bus_stops list.
# So, the values 'starting_timetable_entry_index' and 'ending_timetable_entry_index' are estimated.
#
correspond_travel_requests_to_bus_stops(
travel_requests=timetable_generator.travel_requests,
bus_stops=timetable_generator.bus_stops
)
# 4: Based on the response of the Route Generator, which includes details about the followed bus_route,
# and using only one bus vehicle, the Look Ahead generates some initial timetables which cover the
# whole datetime period from timetables_starting_datetime to timetables_ending_datetime.
# Initially, the list of travel requests of these timetables is empty, and the departure_datetime and
# arrival_datetime values of the timetable_entries are based exclusively on the details of the bus_route.
# In the next steps of the algorithm, these timetables are used in the initial clustering
# of the travel requests.
#
timetable_generator.timetables = generate_initial_timetables(
bus_line_id=bus_line_id,
timetables_starting_datetime=timetables_starting_datetime,
timetables_ending_datetime=timetables_ending_datetime,
route_generator_response=timetable_generator.route_generator_response
)
current_average_waiting_time_of_timetables = float('Inf')
while True:
new_timetables = generate_new_timetables_based_on_travel_requests(
current_timetables=timetable_generator.timetables,
travel_requests=timetable_generator.travel_requests
)
new_average_waiting_time_of_timetables = calculate_average_waiting_time_of_timetables_in_seconds(
timetables=new_timetables
)
if new_average_waiting_time_of_timetables < current_average_waiting_time_of_timetables:
timetable_generator.timetables = new_timetables
current_average_waiting_time_of_timetables = new_average_waiting_time_of_timetables
print_timetables(timetables=timetable_generator.timetables)
else:
break
print_timetables(timetables=timetable_generator.timetables)
self.mongodb_database_connection.delete_timetable_documents(
bus_line_id=bus_line.get('bus_line_id')
)
self.mongodb_database_connection.insert_timetable_documents(
timetable_documents=timetable_generator.timetables
)
log(module_name='look_ahead_handler', log_type='DEBUG',
log_message='insert_timetable_documents (mongodb_database): ok')
def generate_timetables_for_bus_lines(self, timetables_starting_datetime, timetables_ending_datetime,
requests_min_departure_datetime, requests_max_departure_datetime):
"""
Generate timetables for all bus_lines, for a selected datetime period,
evaluating travel_requests of a specific datetime period.
:param timetables_starting_datetime: datetime
:param timetables_ending_datetime: datetime
:param requests_min_departure_datetime: datetime
:param requests_max_departure_datetime: datetime
:return: None
"""
bus_lines = self.mongodb_database_connection.find_bus_line_documents()
for bus_line in bus_lines:
self.generate_timetables_for_bus_line(
bus_line=bus_line,
timetables_starting_datetime=timetables_starting_datetime,
timetables_ending_datetime=timetables_ending_datetime,
requests_min_departure_datetime=requests_min_departure_datetime,
requests_max_departure_datetime=requests_max_departure_datetime
)
def update_timetables_of_bus_line(self, bus_line=None, bus_line_id=None):
"""
Update the timetables of a bus_line, taking into consideration the current levels of traffic_density.
:param bus_line: bus_line_document
:param bus_line_id: int
:return: None
"""
if bus_line is None and bus_line_id is None:
return None
elif bus_line is None:
bus_line = self.mongodb_database_connection.find_bus_line_document(bus_line_id=bus_line_id)
else:
bus_line_id = bus_line.get('bus_line_id')
bus_stops = bus_line.get('bus_stops')
timetables = self.mongodb_database_connection.find_timetable_documents(bus_line_ids=[bus_line_id])
travel_requests = get_travel_requests_of_timetables(timetables=timetables)
timetable_updater = TimetableUpdater(
bus_stops=bus_stops,
timetables=timetables,
travel_requests=travel_requests
)
update_entries_of_timetables(
timetables=timetable_updater.timetables,
route_generator_response=timetable_updater.route_generator_response
)
current_average_waiting_time_of_timetables = calculate_average_waiting_time_of_timetables_in_seconds(
timetables=timetable_updater.timetables
)
print_timetables(timetables=timetable_updater.timetables)
while True:
new_timetables = generate_new_timetables_based_on_travel_requests(
current_timetables=timetable_updater.timetables,
travel_requests=timetable_updater.travel_requests
)
new_average_waiting_time_of_timetables = calculate_average_waiting_time_of_timetables_in_seconds(
timetables=new_timetables
)
if new_average_waiting_time_of_timetables < current_average_waiting_time_of_timetables:
timetable_updater.timetables = new_timetables
current_average_waiting_time_of_timetables = new_average_waiting_time_of_timetables
print_timetables(timetables=timetable_updater.timetables)
else:
break
print_timetables(timetables=timetable_updater.timetables)
self.mongodb_database_connection.delete_timetable_documents(
bus_line_id=bus_line.get('bus_line_id')
)
self.mongodb_database_connection.insert_timetable_documents(
timetable_documents=timetable_updater.timetables
)
log(module_name='look_ahead_handler', log_type='DEBUG',
log_message='update_timetable_documents (mongodb_database): ok')
def update_timetables_of_bus_lines(self):
"""
Update the timetables of all bus_lines, taking into consideration the current levels of traffic_density.
:return: None
"""
bus_lines = self.mongodb_database_connection.find_bus_line_documents()
for bus_line in bus_lines:
self.update_timetables_of_bus_line(bus_line=bus_line)
class LookAheadHandler(object):
def __init__(self):
self.mongodb_database_connection = MongodbDatabaseConnection(
host=mongodb_host, port=mongodb_port)
log(module_name='look_ahead_handler',
log_type='DEBUG',
log_message='mongodb_database_connection: established')
def generate_bus_line(self, bus_stop_names, bus_line_id=None):
"""
Generate a bus_line, consisted of a bus_line_id and a list of bus_stops, and store it to the corresponding
collection of the System Database. Moreover, identify all the possible waypoints between the bus_stops
of the bus_line, and populate the BusStopWaypoints collection.
:param bus_stop_names: [string]
:param bus_line_id: int
:return: None
"""
# 1: The inputs: bus_line_id and bus_stop_names are provided to the function, so as as a bus_line
# with the corresponding bus_line_id and bus_stops to be generated.
#
# 2: The Look Ahead connects to the System Database and retrieves the bus_stops which correspond to
# the provided bus_stop_names. The function returns None and the bus_line is not generated,
# in case there is a bus_stop_name which does not correspond to a stored bus_stop.
#
if bus_line_id is None:
maximum_bus_line_id = self.mongodb_database_connection.get_maximum_or_minimum(
collection='bus_line')
bus_line_id = maximum_bus_line_id + 1
bus_stops = []
for bus_stop_name in bus_stop_names:
bus_stop_document = self.mongodb_database_connection.find_bus_stop_document(
name=bus_stop_name)
if bus_stop_document is None:
log_message = 'find_bus_stop_document (mongodb_database) - name:', bus_stop_name, '- result: None'
log(module_name='look_ahead_handler',
log_type='DEBUG',
log_message=log_message)
return None
else:
bus_stops.append(bus_stop_document)
# 3: The intermediate waypoints of the bus_routes, which are generated while combining starting and
# ending bus_stops of the bus_line, should be stored as bus_stop_waypoints_documents at the System Database.
# The Look Ahead checks the existing bus_stop_waypoints_documents and communicates with the Route Generator
# in order to identify the waypoints of the bus_routes which are not already stored. The newly generated
# bus_stop_waypoints_documents are getting stored to the corresponding collection of the System Database.
# The function returns None and the bus_line is not generated, in case the Route Generator can not identify
# a possible route in order to connect the bus_stops of the bus_line.
#
number_of_bus_stops = len(bus_stops)
for i in range(0, number_of_bus_stops - 1):
starting_bus_stop = bus_stops[i]
ending_bus_stop = bus_stops[i + 1]
bus_stop_waypoints_document = self.mongodb_database_connection.find_bus_stop_waypoints_document(
starting_bus_stop=starting_bus_stop,
ending_bus_stop=ending_bus_stop)
if bus_stop_waypoints_document is None:
route_generator_response = get_waypoints_between_two_bus_stops(
starting_bus_stop=starting_bus_stop,
ending_bus_stop=ending_bus_stop)
if route_generator_response is None:
log(module_name='look_ahead_handler',
log_type='DEBUG',
log_message=
'get_waypoints_between_two_bus_stops (route_generator): None'
)
return None
else:
waypoints = route_generator_response.get('waypoints')
if len(waypoints) == 0:
log(module_name='look_ahead_handler',
log_type='DEBUG',
log_message=
'get_waypoints_between_two_bus_stops (route_generator): None'
)
return None
lists_of_edge_object_ids = []
for list_of_edges in waypoints:
list_of_edge_object_ids = []
for edge in list_of_edges:
edge_object_id = edge.get('_id')
list_of_edge_object_ids.append(edge_object_id)
lists_of_edge_object_ids.append(
list_of_edge_object_ids)
# waypoints: [[edge_object_id]]
#
waypoints = lists_of_edge_object_ids
self.mongodb_database_connection.insert_bus_stop_waypoints_document(
starting_bus_stop=starting_bus_stop,
ending_bus_stop=ending_bus_stop,
waypoints=waypoints)
# 4: The Look Ahead stores the newly generated bus_line_document, which is consisted of the bus_line_id
# and the list of bus_stops, to the corresponding collection of the System Database.
# In case there is an already existing bus_line_document, with the same bus_line_id,
# then the list of bus_stops gets updated.
#
bus_line_document = {
'bus_line_id': bus_line_id,
'bus_stops': bus_stops
}
self.mongodb_database_connection.insert_bus_line_document(
bus_line_document=bus_line_document)
log(module_name='look_ahead_handler',
log_type='DEBUG',
log_message='insert_bus_line_document (mongodb_database): ok')
def generate_timetables_for_bus_line(self,
timetables_starting_datetime,
timetables_ending_datetime,
requests_min_departure_datetime,
requests_max_departure_datetime,
bus_line=None,
bus_line_id=None):
"""
Generate timetables for a bus_line, for a selected datetime period,
evaluating travel_requests of a specific datetime period.
- The input: timetables_starting_datetime and input: timetables_ending_datetime
are provided to the function, so as timetables for the specific datetime period
to be generated.
- The input: requests_min_departure_datetime and input: requests_max_departure_datetime
are provided to the function, so as travel_requests with departure_datetime corresponding
to the the specific datetime period to be evaluated.
- The input: bus_line or input: bus_line_id is provided to the function,
so as timetables for the specific bus_line to be generated.
:param timetables_starting_datetime: datetime
:param timetables_ending_datetime: datetime
:param requests_min_departure_datetime: datetime
:param requests_max_departure_datetime: datetime
:param bus_line: bus_line_document
:param bus_line_id: int
:return: None
"""
maximum_timetable_id_in_database = self.mongodb_database_connection.get_maximum_or_minimum(
collection='timetable')
# 1: The list of bus_stops corresponding to the provided bus_line is retrieved.
#
# bus_stop_document: {
# '_id', 'osm_id', 'name', 'point': {'longitude', 'latitude'}
# }
# bus_stops: [bus_stop_document]
#
if bus_line is None and bus_line_id is None:
return None
elif bus_line is None:
bus_line = self.mongodb_database_connection.find_bus_line_document(
bus_line_id=bus_line_id)
else:
bus_line_id = bus_line.get('bus_line_id')
bus_stops = bus_line.get('bus_stops')
# 2: The Look Ahead retrieves from the System Database the travel_requests with
# departure_datetime higher than requests_min_departure_datetime and
# lower than requests_max_departure_datetime.
#
# travel_request_document: {
# '_id', 'client_id', 'bus_line_id',
# 'starting_bus_stop': {'_id', 'osm_id', 'name', 'point': {'longitude', 'latitude'}},
# 'ending_bus_stop': {'_id', 'osm_id', 'name', 'point': {'longitude', 'latitude'}},
# 'departure_datetime', 'arrival_datetime'
# }
# travel_requests: [travel_request_document]
#
travel_requests = self.mongodb_database_connection.find_travel_request_documents(
bus_line_ids=[bus_line_id],
min_departure_datetime=requests_min_departure_datetime,
max_departure_datetime=requests_max_departure_datetime)
# 3: (TimetableGenerator is initialized) The Look Ahead sends a request to the Route Generator so as
# to identify the less time-consuming bus_route between the bus_stops of bus_line,
# while taking into consideration the current levels of traffic density.
#
timetable_generator = TimetableGenerator(
maximum_timetable_id_in_database=maximum_timetable_id_in_database,
bus_line_id=bus_line_id,
bus_stops=bus_stops,
travel_requests=travel_requests)
# The list of bus_stops of a bus_line might contain the same bus_stop_osm_ids more than once.
# For this reason, each travel_request needs to be related with the correct index in the bus_stops list.
# So, the values 'starting_timetable_entry_index' and 'ending_timetable_entry_index' are estimated.
#
correspond_travel_requests_to_bus_stops(
travel_requests=timetable_generator.travel_requests,
bus_stops=timetable_generator.bus_stops)
# 4: Based on the response of the Route Generator, which includes details about the followed bus_route,
# and using only one bus vehicle, the Look Ahead generates some initial timetables which cover the
# whole datetime period from timetables_starting_datetime to timetables_ending_datetime.
# Initially, the list of travel requests of these timetables is empty, and the departure_datetime and
# arrival_datetime values of the timetable_entries are based exclusively on the details of the bus_route.
# In the next steps of the algorithm, these timetables are used in the initial clustering
# of the travel requests.
#
timetable_generator.timetables = generate_initial_timetables(
bus_line_id=bus_line_id,
timetables_starting_datetime=timetables_starting_datetime,
timetables_ending_datetime=timetables_ending_datetime,
route_generator_response=timetable_generator.
route_generator_response)
current_average_waiting_time_of_timetables = float('Inf')
while True:
new_timetables = generate_new_timetables_based_on_travel_requests(
current_timetables=timetable_generator.timetables,
travel_requests=timetable_generator.travel_requests)
new_average_waiting_time_of_timetables = calculate_average_waiting_time_of_timetables_in_seconds(
timetables=new_timetables)
if new_average_waiting_time_of_timetables < current_average_waiting_time_of_timetables:
timetable_generator.timetables = new_timetables
current_average_waiting_time_of_timetables = new_average_waiting_time_of_timetables
print_timetables(timetables=timetable_generator.timetables)
else:
break
print_timetables(timetables=timetable_generator.timetables)
self.mongodb_database_connection.delete_timetable_documents(
bus_line_id=bus_line.get('bus_line_id'))
self.mongodb_database_connection.insert_timetable_documents(
timetable_documents=timetable_generator.timetables)
log(module_name='look_ahead_handler',
log_type='DEBUG',
log_message='insert_timetable_documents (mongodb_database): ok')
def generate_timetables_for_bus_lines(self, timetables_starting_datetime,
timetables_ending_datetime,
requests_min_departure_datetime,
requests_max_departure_datetime):
"""
Generate timetables for all bus_lines, for a selected datetime period,
evaluating travel_requests of a specific datetime period.
:param timetables_starting_datetime: datetime
:param timetables_ending_datetime: datetime
:param requests_min_departure_datetime: datetime
:param requests_max_departure_datetime: datetime
:return: None
"""
bus_lines = self.mongodb_database_connection.find_bus_line_documents()
for bus_line in bus_lines:
self.generate_timetables_for_bus_line(
bus_line=bus_line,
timetables_starting_datetime=timetables_starting_datetime,
timetables_ending_datetime=timetables_ending_datetime,
requests_min_departure_datetime=requests_min_departure_datetime,
requests_max_departure_datetime=requests_max_departure_datetime
)
def update_timetables_of_bus_line(self, bus_line=None, bus_line_id=None):
"""
Update the timetables of a bus_line, taking into consideration the current levels of traffic_density.
:param bus_line: bus_line_document
:param bus_line_id: int
:return: None
"""
if bus_line is None and bus_line_id is None:
return None
elif bus_line is None:
bus_line = self.mongodb_database_connection.find_bus_line_document(
bus_line_id=bus_line_id)
else:
bus_line_id = bus_line.get('bus_line_id')
bus_stops = bus_line.get('bus_stops')
timetables = self.mongodb_database_connection.find_timetable_documents(
bus_line_ids=[bus_line_id])
travel_requests = get_travel_requests_of_timetables(
timetables=timetables)
timetable_updater = TimetableUpdater(bus_stops=bus_stops,
timetables=timetables,
travel_requests=travel_requests)
update_entries_of_timetables(
timetables=timetable_updater.timetables,
route_generator_response=timetable_updater.route_generator_response
)
current_average_waiting_time_of_timetables = calculate_average_waiting_time_of_timetables_in_seconds(
timetables=timetable_updater.timetables)
print_timetables(timetables=timetable_updater.timetables)
while True:
new_timetables = generate_new_timetables_based_on_travel_requests(
current_timetables=timetable_updater.timetables,
travel_requests=timetable_updater.travel_requests)
new_average_waiting_time_of_timetables = calculate_average_waiting_time_of_timetables_in_seconds(
timetables=new_timetables)
if new_average_waiting_time_of_timetables < current_average_waiting_time_of_timetables:
timetable_updater.timetables = new_timetables
current_average_waiting_time_of_timetables = new_average_waiting_time_of_timetables
print_timetables(timetables=timetable_updater.timetables)
else:
break
print_timetables(timetables=timetable_updater.timetables)
self.mongodb_database_connection.delete_timetable_documents(
bus_line_id=bus_line.get('bus_line_id'))
self.mongodb_database_connection.insert_timetable_documents(
timetable_documents=timetable_updater.timetables)
log(module_name='look_ahead_handler',
log_type='DEBUG',
log_message='update_timetable_documents (mongodb_database): ok')
def update_timetables_of_bus_lines(self):
"""
Update the timetables of all bus_lines, taking into consideration the current levels of traffic_density.
:return: None
"""
bus_lines = self.mongodb_database_connection.find_bus_line_documents()
for bus_line in bus_lines:
self.update_timetables_of_bus_line(bus_line=bus_line)
class TravelRequestsSimulator(object):
def __init__(self):
self.mongodb_database_connection = MongodbDatabaseConnection(host=mongodb_host, port=mongodb_port)
log(
module_name="travel_requests_simulator",
log_type="DEBUG",
log_message="mongodb_database_connection: established",
)
def clear_travel_requests_collection(self):
"""
Clear all the documents of the TravelRequests collection.
:return: None
"""
self.mongodb_database_connection.clear_travel_request_documents_collection()
log(
module_name="travel_requests_simulator",
log_type="DEBUG",
log_message="clear_travel_request_documents_collection: ok",
)
def delete_travel_request_documents(
self, object_ids=None, client_ids=None, line_ids=None, min_departure_datetime=None, max_departure_datetime=None
):
"""
Delete multiple travel_request_documents.
travel_request_document: {
'_id', 'client_id', 'line_id',
'starting_bus_stop': {'_id', 'osm_id', 'name', 'point': {'longitude', 'latitude'}},
'ending_bus_stop': {'_id', 'osm_id', 'name', 'point': {'longitude', 'latitude'}},
'departure_datetime', 'arrival_datetime',
'starting_timetable_entry_index', 'ending_timetable_entry_index'
}
:param object_ids: [ObjectId]
:param client_ids: [int]
:param line_ids: [int]
:param min_departure_datetime: datetime
:param max_departure_datetime
:return: None
"""
self.mongodb_database_connection.delete_travel_request_documents(
object_ids=object_ids,
client_ids=client_ids,
line_ids=line_ids,
min_departure_datetime=min_departure_datetime,
max_departure_datetime=max_departure_datetime,
)
log(
module_name="travel_requests_simulator", log_type="DEBUG", log_message="delete_travel_request_documents: ok"
)
def generate_random_travel_request_documents(
self, initial_datetime, min_number_of_travel_request_documents, max_number_of_travel_request_documents
):
"""
Generate random number of travel_request_documents for each bus_line,
for a 24hour period starting from a selected datetime, and store them at the
corresponding collection of the System Database.
bus_line_document: {
'_id', 'line_id', 'bus_stops': [{'_id', 'osm_id', 'name', 'point': {'longitude', 'latitude'}}]
}
:param initial_datetime: datetime
:param min_number_of_travel_request_documents: int
:param max_number_of_travel_request_documents: int
:return: None
"""
bus_lines = self.mongodb_database_connection.find_bus_line_documents()
for bus_line in bus_lines:
number_of_travel_request_documents = random.randint(
min_number_of_travel_request_documents, max_number_of_travel_request_documents
)
self.generate_travel_request_documents(
initial_datetime=initial_datetime,
number_of_travel_request_documents=number_of_travel_request_documents,
bus_line=bus_line,
)
def generate_travel_request_documents(
self, initial_datetime, number_of_travel_request_documents, bus_line=None, line_id=None
):
"""
Generate a specific number of travel_request_documents, for the selected bus_line,
for a 24hour period starting from a selected datetime, and store them at the
corresponding collection of the System Database.
bus_line_document: {
'_id', 'line_id', 'bus_stops': [{'_id', 'osm_id', 'name', 'point': {'longitude', 'latitude'}}]
}
:param initial_datetime: datetime
:param number_of_travel_request_documents: int
:param bus_line: bus_line_document
:param line_id: int
:return: None
"""
# 1: The inputs: initial_datetime, number_of_travel_request_documents, and (bus_line or line_id)
# are provided to the Travel Requests Simulator, so as a specific number of travel_request_documents
# to be generated, for the selected bus_line, for a 24hour period starting from
# the selected datetime.
#
# 2: If the provided bus_line is None, then the Travel Requests Simulator retrieves from the System Database
# the bus_line which corresponds to the provided line_id.
#
if bus_line is None and line_id is None:
return None
elif bus_line is None:
bus_line = self.mongodb_database_connection.find_bus_line_document(line_id=line_id)
else:
pass
bus_stops = bus_line.get("bus_stops")
number_of_bus_stops = len(bus_stops)
# 3: The Travel Requests Simulator generates the travel_request_documents, taking into consideration
# the variation of transportation demand during the hours of the day.
#
weighted_datetimes = [
(initial_datetime + timedelta(hours=0), 1),
(initial_datetime + timedelta(hours=1), 1),
(initial_datetime + timedelta(hours=2), 1),
(initial_datetime + timedelta(hours=3), 1),
(initial_datetime + timedelta(hours=4), 1),
(initial_datetime + timedelta(hours=5), 1),
(initial_datetime + timedelta(hours=6), 1),
(initial_datetime + timedelta(hours=7), 1),
(initial_datetime + timedelta(hours=8), 1),
(initial_datetime + timedelta(hours=9), 1),
(initial_datetime + timedelta(hours=10), 1),
(initial_datetime + timedelta(hours=11), 1),
(initial_datetime + timedelta(hours=12), 1),
(initial_datetime + timedelta(hours=13), 1),
(initial_datetime + timedelta(hours=14), 1),
(initial_datetime + timedelta(hours=15), 1),
(initial_datetime + timedelta(hours=16), 1),
(initial_datetime + timedelta(hours=17), 1),
(initial_datetime + timedelta(hours=18), 1),
(initial_datetime + timedelta(hours=19), 1),
(initial_datetime + timedelta(hours=20), 1),
(initial_datetime + timedelta(hours=21), 1),
(initial_datetime + timedelta(hours=22), 1),
(initial_datetime + timedelta(hours=23), 1),
]
datetime_population = [val for val, cnt in weighted_datetimes for i in range(cnt)]
travel_request_documents = []
for i in range(0, number_of_travel_request_documents):
client_id = i
starting_bus_stop_index = random.randint(0, number_of_bus_stops - 2)
starting_bus_stop = bus_stops[starting_bus_stop_index]
ending_bus_stop_index = random.randint(starting_bus_stop_index + 1, number_of_bus_stops - 1)
ending_bus_stop = bus_stops[ending_bus_stop_index]
additional_departure_time_interval = random.randint(0, 59)
departure_datetime = random.choice(datetime_population) + timedelta(
minutes=additional_departure_time_interval
)
travel_request_document = {
"client_id": client_id,
"line_id": line_id,
"starting_bus_stop": starting_bus_stop,
"ending_bus_stop": ending_bus_stop,
"departure_datetime": departure_datetime,
"arrival_datetime": None,
"starting_timetable_entry_index": None,
"ending_timetable_entry_index": None,
}
travel_request_documents.append(travel_request_document)
# 4: The generated travel_request_documents are stored at the
# TravelRequests collection of the System Database.
#
self.mongodb_database_connection.insert_travel_request_documents(
travel_request_documents=travel_request_documents
)
class TravelRequestsSimulator(object):
def __init__(self):
self.mongodb_database_connection = MongodbDatabaseConnection(
host=mongodb_host, port=mongodb_port)
log(module_name='travel_requests_simulator',
log_type='DEBUG',
log_message='mongodb_database_connection: established')
def clear_travel_requests_collection(self):
"""
Clear all the documents of the TravelRequests collection.
:return: None
"""
self.mongodb_database_connection.clear_travel_request_documents_collection(
)
log(module_name='travel_requests_simulator',
log_type='DEBUG',
log_message='clear_travel_request_documents_collection: ok')
def delete_travel_request_documents(self,
object_ids=None,
client_ids=None,
bus_line_ids=None,
min_departure_datetime=None,
max_departure_datetime=None):
"""
Delete multiple travel_request_documents.
:param object_ids: [ObjectId]
:param client_ids: [int]
:param bus_line_ids: [int]
:param min_departure_datetime: datetime
:param max_departure_datetime
:return: None
"""
self.mongodb_database_connection.delete_travel_request_documents(
object_ids=object_ids,
client_ids=client_ids,
bus_line_ids=bus_line_ids,
min_departure_datetime=min_departure_datetime,
max_departure_datetime=max_departure_datetime)
log(module_name='travel_requests_simulator',
log_type='DEBUG',
log_message='delete_travel_request_documents: ok')
def generate_random_travel_request_documents(
self, initial_datetime, min_number_of_travel_request_documents,
max_number_of_travel_request_documents):
"""
Generate random number of travel_request_documents for each bus_line,
for a 24hour period starting from a selected datetime, and store them at the
corresponding collection of the System Database.
:param initial_datetime: datetime
:param min_number_of_travel_request_documents: int
:param max_number_of_travel_request_documents: int
:return: None
"""
bus_lines = self.mongodb_database_connection.find_bus_line_documents()
for bus_line in bus_lines:
number_of_travel_request_documents = random.randint(
min_number_of_travel_request_documents,
max_number_of_travel_request_documents)
self.generate_travel_request_documents(
initial_datetime=initial_datetime,
number_of_travel_request_documents=
number_of_travel_request_documents,
bus_line=bus_line)
def generate_travel_request_documents(self,
initial_datetime,
number_of_travel_request_documents,
bus_line=None,
bus_line_id=None):
"""
Generate a specific number of travel_request_documents, for the selected bus_line,
for a 24hour period starting from a selected datetime, and store them at the
corresponding collection of the System Database.
:param initial_datetime: datetime
:param number_of_travel_request_documents: int
:param bus_line: bus_line_document
:param bus_line_id: int
:return: None
"""
# 1: The inputs: initial_datetime, number_of_travel_request_documents, and (bus_line or bus_line_id)
# are provided to the Travel Requests Simulator, so as a specific number of travel_request_documents
# to be generated, for the selected bus_line, for a 24hour period starting from
# the selected datetime.
#
# 2: If the provided bus_line is None, then the Travel Requests Simulator retrieves from the System Database
# the bus_line which corresponds to the provided bus_line_id.
#
if bus_line is None and bus_line_id is None:
return None
elif bus_line is None:
bus_line = self.mongodb_database_connection.find_bus_line_document(
bus_line_id=bus_line_id)
else:
pass
bus_stops = bus_line.get('bus_stops')
number_of_bus_stops = len(bus_stops)
# 3: The Travel Requests Simulator generates the travel_request_documents, taking into consideration
# the variation of transportation demand during the hours of the day.
#
# distribution_weighted_datetimes = [
# (initial_datetime + timedelta(hours=0), 1),
# (initial_datetime + timedelta(hours=1), 1),
# (initial_datetime + timedelta(hours=2), 1),
# (initial_datetime + timedelta(hours=3), 1),
# (initial_datetime + timedelta(hours=4), 1),
# (initial_datetime + timedelta(hours=5), 1),
# (initial_datetime + timedelta(hours=6), 1),
# (initial_datetime + timedelta(hours=7), 1),
# (initial_datetime + timedelta(hours=8), 1),
# (initial_datetime + timedelta(hours=9), 1),
# (initial_datetime + timedelta(hours=10), 1),
# (initial_datetime + timedelta(hours=11), 1),
# (initial_datetime + timedelta(hours=12), 1),
# (initial_datetime + timedelta(hours=13), 1),
# (initial_datetime + timedelta(hours=14), 1),
# (initial_datetime + timedelta(hours=15), 1),
# (initial_datetime + timedelta(hours=16), 1),
# (initial_datetime + timedelta(hours=17), 1),
# (initial_datetime + timedelta(hours=18), 1),
# (initial_datetime + timedelta(hours=19), 1),
# (initial_datetime + timedelta(hours=20), 1),
# (initial_datetime + timedelta(hours=21), 1),
# (initial_datetime + timedelta(hours=22), 1),
# (initial_datetime + timedelta(hours=23), 1)
# ]
distribution_weighted_datetimes = [
(initial_datetime + timedelta(hours=i),
travel_requests_simulator_datetime_distribution_weights[i])
for i in range(0, 24)
]
datetime_population = [
val for val, cnt in distribution_weighted_datetimes
for i in range(cnt)
]
travel_request_documents = []
maximum_client_id = self.mongodb_database_connection.get_maximum_or_minimum(
collection='travel_request')
for i in range(0, number_of_travel_request_documents):
client_id = maximum_client_id + 1
maximum_client_id = client_id
starting_bus_stop_index = random.randint(0,
number_of_bus_stops - 2)
starting_bus_stop = bus_stops[starting_bus_stop_index]
ending_bus_stop_index = random.randint(starting_bus_stop_index + 1,
number_of_bus_stops - 1)
ending_bus_stop = bus_stops[ending_bus_stop_index]
additional_departure_time_interval = random.randint(0, 59)
departure_datetime = (
random.choice(datetime_population) +
timedelta(minutes=additional_departure_time_interval))
travel_request_document = {
'client_id': client_id,
'bus_line_id': bus_line_id,
'starting_bus_stop': starting_bus_stop,
'ending_bus_stop': ending_bus_stop,
'departure_datetime': departure_datetime,
'arrival_datetime': None,
'starting_timetable_entry_index': None,
'ending_timetable_entry_index': None
}
travel_request_documents.append(travel_request_document)
# 4: The generated travel_request_documents are stored at the
# TravelRequests collection of the System Database.
#
self.mongodb_database_connection.insert_travel_request_documents(
travel_request_documents=travel_request_documents)