WO2023170964A1 - Vehicle service planning device, vehicle service planning assistance method, and program - Google Patents
Vehicle service planning device, vehicle service planning assistance method, and program Download PDFInfo
- Publication number
- WO2023170964A1 WO2023170964A1 PCT/JP2022/011088 JP2022011088W WO2023170964A1 WO 2023170964 A1 WO2023170964 A1 WO 2023170964A1 JP 2022011088 W JP2022011088 W JP 2022011088W WO 2023170964 A1 WO2023170964 A1 WO 2023170964A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- people
- route
- stop
- passengers
- vehicle
- Prior art date
Links
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/123—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
- G08G1/127—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams to a central station ; Indicators in a central station
Definitions
- the present disclosure relates to a vehicle operation planning device, a vehicle operation planning support method, and a program.
- Non-Patent Document 1 a technique has been proposed that minimizes the travel distance of buses. Furthermore, a technology has been proposed that sequentially observes demand and learns an optimal bus operation plan (Non-Patent Document 2).
- Patent Document 1 a technology has also been proposed in which the number of people in a queue at a bus stop is observed using a surveillance camera and used for bus operation planning.
- Non-Patent Document 1 calculates a bus operation plan that minimizes the bus travel distance in relation to passenger demand, it is difficult to grasp the actual demand in advance. Furthermore, although the technology disclosed in Non-Patent Document 2 sequentially observes passenger demand and determines a bus operation plan that minimizes the bus travel distance, it is not possible to minimize passenger waiting time. Further, although the technology disclosed in Patent Document 1 allows the number of people in a queue at a bus stop to be observed using a surveillance camera, it is not possible to update the bus operation plan based on the number of people in the queue.
- the present invention has been made in view of the above points, and provides a bus etc. that minimizes the sum of the cost of the operating company of the bus etc. and the cost of the passengers including waiting time at the bus stop.
- the purpose is to create a vehicle operation plan.
- the invention according to claim 1 is a vehicle operation planning device that plans vehicle operations, which includes the number of people in a queue at each stop at the current observed time for each route of vehicles, and the current time from the first train. Waiting to estimate the number of people who selected routes for each route of vehicles at each stop, aggregated by departure point and destination, from the sum of the cumulative number of passengers up until now and the number of people who selected routes in the operation plan at the previous observation time.
- the operating company of the vehicle and the number of passengers are determined based on the number of people in line estimating the number of passengers, the predicted number of passengers expected after the current observation time, and the number of people selected on the route at the current observation time estimated by the number of people in line estimating the number of passengers in the queue.
- This is a vehicle operation planning device that includes an operation plan creation section that creates an operation plan assuming that the vehicle will act rationally after the current observation time.
- the present invention by considering the actual number of people in the queue, the sum of the cost of the vehicle operating company and the cost of passengers including waiting time at the stop can be minimized. This has the effect that a vehicle operation plan can be created.
- FIG. 1 is a schematic diagram of a communication system 1 in an embodiment of the present invention.
- FIG. 1 is a hardware configuration diagram of a bus operation planning device according to an embodiment. It is a functional block diagram of the bus operation planning device in an embodiment. It is a conceptual diagram which shows the table which comprises a stop DB, and which shows the table which manages the upper limit of the number of stops of each stop. It is a conceptual diagram which shows the table which comprises a stop DB, and which shows the table which manages a bus boarding time queue. It is a conceptual diagram which shows the table which comprises a stop DB, and which shows the table which manages a penalty matrix (d).
- d penalty matrix
- FIG. 3 is a sequence diagram showing a distribution process of operation plan data. It is a flowchart which shows the preparation process of an operation plan. It is a flowchart which shows the preparation process of an operation plan. FIG. 3 is a diagram showing an objective function expressed as an integer linear programming problem.
- FIG. 2 is a diagram showing constraint conditions expressed as an integer linear programming problem.
- FIG. 2 is a diagram showing constraint conditions expressed as an integer linear programming problem.
- FIG. 2 is a diagram showing constraint conditions expressed as an integer linear programming problem. It is a diagram explaining variables. It is a diagram showing a passenger's route selection plan (variable z). It is a diagram showing a matrix number planning (variable w). It is a diagram showing a bus route operation plan (variable V).
- (a) is a diagram showing one item (record) of the number of people in queue DB
- (b) is a diagram showing the cumulative total in one item (record) of the number of passengers DB
- (c) is the optimization result at time (t-1)
- (d) is a diagram showing the estimation result of the number of people in the queue at time (t).
- FIG. 1 is a schematic diagram of a communication system 1 in an embodiment of the present invention.
- the communication system 1 is constructed by a bus operation planning device 2, sensors 6a, 6b, and a communication terminal 9.
- the bus operation planning device 2 is a device that plans on-demand bus operations, which are expected to develop in the future.
- On-demand bus service differs from the conventional bus service, which operates on a fixed route at a predetermined time (strictly speaking, at a "date and time"), by taking into account the number of people queuing at a stop in real time. This is a method to flexibly increase or decrease the number of buses on specific routes.
- the bus operation planning device 2 of this embodiment not only considers the number of people waiting in a queue for a predetermined route at a stop, but also takes into account the personnel costs of the bus company, the fuel costs of the bus, etc., and makes a comprehensive judgment. Create a bus schedule.
- the bus operation planning device 2 is an example of a vehicle operation planning device. In the future, vehicles will also include on-demand taxis, etc., which will provide services such as driving in predetermined alleys.
- a signpost 5a for a route bound for a and a signpost 5b for a route bound for b are installed. Further, the signpost 5a is provided with a sensor 6a for observing the number of people in the queue for the route bound for a. Similarly, the signpost 5b is provided with a sensor 6b for observing the number of people in the queue for the line bound for b. Each sensor 6a, 6b transmits data indicating the number of people in each queue to the bus operation planning device 2 in real time via a communication network 100 such as the Internet. Manage the number of people in line.
- a bus 8 is waiting at the office 7 of the bus operating company, and the bus 8 is equipped with a communication terminal 9.
- the communication terminal 9 receives the data of the operation plan according to the bus operation plan from the bus operation planning device 2 via the communication network 100, so that the bus 8 departs from the office 7 at the time according to the operation plan, Operate routes according to the operation plan.
- any one of the plurality of signposts 5a, 5b, etc. will be referred to as a "signpost 5.”
- any sensor among the plurality of sensors 6a, 6b, etc. will be referred to as “sensor 6”.
- FIG. 1 for convenience of explanation, one bus operation planning device 2 is shown, but there may be a plurality of bus operation planning devices. However, even if there is a plurality of bus operation planning devices, they will be collectively referred to as the bus operation planning device 2.
- one stop 4 is shown in FIG. 1, there are actually multiple stops. Furthermore, in FIG. 1, one stop 4 has two route sign posts 5a and 5b installed, but one stop may have one route sign post, and one stop 4 has two route sign posts 5a and 5b installed. There may be three or more route signposts installed. The number of sensors 6 increases or decreases according to the number of signposts 5. Further, although FIG. 1 shows a case where one bus 8 is waiting at one business office 7, a plurality of buses may be waiting. Each of the multiple buses is equipped with a communication terminal.
- the communication terminal 9 may not be installed on the bus 8, but may be installed in the administrative office of the business office 7, etc. In this case, the office manager informs the bus driver of the bus's departure time and route.
- FIG. 2 is a hardware configuration diagram of the bus operation planning device according to the embodiment.
- the bus schedule device 2 includes a processor 201, a memory 202, an auxiliary storage device 203, a connection device 204, a communication device 205, and a drive device 206. Note that each piece of hardware constituting the bus operation planning device 2 is interconnected via a bus 207.
- the processor 201 plays the role of a control unit that controls the entire bus operation planning device 2, and includes various calculation devices such as a CPU (Central Processing Unit). Processor 201 reads various programs onto memory 202 and executes them. Note that the processor 201 may include GPGPU (General-purpose computing on graphics processing units).
- GPGPU General-purpose computing on graphics processing units
- the memory 202 includes main storage devices such as ROM (Read Only Memory) and RAM (Random Access Memory).
- the processor 201 and the memory 202 form a so-called computer, and when the processor 201 executes various programs read onto the memory 202, the computer realizes various functions.
- the auxiliary storage device 203 stores various programs and various information used when the various programs are executed by the processor 201.
- connection device 204 is a connection device that connects an external device (for example, a display device 210, an operation device 211) and the bus operation planning device 2.
- the communication device 205 is a communication device for transmitting and receiving various information with other devices.
- the drive device 206 is a device for setting the recording medium 230.
- the recording medium 230 herein includes a medium that records information optically, electrically, or magnetically, such as a CD-ROM (Compact Disc Read-Only Memory), a flexible disk, and a magneto-optical disk. Further, the recording medium 230 may include a semiconductor memory that electrically records information, such as a ROM (Read Only Memory) or a flash memory.
- the various programs to be installed in the auxiliary storage device 203 are installed by, for example, setting the distributed recording medium 230 in the drive device 206 and reading out the various programs recorded on the recording medium 230 by the drive device 206. be done.
- various programs installed in the auxiliary storage device 203 may be installed by being downloaded from a network via the communication device 205.
- FIG. 3 is a functional configuration diagram of the bus operation planning device in the embodiment.
- the bus operation planning device 2 includes a transmitting/receiving section 21, an operation plan creating section 22, a queue estimating section 23, and a storage/reading section 29.
- Each of these parts is a function that the processor 201 causes the bus operation planning device 2 to implement using one or more programs installed in the bus operation planning device 2.
- a stop DB (Data Base) 31 a route DB 32, a queue number DB 33, a passenger number DB 34, and a demand forecast DB 35 are constructed.
- FIG. 4 is a conceptual diagram showing a table constituting the stop DB and a table for managing the upper limit of the number of cars stopping at each stop.
- the value of the upper limit E of the number of buses stopping is managed for each stop ID for identifying the stop. For example, it is indicated that only three buses can stop at the stop indicated by the stop ID "bs1" at the same time.
- the ID is an example of identification information (the same applies hereinafter).
- FIG. 5 is a conceptual diagram showing a table configuring the stop DB and a table for managing a bus boarding time matrix. As shown in FIG. 5, the boarding time (minutes) when the bus travels between each stop is managed based on the relationship between the boarding stop ID and the alighting stop ID.
- FIG. 6 is a conceptual diagram showing a table configuring the stop DB and a table for managing a penalty matrix.
- the time (minutes) it takes for a passenger to travel is managed based on the relationship between the departure point ID or destination ID and the stop ID. For example, it takes 0 minutes to walk from your home (d1), which is the departure point, to the bus stop closest to your home (ID: bs1), but it takes 30 minutes to walk from your home (d1) to the bus stop (ID: bs2), so This will be treated as a penalty when using each bus stop.
- FIG. 7 is a conceptual diagram showing a table constituting the stop DB and a penalty matrix.
- the time (minutes) required for a passenger to travel without using a bus route is managed based on the relationship between the departure point ID and the destination ID. For example, when going from your home, which is your starting point, to a movie theater at your destination, this is equivalent to the criteria for determining whether using a bus route is more advantageous in terms of travel time. (minutes) will be treated as a penalty.
- FIG. 8 is a conceptual diagram showing a table configuring the route DB.
- the route DB 32 stop IDs from the first stop ID to the last stop are managed for each route ID.
- FIG. 9 is a conceptual diagram showing a table configuring the queuing number DB (observation data).
- the number of people queuing DB 33 manages the number of people queuing in real time actually observed by the sensor 6 for each predetermined route ID using the stop ID of the stop of a predetermined boarding at a predetermined time. As a result, for example, as shown in FIG. 1, even if the stop 4 is the same, if the signposts 5a and 5b of the lines on which the lines are lined up are different, the number of people queuing can be managed separately.
- FIG. 10 is a conceptual diagram showing a table forming the passenger number DB (observation data).
- the passenger number DB 34 the number of passengers actually observed by the sensor 6 is managed for each predetermined route ID using a stop ID indicating a stop for a predetermined ride in a predetermined time period. For example, 30 people boarded one or more buses on the same route (ID; r1) at the same stop (ID: bs1) in the 10 minutes from 5:00 to 5:10 on 2022.1.1. It has been shown that
- FIG. 11 is a conceptual diagram showing the tables that constitute the demand forecast DB.
- the demand forecast DB 35 manages the predicted number of passengers (predicted demand number) for each predetermined destination ID at a predetermined departure point ID in a predetermined time period. For example, the number of passengers predicted to travel from a departure point in a certain area (for example, around 1-1 Street) to a certain destination in a certain area (for example, around 9-9 Street) is Managed. Note that "passengers" include not only those who use buses, but also those who consider using buses and then travel without using buses.
- the transmitting/receiving unit 21 transmits and receives data to and from other devices.
- the transmitting/receiving unit 21 receives observation data from the sensor 6 or transmits data on the current (t) operation plan to the communication terminal 9 related to the bus 8.
- the operation plan creation unit 22 calculates the number of people waiting in line at the current observation time (hereinafter, “current observation time” may be referred to as “current time”) for each route of the vehicle at each stop, and the number of people queuing from the first train to the current time. From the sum of the cumulative number of passengers and the number of people who selected the route in the operation plan at the previous observation time, we estimate the number of people who selected the route for each route of the vehicles at each stop, tabulated by departure point and destination.
- the queuing number estimating unit 23 determines whether the vehicle operating company and passengers are at the current observation time based on the predicted number of passengers expected after the current time and the number of route selections at the current time estimated by the queuing number estimating unit 23.
- the operation plan is created assuming that the vehicle will behave rationally thereafter.
- the storage/reading unit 29 stores predetermined data in each of the DBs 31 to 35 and reads predetermined data from each of the DBs 31 to 35.
- FIG. 12 is a sequence diagram showing the operation plan data distribution process.
- a sensor 6a installed on the signpost 5a of the route bound for bus stop 4 observes the number of people queuing, and the observation data indicating the result of this observation is sent to the bus operation planning device 2. (S1).
- the transmitting/receiving section 21 of the bus operation planning device 2 receives the observed data, and the storage/reading section 29 stores the observed data in the number of queues DB 33.
- the observation data shows one record in FIG.
- the sensor 6b installed on the signpost 5b of the route bound for bus stop 4 observes the number of people in the queue, and transmits observation data indicating the result of this observation to the bus operation planning device 2 (S2).
- the transmitting/receiving section 21 of the bus operation planning device 2 receives the observed data, and the storage/reading section 29 stores the observed data in the number of queues DB 33. Note that both the process (S1) and the process (S2) are repeated periodically (for example, once every 10 minutes).
- FIGS. 13 to 23 are flowcharts showing the operation plan creation process.
- FIG. 15 is a diagram showing an objective function expressed as an integer linear programming problem.
- each part P1 to P7 of the objective function indicates the following contents.
- FIGS. 16 to 18 are diagrams showing constraint conditions expressed as an integer linear programming problem.
- FIG. 19 is a diagram explaining each variable shown in FIGS. 15 to 18.
- Equation 1 The number of passengers is equal to the sum of the number of people choosing other than the bus and the number of people boarding the bus.
- Equation 2 The difference between the total number of people queuing and the total number of people riding the bus.
- Constraint formula 3 where is the number of people in the queue: Constraint that all passengers board the last bus (the number of people in the queue is 0 at the last time) Equation 4: The total number of passengers is less than or equal to bus capacity C.
- Constraint Equation 5 The total number of buses in operation is less than or equal to the upper limit number U.
- Constraint Equation 6 The total number of buses stopping at stop m is, Constraint equations 7 to 10, where the number of buses is less than or equal to the upper limit E_m: Constraint equation 11, where the number of buses is a non-negative integer: Constraint equation 12, where the number of buses is a non-negative integer: The number of passengers who wish to travel (passenger demand forecast) is a non-negative integer.
- Constraint Equation 13 The current number of people selected z is given as a non-negative integer.
- Constraint Equation 14 The current number of people queuing w is given as a non-negative integer. 14 will be explained.
- the storage/reading unit 29 reads the inter-stop boarding time matrix ⁇ , the penalty matrix d, and the maximum number of stopping buses E from the stop DB 31, and reads bus route candidates from the route DB 32.
- the number of passengers (predicted demand number) x is read out from the demand forecast DB 35.
- the operation plan creation unit 22 initializes the current time t to 0 in the objective function of FIG. 15 (S12).
- a "temporary operation plan” is created for the time being, and in the processes (S15 to S17) described later, a "temporary operation plan" is created based on observation data indicating the current number of people in the queue obtained from the sensor 6 of each stop. , an ⁇ actual operation plan'' for operating the waiting buses is created.
- the contents of the operation plan will be briefly explained (see FIG. 19).
- Number of non-passengers a is the number of people who travel to their destination without using the bus (those who choose not to use the bus), assuming that people who queue at the bus stop always get on the bus. It is the number of passengers indicating the number of people.
- Numberer of passengers b is the number of passengers, which is the number of people who travel by bus (people who choose to ride the bus).
- the "route selection planned number of passengers z" indicates the number of passengers who select and board a bus on a predetermined route at a predetermined stop in order to travel from a predetermined departure point to a predetermined destination during a predetermined time period.
- the "planned number of passengers w" indicates the number of passengers who want to travel from a predetermined departure point to a predetermined destination at a predetermined time and line up in a queue for a predetermined route.
- Numberer of buses in operation V indicates the number of buses operating on a predetermined route during a predetermined time period.
- the operation plan creation unit 22 sets the current time t to (t+1) in the objective function of FIG. 15 (S14).
- the storage/reading unit 29 reads the number of people queuing w(t) at the current time t for each bus route at each stop from the number of people queuing DB 33, and reads out the number of people queuing w(t) at the current time t for each bus route at each stop from the number of passengers DB 34.
- the number of passengers b(t) is read out (S15).
- the number of people in the queue estimating unit 23 calculates the sum of the number of people in the queue for each bus route at each stop w(t) and the cumulative total of the number of passengers b(t) and (a part of (Equation 2) ), from the route selection z(t-1) of the operation plan ((t-1) version), estimate the route selection z(t) for each bus route at each stop tabulated by departure point and destination (S16 ).
- the passenger route selection plan (variable z), the queue number plan (variable w), and the bus route operation plan (variable V) will be explained using FIGS. 20 to 22.
- FIG. 20 is a diagram showing a passenger's route selection plan (variable z). As shown in FIG. 20, in the data of the passenger's route selection plan, for each stop ID and route ID of the boarding stop in a predetermined time period, the departure point ID, the stop ID of the alighting stop, and the destination ID are used. , and the number of route selections (z) are associated.
- FIG. 21 is a diagram showing the matrix number planning (variable w). As shown in FIG. 21, in the queuing number planning data, the stop ID of the boarding stop, route ID, and queuing number planning (w) are associated for each time. Note that the number of people in the queue (w) shown in FIG. 9 is the number of people in the queue actually observed by the sensor 6, whereas the number of people in the queue (w) in FIG. 21 is the number of people who are planning to queue. (planned) number of people in line.
- FIG. 22 is a diagram showing a bus route operation plan (variable V). As shown in FIG. 22, in the bus route operation plan data, a route ID and the number (V) of buses that should operate on the route related to this route ID are associated with each time slot.
- FIG. 23 (a) is a diagram showing one item (record) of the number of people in queue DB, (b) is a diagram showing the cumulative total in one item (record) of the number of passengers DB, and (c) is the optimum at time (t-1). (d) is a diagram showing the estimation result of the number of people in the queue at time (t).
- FIG. 23(a) is data that shows one record of FIG. 9 again for reference.
- FIG. 23(b) is data showing the cumulative number of passengers from the first train in one record of FIG. 10 for reference.
- the number of passengers (b) in FIG. 23(b) is a value corresponding to b in (Equation 2) of the constraint condition.
- the number of people who lined up at the sign post for the predetermined route (r1) at the predetermined stop (ID: bs1) between 5:10 and the first train is 36 (36 people lined up at 5:10).
- the operation plan creation unit 22 determines that the operating company and passengers will act rationally after the observation based on the assumed passenger demand forecast x and route selection z(t) after the current time t. Assuming this, an operation plan (T version) (number of non-boarders a, number of passengers b, planned number of route selection z, planned number of people in line w, number of operating vehicles V) is created (S17).
- the transmitting/receiving unit 21 distributes the data of the bus operation plan (T version) (S18/S4 in FIG. 4).
- the operation plan creation unit 22 determines whether the bus company has ended its operations (S19). If the business has not ended (S19; NO), the process returns to the process of FIG. 13 (S14). After this, in the process (S15), the storage/reading unit 29 updates the number of passengers b(t) at the current time t. On the other hand, if the business has ended (S19; YES), the operation plan creation process ends.
- the bus operation planning device 2 formulates an optimization problem in which the waiting time at the route signpost at the stop is used as the objective function and the queue is incorporated as the constraint.
- the breakdown is estimated using the observed value from the sensor 6 of the number of people in the queue (we know which route to take, but we do not know which stop to get off at, so it is estimated: multiple routes at one stop), An optimal solution can be found that takes into account the benefits for both the operating company and passengers.
- the present invention is not limited to the above-described embodiments, and may have the following configuration or processing (operation).
- Each functional configuration of the bus operation planning device 2 can be realized by a computer and a program as described above, but this program can also be recorded on a (non-temporary) recording medium and presented, or it can be provided through a network such as the Internet. It is also possible.
- Communication system 2 Bus operation planning device (an example of vehicle operation planning device) 4 Stops 5a, 5b Signposts 6a, 6b Sensor 7 Office 8 Bus (an example of vehicle) 9 Communication terminal 10 Terminal position 21 Transmitting/receiving section (an example of a transmitting section, an example of a receiving section) 22 Operation plan creation section 23 Queue number estimation section 29 Storage/reading section 31 Stop DB 32 Route DB 33 Number of people in line DB 34 Number of passengers DB 35 Demand forecast DB 100 Communication network
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Traffic Control Systems (AREA)
Abstract
The purpose of the present invention is to create a service plan for vehicles such as busses whereby it is possible to minimize the sum of the costs of a company operating vehicles such as busses and the costs to passengers including the time spent waiting at bus stops. Accordingly, the present disclosure is a vehicle service planning device that is for planning vehicle service and comprises: a queuing number estimation unit that estimates the number of people choosing a route for each vehicle route at each of stops totaled by departure location and destination on the basis of the total of the number of people waiting in queues at the current observation time for each of the vehicle routes at each of the stops and the cumulative number of passengers from the first departure to the current time, and on the basis of the number of people choosing the routes in a service plan at the previous observation time; and a service plan creation unit for creating a service plan under the assumption that the company operating the vehicles and the passengers will act in a rational manner starting from the current observation time on the basis of the predicted passenger demand expected starting from the current observation time and the number of people choosing the routes at the current observation time estimated by the queuing number estimation unit.
Description
本開示内容は、車両運行計画装置、車両運行計画支援方法、及びプログラムに関する。
The present disclosure relates to a vehicle operation planning device, a vehicle operation planning support method, and a program.
近年、バス運行計画を作成するため、これまで様々な技術が提案されている。例えば、乗客の需要を満たす計画の中で、バスの移動距離を最短とする技術が提案されている(非特許文献1)。また、逐次的に需要を観測して、最適なバス運行計画を学習する技術も提案されている(非特許文献2)。
In recent years, various technologies have been proposed for creating bus operation plans. For example, in a plan to meet passenger demand, a technique has been proposed that minimizes the travel distance of buses (Non-Patent Document 1). Furthermore, a technology has been proposed that sequentially observes demand and learns an optimal bus operation plan (Non-Patent Document 2).
ところで、監視カメラでバス停の待ち行列の人数を観測して、バス運行計画に利用する技術も提案されている(特許文献1)。
Incidentally, a technology has also been proposed in which the number of people in a queue at a bus stop is observed using a surveillance camera and used for bus operation planning (Patent Document 1).
しかしながら、非特許文献1の技術は,乗客の需要に対してバス移動距離を最小とするバス運行計画を求めるが、現実に近い需要を事前に把握することが困難である。また、非特許文献2の技術は、乗客の需要を逐次的に観測して、バス移動距離を最小とするバス運行計画を求めるが、乗客の待ち時間を最小化の対象とすることができない。更に、特許文献1の技術は、監視カメラによりバス停の待ち行列の人数を観測できるが、待ち行列人数に基づいてバス運行計画を更新することまではできない。
However, although the technique of Non-Patent Document 1 calculates a bus operation plan that minimizes the bus travel distance in relation to passenger demand, it is difficult to grasp the actual demand in advance. Furthermore, although the technology disclosed in Non-Patent Document 2 sequentially observes passenger demand and determines a bus operation plan that minimizes the bus travel distance, it is not possible to minimize passenger waiting time. Further, although the technology disclosed in Patent Document 1 allows the number of people in a queue at a bus stop to be observed using a surveillance camera, it is not possible to update the bus operation plan based on the number of people in the queue.
本発明は、上記の点に鑑みてなされたものであり、バス等の車両の運行会社のコストと、停留所での待ち時間を含めた乗客のコストとの和を最小化するようなバス等の車両の運行計画を作成することを目的とする。
The present invention has been made in view of the above points, and provides a bus etc. that minimizes the sum of the cost of the operating company of the bus etc. and the cost of the passengers including waiting time at the bus stop. The purpose is to create a vehicle operation plan.
上記目的を達成するため、請求項1に係る発明は、車両運行の計画を行う車両運行計画装置であって、各停留所の車両の路線毎の現在の観測時刻における待ち行列人数と始発から現在時刻までの乗車人数の累計との和と、一つ前の観測時刻における運行計画の路線選択人数から、出発地別かつ目的地別に集計した各停留所の車両の路線毎の路線選択人数を推定する待ち行列人数推定部と、現在の観測時刻以降の想定する乗客需要の予測人数及び前記待ち行列人数推定部によって推定された現在の観測時刻における前記路線選択人数から、前記車両の運行会社と乗客が前記現在の観測時刻以降に合理的に行動することを仮定して運行計画を作成する運行計画作成部と、を有する車両運行計画装置である。
In order to achieve the above object, the invention according to claim 1 is a vehicle operation planning device that plans vehicle operations, which includes the number of people in a queue at each stop at the current observed time for each route of vehicles, and the current time from the first train. Waiting to estimate the number of people who selected routes for each route of vehicles at each stop, aggregated by departure point and destination, from the sum of the cumulative number of passengers up until now and the number of people who selected routes in the operation plan at the previous observation time. The operating company of the vehicle and the number of passengers are determined based on the number of people in line estimating the number of passengers, the predicted number of passengers expected after the current observation time, and the number of people selected on the route at the current observation time estimated by the number of people in line estimating the number of passengers in the queue. This is a vehicle operation planning device that includes an operation plan creation section that creates an operation plan assuming that the vehicle will act rationally after the current observation time.
以上説明したように本発明によれば、実際の待ち行列の人数を考慮することで、車両の運行会社のコストと停留所での待ち時間を含めた乗客のコストとの和を最小化するような車両運行計画を作成することができるという効果を奏する。
As explained above, according to the present invention, by considering the actual number of people in the queue, the sum of the cost of the vehicle operating company and the cost of passengers including waiting time at the stop can be minimized. This has the effect that a vehicle operation plan can be created.
〔全体構成の概略〕
図1は、本発明の実施形態における通信システム1の概略図である。通信システム1は、バス運行計画装置2、センサ6a,6b、及び通信端末9によって構築されている。 [Overview of overall configuration]
FIG. 1 is a schematic diagram of acommunication system 1 in an embodiment of the present invention. The communication system 1 is constructed by a bus operation planning device 2, sensors 6a, 6b, and a communication terminal 9.
図1は、本発明の実施形態における通信システム1の概略図である。通信システム1は、バス運行計画装置2、センサ6a,6b、及び通信端末9によって構築されている。 [Overview of overall configuration]
FIG. 1 is a schematic diagram of a
バス運行計画装置2は、今後発展が見込まれるオンデマンドのバス運行の計画を行う装置である。オンデマンドのバス運行は、これまでのように予め決められた時刻(厳密には「日時」)に、決められた路線を運行する場合とは異なり、リアルタイムで停留所の待ち行列の人数を考慮して柔軟に特定の路線に対してバスを増便又は減便する方法である。
The bus operation planning device 2 is a device that plans on-demand bus operations, which are expected to develop in the future. On-demand bus service differs from the conventional bus service, which operates on a fixed route at a predetermined time (strictly speaking, at a "date and time"), by taking into account the number of people queuing at a stop in real time. This is a method to flexibly increase or decrease the number of buses on specific routes.
本実施形態のバス運行計画装置2は、停留所の所定路線の待ち行列の人数を考慮するだけでなく、バス会社の人件費やバスの燃料費等も考慮することで、総合的に判断してバス運行計画を作成する。なお、バス運行計画装置2は、車両運行計画装置の一例である。車両には、将来、所定の路地等を走行するサービスが行われるオンデマンドのタクシー等も含まれる。
The bus operation planning device 2 of this embodiment not only considers the number of people waiting in a queue for a predetermined route at a stop, but also takes into account the personnel costs of the bus company, the fuel costs of the bus, etc., and makes a comprehensive judgment. Create a bus schedule. Note that the bus operation planning device 2 is an example of a vehicle operation planning device. In the future, vehicles will also include on-demand taxis, etc., which will provide services such as driving in predetermined alleys.
図1では、ある停留所4に、a行きの路線の標識柱5aと、b行きの標識柱5bが設置されている。また、標識柱5aには、a行きの路線の待ち行列の人数を観測するためのセンサ6aが設けられている。同様に、標識柱5bには、b行きの路線の待ち行列の人数を観測するためのセンサ6bが設けられている。各センサ6a,6bは、インターネット等の通信ネットワーク100を介して、バス運行計画装置2に対し、リアルタイムで各待ち行列の人数を示すデータを送信することで、バス運行計画装置2が、各待ち行列の人数を管理する。
In FIG. 1, at a certain stop 4, a signpost 5a for a route bound for a and a signpost 5b for a route bound for b are installed. Further, the signpost 5a is provided with a sensor 6a for observing the number of people in the queue for the route bound for a. Similarly, the signpost 5b is provided with a sensor 6b for observing the number of people in the queue for the line bound for b. Each sensor 6a, 6b transmits data indicating the number of people in each queue to the bus operation planning device 2 in real time via a communication network 100 such as the Internet. Manage the number of people in line.
また、バスの運行会社の営業所7にはバス8が待機しており、バス8には通信端末9が搭載されている。通信端末9が、通信ネットワーク100を介してバス運行計画装置2からバス運行計画に従った運行計画のデータを受信することで、バス8が運行計画に従った時間に営業所7から出発し、運行計画に従った路線を運行する。
Furthermore, a bus 8 is waiting at the office 7 of the bus operating company, and the bus 8 is equipped with a communication terminal 9. The communication terminal 9 receives the data of the operation plan according to the bus operation plan from the bus operation planning device 2 via the communication network 100, so that the bus 8 departs from the office 7 at the time according to the operation plan, Operate routes according to the operation plan.
なお、以降、複数の標識柱5a,5b等のうち任意の標識柱を「標識柱5」と示す。また、複数のセンサ6a,6b等のうち任意のセンサを「センサ6」と示す。また、図1では、説明の便宜上、1つのバス運行計画装置2が示されているが、複数のバス運行計画装置があってもよい。但し、複数のバス運行計画装置がある場合であっても、まとめてバス運行計画装置2と示す。
Hereinafter, any one of the plurality of signposts 5a, 5b, etc. will be referred to as a "signpost 5." Further, any sensor among the plurality of sensors 6a, 6b, etc. will be referred to as "sensor 6". Further, in FIG. 1, for convenience of explanation, one bus operation planning device 2 is shown, but there may be a plurality of bus operation planning devices. However, even if there is a plurality of bus operation planning devices, they will be collectively referred to as the bus operation planning device 2.
また、図1では、1つの停留所4が示されているが、実際には複数の停留所が存在する。更に、図1では、1つの停留所4に2つの路線用の標識柱5a,5bが設置されているが、1つの停留所に1つの路線用の標識柱が設置されていてもよく、1つの停留所に3つ以上の路線用の標識柱が設置されていてもよい。センサ6は標識柱5の数に従って増減する。また、図1では、1つの営業所7に1台のバス8が待機している場合について示されているが、複数のバスが待機していても良い。複数のバスのそれぞれに通信端末が搭載されている。
Furthermore, although one stop 4 is shown in FIG. 1, there are actually multiple stops. Furthermore, in FIG. 1, one stop 4 has two route sign posts 5a and 5b installed, but one stop may have one route sign post, and one stop 4 has two route sign posts 5a and 5b installed. There may be three or more route signposts installed. The number of sensors 6 increases or decreases according to the number of signposts 5. Further, although FIG. 1 shows a case where one bus 8 is waiting at one business office 7, a plurality of buses may be waiting. Each of the multiple buses is equipped with a communication terminal.
更に、バス8には通信端末9が搭載されず、営業所7の事務管理室等に設置されていてもよい。この場合、事務管理者からバスの運転手にバスの出発時間と路線が伝えられる。
Furthermore, the communication terminal 9 may not be installed on the bus 8, but may be installed in the administrative office of the business office 7, etc. In this case, the office manager informs the bus driver of the bus's departure time and route.
〔バス運行計画装置のハードウェア構成〕
次に、図2を用いて、バス運行計画装置2のハードウェア構成について説明する。図2は、実施形態に係るバス運行計画装置のハードウェア構成図である。 [Hardware configuration of bus operation planning device]
Next, the hardware configuration of the busoperation planning device 2 will be explained using FIG. 2. FIG. 2 is a hardware configuration diagram of the bus operation planning device according to the embodiment.
次に、図2を用いて、バス運行計画装置2のハードウェア構成について説明する。図2は、実施形態に係るバス運行計画装置のハードウェア構成図である。 [Hardware configuration of bus operation planning device]
Next, the hardware configuration of the bus
図3に示されているように、バス運行計画装置2は、プロセッサ201、メモリ202、補助記憶装置203、接続装置204、通信装置205、ドライブ装置206を有する。なお、バス運行計画装置2を構成する各ハードウェアは、バス207を介して相互に接続される。
As shown in FIG. 3, the bus schedule device 2 includes a processor 201, a memory 202, an auxiliary storage device 203, a connection device 204, a communication device 205, and a drive device 206. Note that each piece of hardware constituting the bus operation planning device 2 is interconnected via a bus 207.
プロセッサ201は、バス運行計画装置2全体の制御を行う制御部の役割を果たし、CPU(Central Processing Unit)等の各種演算デバイスを有する。プロセッサ201は、各種プログラムをメモリ202上に読み出して実行する。なお、プロセッサ201には、GPGPU(General-purpose computing on graphics processing units)が含まれていてもよい。
The processor 201 plays the role of a control unit that controls the entire bus operation planning device 2, and includes various calculation devices such as a CPU (Central Processing Unit). Processor 201 reads various programs onto memory 202 and executes them. Note that the processor 201 may include GPGPU (General-purpose computing on graphics processing units).
メモリ202は、ROM(Read Only Memory)、RAM(Random Access Memory)等の主記憶デバイスを有する。プロセッサ201とメモリ202とは、いわゆるコンピュータを形成し、プロセッサ201が、メモリ202上に読み出した各種プログラムを実行することで、当該コンピュータは各種機能を実現する。
The memory 202 includes main storage devices such as ROM (Read Only Memory) and RAM (Random Access Memory). The processor 201 and the memory 202 form a so-called computer, and when the processor 201 executes various programs read onto the memory 202, the computer realizes various functions.
補助記憶装置203は、各種プログラムや、各種プログラムがプロセッサ201によって実行される際に用いられる各種情報を格納する。
The auxiliary storage device 203 stores various programs and various information used when the various programs are executed by the processor 201.
接続装置204は、外部装置(例えば、表示装置210、操作装置211)とバス運行計画装置2とを接続する接続デバイスである。
The connection device 204 is a connection device that connects an external device (for example, a display device 210, an operation device 211) and the bus operation planning device 2.
通信装置205は、他の装置との間で各種情報を送受信するための通信デバイスである。
The communication device 205 is a communication device for transmitting and receiving various information with other devices.
ドライブ装置206は記録媒体230をセットするためのデバイスである。ここでいう記録媒体230には、CD-ROM(Compact Disc Read-Only Memory)、フレキシブルディスク、光磁気ディスク等のように情報を光学的、電気的あるいは磁気的に記録する媒体が含まれる。また、記録媒体230には、ROM(Read Only Memory)、フラッシュメモリ等のように情報を電気的に記録する半導体メモリ等が含まれていてもよい。
The drive device 206 is a device for setting the recording medium 230. The recording medium 230 herein includes a medium that records information optically, electrically, or magnetically, such as a CD-ROM (Compact Disc Read-Only Memory), a flexible disk, and a magneto-optical disk. Further, the recording medium 230 may include a semiconductor memory that electrically records information, such as a ROM (Read Only Memory) or a flash memory.
なお、補助記憶装置203にインストールされる各種プログラムは、例えば、配布された記録媒体230がドライブ装置206にセットされ、該記録媒体230に記録された各種プログラムがドライブ装置206により読み出されることでインストールされる。あるいは、補助記憶装置203にインストールされる各種プログラムは、通信装置205を介してネットワークからダウンロードされることで、インストールされてもよい。
Note that the various programs to be installed in the auxiliary storage device 203 are installed by, for example, setting the distributed recording medium 230 in the drive device 206 and reading out the various programs recorded on the recording medium 230 by the drive device 206. be done. Alternatively, various programs installed in the auxiliary storage device 203 may be installed by being downloaded from a network via the communication device 205.
〔バス運行計画装置の機能構成〕
続いて、図3を用いて、バス運行計画装置の機能構成について説明する。図3は、実施形態におけるバス運行計画装置の機能構成図である。 [Functional configuration of bus operation planning device]
Next, the functional configuration of the bus operation planning device will be explained using FIG. 3. FIG. 3 is a functional configuration diagram of the bus operation planning device in the embodiment.
続いて、図3を用いて、バス運行計画装置の機能構成について説明する。図3は、実施形態におけるバス運行計画装置の機能構成図である。 [Functional configuration of bus operation planning device]
Next, the functional configuration of the bus operation planning device will be explained using FIG. 3. FIG. 3 is a functional configuration diagram of the bus operation planning device in the embodiment.
図3に示されているように、バス運行計画装置2は、送受信部21、運行計画作成部22、待ち行列人数推定部23、及び記憶・読出部29を有している。これら各部は、バス運行計画装置2にインストールされた1以上のプログラムを使用して、プロセッサ201がバス運行計画装置2に実現させる機能である。
As shown in FIG. 3, the bus operation planning device 2 includes a transmitting/receiving section 21, an operation plan creating section 22, a queue estimating section 23, and a storage/reading section 29. Each of these parts is a function that the processor 201 causes the bus operation planning device 2 to implement using one or more programs installed in the bus operation planning device 2.
また、バス運行計画装置2のメモリ202又は補助記憶装置203には、停留所DB(Data Base)31、路線DB32、行列人数DB33、乗車人数DB34、及び需要予測DB35が構築されている。
Furthermore, in the memory 202 or the auxiliary storage device 203 of the bus operation planning device 2, a stop DB (Data Base) 31, a route DB 32, a queue number DB 33, a passenger number DB 34, and a demand forecast DB 35 are constructed.
<停留所DB>
(停車台数上限)
図4は、停留所DBを構成するテーブルを示し、各停留所の停車台数の上限を管理するテーブルを示す概念図である。図4に示されているように、停留所を識別するための停留所ID毎に、バスの停車台数の上限Eの値が管理されている。例えば、停留所ID「bs1」で示される停留所には、同時に3台のバスしか停車できない旨が示されている。なお、IDは識別情報の一例である(以下、同様)。 <Stop DB>
(Maximum number of stopping cars)
FIG. 4 is a conceptual diagram showing a table constituting the stop DB and a table for managing the upper limit of the number of cars stopping at each stop. As shown in FIG. 4, the value of the upper limit E of the number of buses stopping is managed for each stop ID for identifying the stop. For example, it is indicated that only three buses can stop at the stop indicated by the stop ID "bs1" at the same time. Note that the ID is an example of identification information (the same applies hereinafter).
(停車台数上限)
図4は、停留所DBを構成するテーブルを示し、各停留所の停車台数の上限を管理するテーブルを示す概念図である。図4に示されているように、停留所を識別するための停留所ID毎に、バスの停車台数の上限Eの値が管理されている。例えば、停留所ID「bs1」で示される停留所には、同時に3台のバスしか停車できない旨が示されている。なお、IDは識別情報の一例である(以下、同様)。 <Stop DB>
(Maximum number of stopping cars)
FIG. 4 is a conceptual diagram showing a table constituting the stop DB and a table for managing the upper limit of the number of cars stopping at each stop. As shown in FIG. 4, the value of the upper limit E of the number of buses stopping is managed for each stop ID for identifying the stop. For example, it is indicated that only three buses can stop at the stop indicated by the stop ID "bs1" at the same time. Note that the ID is an example of identification information (the same applies hereinafter).
(バス乗車時間行列)
図5は、停留所DBを構成するテーブルを示し、バス乗車時間行列を管理するテーブルを示す概念図である。図5に示されているように、乗車停留所IDと降車停留所IDとの関係で、各停留所間をバスが移動する際の乗車時間(分)が管理されている。 (Bus boarding time queue)
FIG. 5 is a conceptual diagram showing a table configuring the stop DB and a table for managing a bus boarding time matrix. As shown in FIG. 5, the boarding time (minutes) when the bus travels between each stop is managed based on the relationship between the boarding stop ID and the alighting stop ID.
図5は、停留所DBを構成するテーブルを示し、バス乗車時間行列を管理するテーブルを示す概念図である。図5に示されているように、乗車停留所IDと降車停留所IDとの関係で、各停留所間をバスが移動する際の乗車時間(分)が管理されている。 (Bus boarding time queue)
FIG. 5 is a conceptual diagram showing a table configuring the stop DB and a table for managing a bus boarding time matrix. As shown in FIG. 5, the boarding time (minutes) when the bus travels between each stop is managed based on the relationship between the boarding stop ID and the alighting stop ID.
(ペナルティ行列)
図6は、停留所DBを構成するテーブルを示し、ペナルティ行列を管理するテーブルを示す概念図である。図6に示されているように、出発地ID又は目的地IDと停留所IDとの関係で、旅客が移動に掛かる時間(分)が管理されている。例えば、出発地である自宅(d1)から自宅の最寄りのバス停(ID:bs1)までは徒歩0分で到着するが、自宅(d1)からバス停(ID:bs2)までは徒歩30分掛かるため、各バス停を用いるときのペナルティとして扱われる。 (penalty matrix)
FIG. 6 is a conceptual diagram showing a table configuring the stop DB and a table for managing a penalty matrix. As shown in FIG. 6, the time (minutes) it takes for a passenger to travel is managed based on the relationship between the departure point ID or destination ID and the stop ID. For example, it takes 0 minutes to walk from your home (d1), which is the departure point, to the bus stop closest to your home (ID: bs1), but it takes 30 minutes to walk from your home (d1) to the bus stop (ID: bs2), so This will be treated as a penalty when using each bus stop.
図6は、停留所DBを構成するテーブルを示し、ペナルティ行列を管理するテーブルを示す概念図である。図6に示されているように、出発地ID又は目的地IDと停留所IDとの関係で、旅客が移動に掛かる時間(分)が管理されている。例えば、出発地である自宅(d1)から自宅の最寄りのバス停(ID:bs1)までは徒歩0分で到着するが、自宅(d1)からバス停(ID:bs2)までは徒歩30分掛かるため、各バス停を用いるときのペナルティとして扱われる。 (penalty matrix)
FIG. 6 is a conceptual diagram showing a table configuring the stop DB and a table for managing a penalty matrix. As shown in FIG. 6, the time (minutes) it takes for a passenger to travel is managed based on the relationship between the departure point ID or destination ID and the stop ID. For example, it takes 0 minutes to walk from your home (d1), which is the departure point, to the bus stop closest to your home (ID: bs1), but it takes 30 minutes to walk from your home (d1) to the bus stop (ID: bs2), so This will be treated as a penalty when using each bus stop.
(ペナルティ行列)
図7は、図6と同じく、停留所DBを構成するテーブルを示し、ペナルティ行列を示す概念図である。図7に示されているように、出発地IDと目的地IDの関係で、バス路線を用いずに移動する場合に旅客に掛かる時間(分)が管理されている。例えば、出発地である自宅から目的地の映画館に行くような場合に、バス路線を用いるほうが移動時間にメリットがあるか判断する基準に相当し、バスを用いない場合に移動に掛かかる時間(分)がペナルティとして扱われる。 (penalty matrix)
Similar to FIG. 6, FIG. 7 is a conceptual diagram showing a table constituting the stop DB and a penalty matrix. As shown in FIG. 7, the time (minutes) required for a passenger to travel without using a bus route is managed based on the relationship between the departure point ID and the destination ID. For example, when going from your home, which is your starting point, to a movie theater at your destination, this is equivalent to the criteria for determining whether using a bus route is more advantageous in terms of travel time. (minutes) will be treated as a penalty.
図7は、図6と同じく、停留所DBを構成するテーブルを示し、ペナルティ行列を示す概念図である。図7に示されているように、出発地IDと目的地IDの関係で、バス路線を用いずに移動する場合に旅客に掛かる時間(分)が管理されている。例えば、出発地である自宅から目的地の映画館に行くような場合に、バス路線を用いるほうが移動時間にメリットがあるか判断する基準に相当し、バスを用いない場合に移動に掛かかる時間(分)がペナルティとして扱われる。 (penalty matrix)
Similar to FIG. 6, FIG. 7 is a conceptual diagram showing a table constituting the stop DB and a penalty matrix. As shown in FIG. 7, the time (minutes) required for a passenger to travel without using a bus route is managed based on the relationship between the departure point ID and the destination ID. For example, when going from your home, which is your starting point, to a movie theater at your destination, this is equivalent to the criteria for determining whether using a bus route is more advantageous in terms of travel time. (minutes) will be treated as a penalty.
<路線DB>
図8は、路線DBを構成するテーブルを示す概念図である。路線DB32では、路線ID毎に、始発の停留所IDから終点までの停留所IDが管理されている。 <Route DB>
FIG. 8 is a conceptual diagram showing a table configuring the route DB. In theroute DB 32, stop IDs from the first stop ID to the last stop are managed for each route ID.
図8は、路線DBを構成するテーブルを示す概念図である。路線DB32では、路線ID毎に、始発の停留所IDから終点までの停留所IDが管理されている。 <Route DB>
FIG. 8 is a conceptual diagram showing a table configuring the route DB. In the
<行列人数DB>
図9は、行列人数DB(観測データ)を構成するテーブルを示す概念図である。行列人数DB33では、所定の時刻における所定の乗車の停留所の停留所IDで所定の路線ID毎に、センサ6で実際に観測されたリアルタイムの行列人数が管理される。これにより、例えば、図1に示されているように、同じ停留所4であっても、並んでいる路線の標識柱5a,5bが異なれば、それぞれ区別して行列人数が管理される。 <DB of number of people in line>
FIG. 9 is a conceptual diagram showing a table configuring the queuing number DB (observation data). The number ofpeople queuing DB 33 manages the number of people queuing in real time actually observed by the sensor 6 for each predetermined route ID using the stop ID of the stop of a predetermined boarding at a predetermined time. As a result, for example, as shown in FIG. 1, even if the stop 4 is the same, if the signposts 5a and 5b of the lines on which the lines are lined up are different, the number of people queuing can be managed separately.
図9は、行列人数DB(観測データ)を構成するテーブルを示す概念図である。行列人数DB33では、所定の時刻における所定の乗車の停留所の停留所IDで所定の路線ID毎に、センサ6で実際に観測されたリアルタイムの行列人数が管理される。これにより、例えば、図1に示されているように、同じ停留所4であっても、並んでいる路線の標識柱5a,5bが異なれば、それぞれ区別して行列人数が管理される。 <DB of number of people in line>
FIG. 9 is a conceptual diagram showing a table configuring the queuing number DB (observation data). The number of
<乗車人数DB>
図10は、乗車人数DB(観測データ)を構成するテーブルを示す概念図である。乗車人数DB34では、所定の時間帯における所定の乗車の停留所を示す停留所IDで所定の路線ID毎に、センサ6で実際に観測された乗車人数が管理されている。例えば、2022.1.1 5:00-5:10の10分間で、同じ停留所(ID:bs1)の同じ路線(ID;r1)において、1台又は複数台のバスに乗車した人数が30人であることが示されている。 <Number of passengers DB>
FIG. 10 is a conceptual diagram showing a table forming the passenger number DB (observation data). In thepassenger number DB 34, the number of passengers actually observed by the sensor 6 is managed for each predetermined route ID using a stop ID indicating a stop for a predetermined ride in a predetermined time period. For example, 30 people boarded one or more buses on the same route (ID; r1) at the same stop (ID: bs1) in the 10 minutes from 5:00 to 5:10 on 2022.1.1. It has been shown that
図10は、乗車人数DB(観測データ)を構成するテーブルを示す概念図である。乗車人数DB34では、所定の時間帯における所定の乗車の停留所を示す停留所IDで所定の路線ID毎に、センサ6で実際に観測された乗車人数が管理されている。例えば、2022.1.1 5:00-5:10の10分間で、同じ停留所(ID:bs1)の同じ路線(ID;r1)において、1台又は複数台のバスに乗車した人数が30人であることが示されている。 <Number of passengers DB>
FIG. 10 is a conceptual diagram showing a table forming the passenger number DB (observation data). In the
<需要予測DB>
図11は、需要予測DBを構成するテーブルを示す概念図である。需要予測DB35では、所定の時間帯における所定の出発地IDで所定の目的地ID毎に、予測された旅客数(需要予測人数)が管理されている。例えば、ある地域(例えば、「1丁目1番地」あたり)である出発地から、ある地域(例えば、「9丁目9番地」あたり)である目的地までに行くであろうと予測された旅客数が管理されている。なお、「旅客」には、バスを利用する人だけでなく、バス利用を検討した上でバスを利用せずに移動する人も含まれる。 <Demand forecast DB>
FIG. 11 is a conceptual diagram showing the tables that constitute the demand forecast DB. Thedemand forecast DB 35 manages the predicted number of passengers (predicted demand number) for each predetermined destination ID at a predetermined departure point ID in a predetermined time period. For example, the number of passengers predicted to travel from a departure point in a certain area (for example, around 1-1 Street) to a certain destination in a certain area (for example, around 9-9 Street) is Managed. Note that "passengers" include not only those who use buses, but also those who consider using buses and then travel without using buses.
図11は、需要予測DBを構成するテーブルを示す概念図である。需要予測DB35では、所定の時間帯における所定の出発地IDで所定の目的地ID毎に、予測された旅客数(需要予測人数)が管理されている。例えば、ある地域(例えば、「1丁目1番地」あたり)である出発地から、ある地域(例えば、「9丁目9番地」あたり)である目的地までに行くであろうと予測された旅客数が管理されている。なお、「旅客」には、バスを利用する人だけでなく、バス利用を検討した上でバスを利用せずに移動する人も含まれる。 <Demand forecast DB>
FIG. 11 is a conceptual diagram showing the tables that constitute the demand forecast DB. The
<各機能部>
続いて、各機能部について説明する。 <Each functional part>
Next, each functional section will be explained.
続いて、各機能部について説明する。 <Each functional part>
Next, each functional section will be explained.
送受信部21は、他の装置等とデータの送受信を行う。例えば、送受信部21は、センサ6から観測データを受信したり、バス8に関わる通信端末9に現在(t)の運行計画のデータを送信したりする。
The transmitting/receiving unit 21 transmits and receives data to and from other devices. For example, the transmitting/receiving unit 21 receives observation data from the sensor 6 or transmits data on the current (t) operation plan to the communication terminal 9 related to the bus 8.
運行計画作成部22は、各停留所の車両の路線毎の現在の観測時刻(以降、「現在の観測時刻」を「現在時刻」と示す場合もある)における待ち行列人数と始発から現在時刻までの乗車人数の累計との和と、一つ前の観測時刻における運行計画の路線選択人数から、出発地別かつ目的地別に集計した各停留所の車両の路線毎の路線選択人数を推定する。
The operation plan creation unit 22 calculates the number of people waiting in line at the current observation time (hereinafter, "current observation time" may be referred to as "current time") for each route of the vehicle at each stop, and the number of people queuing from the first train to the current time. From the sum of the cumulative number of passengers and the number of people who selected the route in the operation plan at the previous observation time, we estimate the number of people who selected the route for each route of the vehicles at each stop, tabulated by departure point and destination.
待ち行列人数推定部23は、現在時刻以降の想定する乗客需要の予測人数及び待ち行列人数推定部23によって推定された現在時刻における路線選択人数から、車両の運行会社と乗客が前記現在の観測時刻以降に合理的に行動することを仮定して運行計画を作成する。
The queuing number estimating unit 23 determines whether the vehicle operating company and passengers are at the current observation time based on the predicted number of passengers expected after the current time and the number of route selections at the current time estimated by the queuing number estimating unit 23. The operation plan is created assuming that the vehicle will behave rationally thereafter.
記憶・読出部29は、各DB31~35に対して所定のデータを記憶したり、各DB31~35から所定のデータを読み出したりする。
The storage/reading unit 29 stores predetermined data in each of the DBs 31 to 35 and reads predetermined data from each of the DBs 31 to 35.
なお、各機能部に関しては、後ほど詳細に説明する。
Note that each functional unit will be explained in detail later.
〔実施形態の処理又は動作〕
続いて、図12を用いて、運行計画データの配信処理を説明する。図12は、運行計画データの配信処理を示すシーケンス図である。 [Processing or operation of embodiment]
Next, the operation plan data distribution process will be explained using FIG. 12. FIG. 12 is a sequence diagram showing the operation plan data distribution process.
続いて、図12を用いて、運行計画データの配信処理を説明する。図12は、運行計画データの配信処理を示すシーケンス図である。 [Processing or operation of embodiment]
Next, the operation plan data distribution process will be explained using FIG. 12. FIG. 12 is a sequence diagram showing the operation plan data distribution process.
図12に示されているように、停留所4のa行きの路線の標識柱5aに設置されたセンサ6aが待ち行列人数を観測して、この観測の結果を示す観測データをバス運行計画装置2に送信する(S1)。これにより、バス運行計画装置2の送受信部21が、観測データを受信し、記憶・読出部29が観測データを行列人数DB33に記憶する。観測データは、図9の1レコードを示す。
As shown in FIG. 12, a sensor 6a installed on the signpost 5a of the route bound for bus stop 4 observes the number of people queuing, and the observation data indicating the result of this observation is sent to the bus operation planning device 2. (S1). As a result, the transmitting/receiving section 21 of the bus operation planning device 2 receives the observed data, and the storage/reading section 29 stores the observed data in the number of queues DB 33. The observation data shows one record in FIG.
同様に、停留所4のb行きの路線の標識柱5bに設置されたセンサ6bが待ち行列人数を観測して、この観測の結果を示す観測データをバス運行計画装置2に送信する(S2)。これにより、バス運行計画装置2の送受信部21が、観測データを受信し、記憶・読出部29が観測データを行列人数DB33に記憶する。なお、処理(S1)と処理(S2)は共に、定期的(例えば、10分に1回)繰り返される。
Similarly, the sensor 6b installed on the signpost 5b of the route bound for bus stop 4 observes the number of people in the queue, and transmits observation data indicating the result of this observation to the bus operation planning device 2 (S2). As a result, the transmitting/receiving section 21 of the bus operation planning device 2 receives the observed data, and the storage/reading section 29 stores the observed data in the number of queues DB 33. Note that both the process (S1) and the process (S2) are repeated periodically (for example, once every 10 minutes).
次に、バス運行計画装置2は、目的関数を利用して運行計画の処理を実行する(S3)。ここで、図13乃至図23を用いて、運行計画の処理について詳細に説明する。図13及び図14は、運行計画の作成処理を示すフローチャートである。図15は、整数線形計画問題として表現した目的関数を示す図である。
Next, the bus operation planning device 2 executes operation plan processing using the objective function (S3). Here, the operation plan processing will be explained in detail using FIGS. 13 to 23. 13 and 14 are flowcharts showing the operation plan creation process. FIG. 15 is a diagram showing an objective function expressed as an integer linear programming problem.
ここで、図15を用いて、目的関数を説明する。目的関数は、停留所の所定路線の待ち行列の人数を考慮するだけでなく、バス会社の人件費やバスの燃料費等も考慮することで、総合的に判断してバス運行計画を立てるための関数である。そのため、目的関数の各部分P1~P7は、以下の内容を示してる。
P1:バス運行の経路長
P2:出発地から乗車の停留所までのペナルティコスト(例えば、自宅から最寄りのバス停までに掛かる費用や時間等)
P3:降車の停留所から目的地までのペナルティコスト(例えば、降車した停留所から目的地の映画館までに係る費用や時間等)
P4:乗客の乗車時間(乗車の停留所から降車の停留所までにかかった時間)
P5:路線に割り当てるOD(Origin-Destination)集団の人数
P6:出発地から目的地までのペナルティコスト(例えば、自宅等の出発地から目的地の映画館に行くまでに、バスを利用せずに、徒歩やタクシーを利用したりすることで、目的地までに到着するまでの費用や時間等)
P7:待ち人数×Δ=のべ待ち時間[人・分]
また、図16乃至図18は、整数線形計画問題として表現した制約条件を示す図である。そして、図19は、図15乃至図18で示された各変数を説明する図である。 Here, the objective function will be explained using FIG. 15. The objective function not only takes into account the number of people waiting in the queue for a given route at the bus stop, but also takes into consideration the bus company's personnel costs, bus fuel costs, etc., so that it can be used to make a comprehensive judgment and plan the bus operation. It is a function. Therefore, each part P1 to P7 of the objective function indicates the following contents.
P1: Route length of bus operation P2: Penalty cost from departure point to boarding stop (for example, cost and time required to get from home to the nearest bus stop, etc.)
P3: Penalty cost from the stop you get off at to your destination (for example, the cost and time involved from the stop you get off at to the movie theater at your destination)
P4: Passenger boarding time (time taken from boarding stop to getting off stop)
P5: Number of people in the OD (Origin-Destination) group assigned to the route P6: Penalty cost from the departure point to the destination (for example, the penalty cost from the departure point such as home to the destination movie theater without using a bus) , the cost and time required to reach the destination by walking or using a taxi)
P7: Number of people waiting x Δ = Total waiting time [people/minutes]
Further, FIGS. 16 to 18 are diagrams showing constraint conditions expressed as an integer linear programming problem. FIG. 19 is a diagram explaining each variable shown in FIGS. 15 to 18.
P1:バス運行の経路長
P2:出発地から乗車の停留所までのペナルティコスト(例えば、自宅から最寄りのバス停までに掛かる費用や時間等)
P3:降車の停留所から目的地までのペナルティコスト(例えば、降車した停留所から目的地の映画館までに係る費用や時間等)
P4:乗客の乗車時間(乗車の停留所から降車の停留所までにかかった時間)
P5:路線に割り当てるOD(Origin-Destination)集団の人数
P6:出発地から目的地までのペナルティコスト(例えば、自宅等の出発地から目的地の映画館に行くまでに、バスを利用せずに、徒歩やタクシーを利用したりすることで、目的地までに到着するまでの費用や時間等)
P7:待ち人数×Δ=のべ待ち時間[人・分]
また、図16乃至図18は、整数線形計画問題として表現した制約条件を示す図である。そして、図19は、図15乃至図18で示された各変数を説明する図である。 Here, the objective function will be explained using FIG. 15. The objective function not only takes into account the number of people waiting in the queue for a given route at the bus stop, but also takes into consideration the bus company's personnel costs, bus fuel costs, etc., so that it can be used to make a comprehensive judgment and plan the bus operation. It is a function. Therefore, each part P1 to P7 of the objective function indicates the following contents.
P1: Route length of bus operation P2: Penalty cost from departure point to boarding stop (for example, cost and time required to get from home to the nearest bus stop, etc.)
P3: Penalty cost from the stop you get off at to your destination (for example, the cost and time involved from the stop you get off at to the movie theater at your destination)
P4: Passenger boarding time (time taken from boarding stop to getting off stop)
P5: Number of people in the OD (Origin-Destination) group assigned to the route P6: Penalty cost from the departure point to the destination (for example, the penalty cost from the departure point such as home to the destination movie theater without using a bus) , the cost and time required to reach the destination by walking or using a taxi)
P7: Number of people waiting x Δ = Total waiting time [people/minutes]
Further, FIGS. 16 to 18 are diagrams showing constraint conditions expressed as an integer linear programming problem. FIG. 19 is a diagram explaining each variable shown in FIGS. 15 to 18.
ここで、図16乃至図18に示された制約条件における(式1)~(式14)について、以下に説明する。なお、図18の(式12)~(式14)に関しては、最適化のために変化させずに外部から決める(現在時刻に関しての変数を固定する)という意味で"Given"が示されている。
式1:旅客の人数が、バス以外を選択する人数と,バスに乗車する人数との和と等しいとする制約
式2:待ち行列として並んだ累計人数と,バスに乗った累計人数との差が行列人数とする制約
式3:最終のバスまでに乗客全員を乗車させる制約(最終時刻で行列人数が0)
式4:乗客の合計が、バスの定員C以下である制約
式5:運行するバスの台数の合計が,上限台数U以下である制約
式6:停留所mに停まるバスの台数の合計が,上限台数E_m以下である制約
式7~式10:人数を非負整数とする制約
式11:バスの台数を非負整数とする制約
式12:移動を希望する旅客人数(乗客需要予測)が非負整数で所与とする制約
式13:現在の選択人数zが非負整数で所与とする制約
式14:現在の行列人数wが非負整数で所与とする制約
上記の内容を踏まえて、図13及び図14の処理を説明する。 Here, (Formula 1) to (Formula 14) under the constraint conditions shown in FIGS. 16 to 18 will be explained below. Regarding (Formula 12) to (Formula 14) in FIG. 18, "Given" is shown to mean that they are determined externally without changing for optimization (fixing the variable related to the current time). .
Equation 1: The number of passengers is equal to the sum of the number of people choosing other than the bus and the number of people boarding the bus. Equation 2: The difference between the total number of people queuing and the total number of people riding the bus.Constraint formula 3 where is the number of people in the queue: Constraint that all passengers board the last bus (the number of people in the queue is 0 at the last time)
Equation 4: The total number of passengers is less than or equal to bus capacity C. Constraint Equation 5: The total number of buses in operation is less than or equal to the upper limit number U. Constraint Equation 6: The total number of buses stopping at stop m is,Constraint equations 7 to 10, where the number of buses is less than or equal to the upper limit E_m: Constraint equation 11, where the number of buses is a non-negative integer: Constraint equation 12, where the number of buses is a non-negative integer: The number of passengers who wish to travel (passenger demand forecast) is a non-negative integer. Constraint Equation 13: The current number of people selected z is given as a non-negative integer. Constraint Equation 14: The current number of people queuing w is given as a non-negative integer. 14 will be explained.
式1:旅客の人数が、バス以外を選択する人数と,バスに乗車する人数との和と等しいとする制約
式2:待ち行列として並んだ累計人数と,バスに乗った累計人数との差が行列人数とする制約
式3:最終のバスまでに乗客全員を乗車させる制約(最終時刻で行列人数が0)
式4:乗客の合計が、バスの定員C以下である制約
式5:運行するバスの台数の合計が,上限台数U以下である制約
式6:停留所mに停まるバスの台数の合計が,上限台数E_m以下である制約
式7~式10:人数を非負整数とする制約
式11:バスの台数を非負整数とする制約
式12:移動を希望する旅客人数(乗客需要予測)が非負整数で所与とする制約
式13:現在の選択人数zが非負整数で所与とする制約
式14:現在の行列人数wが非負整数で所与とする制約
上記の内容を踏まえて、図13及び図14の処理を説明する。 Here, (Formula 1) to (Formula 14) under the constraint conditions shown in FIGS. 16 to 18 will be explained below. Regarding (Formula 12) to (Formula 14) in FIG. 18, "Given" is shown to mean that they are determined externally without changing for optimization (fixing the variable related to the current time). .
Equation 1: The number of passengers is equal to the sum of the number of people choosing other than the bus and the number of people boarding the bus. Equation 2: The difference between the total number of people queuing and the total number of people riding the bus.
Equation 4: The total number of passengers is less than or equal to bus capacity C. Constraint Equation 5: The total number of buses in operation is less than or equal to the upper limit number U. Constraint Equation 6: The total number of buses stopping at stop m is,
まず、記憶・読出部29は、停留所DB31から停留所間の乗車時間行列τとペナルティ行列dと停車台数上限Eを読出し、路線DB32からバス路線の候補
First, the storage/reading unit 29 reads the inter-stop boarding time matrix τ, the penalty matrix d, and the maximum number of stopping buses E from the stop DB 31, and reads bus route candidates from the route DB 32.
続いて、図13に戻り、運行計画作成部22は、図15の目的関数において現在時刻tを0として初期化する(S12)。
Next, returning to FIG. 13, the operation plan creation unit 22 initializes the current time t to 0 in the objective function of FIG. 15 (S12).
そして、運行計画作成部22は、t=0以降の想定する乗客需要予測xに対して、行列人数w=0、乗車人数b=0とし、運行会社と乗客が待ち行列の観測以降に合理的に行動することを仮定して、仮の運行計画(t=0版)(非乗車人数a,乗車人数b,路線選択計画人数z,行列計画人数w,運行台数V)を作成する(S13)。なお、この処理(S13)では、ひとまず「仮の運行計画」が作成され、後述の処理(S15~S17)において、各停留所のセンサ6から取得した現在の待ち行列人数を示す観測データに基づいて、待機中のバスを運行させるための「実際の運行計画」が作成される。ここで、運行計画の内容について簡単に説明する(図19参照)。
Then, the operation plan creation unit 22 sets the number of queues w = 0 and the number of passengers b = 0 for the assumed passenger demand forecast x after t = 0, and the operating company and passengers A tentative operation plan (t=0 version) (number of non-boarders a, number of passengers b, number of people planning to select a route z, number of people planning to line up w, number of vehicles in operation V) is created (S13). . In addition, in this process (S13), a "temporary operation plan" is created for the time being, and in the processes (S15 to S17) described later, a "temporary operation plan" is created based on observation data indicating the current number of people in the queue obtained from the sensor 6 of each stop. , an ``actual operation plan'' for operating the waiting buses is created. Here, the contents of the operation plan will be briefly explained (see FIG. 19).
「非乗車人数a」は、停留所で待ち行列に並んだ人は必ずバスに乗るということを前提として、バスを利用しないで目的地まで移動する人(バスを利用しないことを選択した人)の人数を示す旅客数である。
"Number of non-passengers a" is the number of people who travel to their destination without using the bus (those who choose not to use the bus), assuming that people who queue at the bus stop always get on the bus. It is the number of passengers indicating the number of people.
「乗車人数b」は、バスを使って移動する人(バスに乗ることを選択した人)の人数である乗客人数である。
"Number of passengers b" is the number of passengers, which is the number of people who travel by bus (people who choose to ride the bus).
「路線選択計画人数z」は、所定の時間帯に、所定の出発地から所定の目的地に移動したくて、所定の停留所の所定の路線のバスを選択して乗車する乗車人数を示す。
The "route selection planned number of passengers z" indicates the number of passengers who select and board a bus on a predetermined route at a predetermined stop in order to travel from a predetermined departure point to a predetermined destination during a predetermined time period.
「行列計画人数w」は、所定の時刻に、所定の出発地から所定の目的地に移動したくて、所定の路線の待ち行列に並ぶ乗客人数を示す。
The "planned number of passengers w" indicates the number of passengers who want to travel from a predetermined departure point to a predetermined destination at a predetermined time and line up in a queue for a predetermined route.
「運行台数V」は、所定の時間帯に所定の路線として運行するバスの台数を示す。
"Number of buses in operation V" indicates the number of buses operating on a predetermined route during a predetermined time period.
なお、路線選択計画z、行列人数計画w、及び運行Vに関しては、図20乃至図22を用いて、後ほど詳細に説明する。
Note that the route selection plan z, the queue number plan w, and the operation V will be explained in detail later using FIGS. 20 to 22.
次に、運行計画作成部22は、図15の目的関数において現在時刻tを(t+1)とする(S14)。
Next, the operation plan creation unit 22 sets the current time t to (t+1) in the objective function of FIG. 15 (S14).
そして、記憶・読出部29は、行列人数DB33から、各停留所のバス路線毎の現在時刻tの行列人数w(t)を読み出し、乗車人数DB34から、各停留所のバス路線毎の現在時刻tの乗車人数b(t)を読み出す(S15)。
Then, the storage/reading unit 29 reads the number of people queuing w(t) at the current time t for each bus route at each stop from the number of people queuing DB 33, and reads out the number of people queuing w(t) at the current time t for each bus route at each stop from the number of passengers DB 34. The number of passengers b(t) is read out (S15).
続いて、図14に進み、待ち行列人数推定部23は、各停留所のバス路線毎の行列人数w(t)と乗車人数b(t)の累計との和と((式2)の一部)、運行計画((t-1)版)の路線選択z(t-1)から、出発地別かつ目的地別に集計した各停留所のバス路線毎の路線選択z(t)を推定する(S16)。
Next, proceeding to FIG. 14, the number of people in the queue estimating unit 23 calculates the sum of the number of people in the queue for each bus route at each stop w(t) and the cumulative total of the number of passengers b(t) and (a part of (Equation 2) ), from the route selection z(t-1) of the operation plan ((t-1) version), estimate the route selection z(t) for each bus route at each stop tabulated by departure point and destination (S16 ).
ここで、図20乃至図22を用い、運行計画の内容として、乗客の路線選択計画(変数z)、行列人数計画(変数w)、及びバス路線の運行計画(変数V)を説明する。
Here, as the contents of the operation plan, the passenger route selection plan (variable z), the queue number plan (variable w), and the bus route operation plan (variable V) will be explained using FIGS. 20 to 22.
(乗客の路線選択計画(変数z))
図20は、乗客の路線選択計画(変数z)を示す図である。図20に示されているように、乗客の路線選択計画のデータでは、所定の時間帯において乗車の停留所の停留所ID及び路線ID毎に、出発地ID、降車の停留所の停留所ID、目的地ID、及び路線選択人数(z)が関連付けられている。 (Passenger route selection plan (variable z))
FIG. 20 is a diagram showing a passenger's route selection plan (variable z). As shown in FIG. 20, in the data of the passenger's route selection plan, for each stop ID and route ID of the boarding stop in a predetermined time period, the departure point ID, the stop ID of the alighting stop, and the destination ID are used. , and the number of route selections (z) are associated.
図20は、乗客の路線選択計画(変数z)を示す図である。図20に示されているように、乗客の路線選択計画のデータでは、所定の時間帯において乗車の停留所の停留所ID及び路線ID毎に、出発地ID、降車の停留所の停留所ID、目的地ID、及び路線選択人数(z)が関連付けられている。 (Passenger route selection plan (variable z))
FIG. 20 is a diagram showing a passenger's route selection plan (variable z). As shown in FIG. 20, in the data of the passenger's route selection plan, for each stop ID and route ID of the boarding stop in a predetermined time period, the departure point ID, the stop ID of the alighting stop, and the destination ID are used. , and the number of route selections (z) are associated.
(行列人数計画(変数w))
図21は、行列人数計画(変数w)を示す図である。図21に示されているように、行列人数計画のデータでは、時刻毎に、乗車の停留所の停留所ID、路線ID、及び行列人数計画(w)が関連付けられている。なお、図9に示されている行列人数(w)は、センサ6により実際に観測された行列人数であるのに対して、図21の行列人数(w)は、待ち行列に並ぶ計画がある(予定)の行列人数である。 (matrix number of people planning (variable w))
FIG. 21 is a diagram showing the matrix number planning (variable w). As shown in FIG. 21, in the queuing number planning data, the stop ID of the boarding stop, route ID, and queuing number planning (w) are associated for each time. Note that the number of people in the queue (w) shown in FIG. 9 is the number of people in the queue actually observed by thesensor 6, whereas the number of people in the queue (w) in FIG. 21 is the number of people who are planning to queue. (planned) number of people in line.
図21は、行列人数計画(変数w)を示す図である。図21に示されているように、行列人数計画のデータでは、時刻毎に、乗車の停留所の停留所ID、路線ID、及び行列人数計画(w)が関連付けられている。なお、図9に示されている行列人数(w)は、センサ6により実際に観測された行列人数であるのに対して、図21の行列人数(w)は、待ち行列に並ぶ計画がある(予定)の行列人数である。 (matrix number of people planning (variable w))
FIG. 21 is a diagram showing the matrix number planning (variable w). As shown in FIG. 21, in the queuing number planning data, the stop ID of the boarding stop, route ID, and queuing number planning (w) are associated for each time. Note that the number of people in the queue (w) shown in FIG. 9 is the number of people in the queue actually observed by the
(バス路線の運行計画(変数V))
図22は、バス路線の運行計画(変数V)を示す図である。図22に示されているように、バス路線の運行計画のデータでは、時間帯毎に、路線ID及び、この路線IDに係る路線を運行すべきバスの台数(V)が関連付けられている。 (Bus route operation plan (variable V))
FIG. 22 is a diagram showing a bus route operation plan (variable V). As shown in FIG. 22, in the bus route operation plan data, a route ID and the number (V) of buses that should operate on the route related to this route ID are associated with each time slot.
図22は、バス路線の運行計画(変数V)を示す図である。図22に示されているように、バス路線の運行計画のデータでは、時間帯毎に、路線ID及び、この路線IDに係る路線を運行すべきバスの台数(V)が関連付けられている。 (Bus route operation plan (variable V))
FIG. 22 is a diagram showing a bus route operation plan (variable V). As shown in FIG. 22, in the bus route operation plan data, a route ID and the number (V) of buses that should operate on the route related to this route ID are associated with each time slot.
(路線選択人数の推定)
次に、図23を用いて、待ち行列人数推定部23が行う路線選択人数(z)を推定する方法を詳細に説明する。図23(a)は行列人数DBの一項(レコード)を示す図、(b)は乗車人数DBの一項(レコード)における累計を示す図、(c)は時刻(t-1)における最適化結果を示す図、(d)は時刻(t)における待ち行列人数の推定結果を示す図である。 (Estimation of number of people choosing route)
Next, a method for estimating the number of people who have selected a route (z) performed by the queuenumber estimation unit 23 will be described in detail using FIG. 23. Figure 23 (a) is a diagram showing one item (record) of the number of people in queue DB, (b) is a diagram showing the cumulative total in one item (record) of the number of passengers DB, and (c) is the optimum at time (t-1). (d) is a diagram showing the estimation result of the number of people in the queue at time (t).
次に、図23を用いて、待ち行列人数推定部23が行う路線選択人数(z)を推定する方法を詳細に説明する。図23(a)は行列人数DBの一項(レコード)を示す図、(b)は乗車人数DBの一項(レコード)における累計を示す図、(c)は時刻(t-1)における最適化結果を示す図、(d)は時刻(t)における待ち行列人数の推定結果を示す図である。 (Estimation of number of people choosing route)
Next, a method for estimating the number of people who have selected a route (z) performed by the queue
なお、図23(a)は、参考のために図9の一レコードを再度示したデータである。また、図23(b)は、参考のために図10の一レコードにおいて始発からの累計の乗車人数を示したデータである。図23(b)の乗車人数(b)は、制約条件の(式2)のbに対応する値である。図23の例では、始発から5:10の間に、所定の停留所(ID:bs1)の所定の路線(r1)の標識柱に並んだ人は、36人(5:10の時点で並んでいる6人(図23(a))と始発から5:10までの間に乗車して停留所を去ってしまった乗車人数(b)の累計の30人(図23(b))との和)である。そして、図23(c)により、同じ停留所(bs1)の同じ路線(ID:r1)の標識柱において、1つ前の時間帯(始発~5:00)で計画上求められた路線選択人数(z)の累計が24人(4人+8人+12人の和)であるとすると、現時間帯(5:00-5:10)で、同じ停留所(ID:bs1)の同じ路線(ID:r1)の標識柱において、新たに到着することで待ち行列に並んだ人数は、12人(36人(図23(a)、(b))と24人(図23(c))の差)である。そして、図23(d)において、12人を3つのルート(d1→bs3→d3,d1→bs3→d4,d2→bs3→d3)に振り分けられる場合、図23(c)の各ルートの路線選択人数(z)の累計に比例して振り分けられる(比例配分される)。即ち、始発から5:00までに並んでいた人数に5:00から5:10までの10分間に並んだ人数を加えて新たに並んだ人数(z)の累計を求め、この累計から、始発から5:10までの乗車人数を引くと、5:10時点での行列の待ち人数を推定により求めることができる。これは、(式2)において、新たに並んだ人数(z)の累計から、乗車人数(b)の累計を引くと、現在並んでいる人(w)を推定することができることを示している。
Note that FIG. 23(a) is data that shows one record of FIG. 9 again for reference. Moreover, FIG. 23(b) is data showing the cumulative number of passengers from the first train in one record of FIG. 10 for reference. The number of passengers (b) in FIG. 23(b) is a value corresponding to b in (Equation 2) of the constraint condition. In the example in Figure 23, the number of people who lined up at the sign post for the predetermined route (r1) at the predetermined stop (ID: bs1) between 5:10 and the first train is 36 (36 people lined up at 5:10). (Figure 23 (a)) plus the total number of passengers (b) who boarded the bus between the first train and 5:10 and left the stop (30 people (Figure 23 (b))) It is. Then, according to Fig. 23(c), the number of people choosing the route (( z) is 24 people (sum of 4 + 8 + 12 people), in the current time period (5:00-5:10), on the same route (ID: r1) at the same stop (ID: bs1). ), the number of people who queued due to new arrivals was 12 people (the difference between 36 people (Figures 23(a) and (b)) and 24 people (Figure 23(c))). be. In Figure 23(d), if 12 people can be divided into three routes (d1→bs3→d3, d1→bs3→d4, d2→bs3→d3), route selection for each route in FIG. 23(c) is performed. It will be distributed in proportion to the cumulative number of people (z). In other words, add the number of people who were in line for 10 minutes from 5:00 to 5:10 to the number of people who were in line from the first train until 5:00 to find the cumulative total of new people in line (z), and from this cumulative total, By subtracting the number of passengers from 5:10 to 5:10, we can estimate the number of people waiting in line at 5:10. This shows that in (Equation 2), by subtracting the cumulative total of the number of passengers (b) from the cumulative total of the new number of people (z), the number of people currently in line (w) can be estimated. .
続いて、図14に戻り、運行計画作成部22は、現在時刻t以降の想定する乗客需要予測x及び路線選択z(t)から、運行会社と乗客が観測以降に合理的に行動することを仮定して、運行計画(t版)(非乗車人数a,乗車人数b,路線選択計画人数z,行列人数計画人数w,運行台数V)を作成する(S17)。
Next, returning to FIG. 14, the operation plan creation unit 22 determines that the operating company and passengers will act rationally after the observation based on the assumed passenger demand forecast x and route selection z(t) after the current time t. Assuming this, an operation plan (T version) (number of non-boarders a, number of passengers b, planned number of route selection z, planned number of people in line w, number of operating vehicles V) is created (S17).
次に、送受信部21が、図4に示されているように、バスの運行計画(t版)のデータを配信する(S18/図4ではS4)。
Next, as shown in FIG. 4, the transmitting/receiving unit 21 distributes the data of the bus operation plan (T version) (S18/S4 in FIG. 4).
次に、運行計画作成部22は、バス会社の営業が終了したかを判断する(S19)。営業が終了していない場合には(S19;NO)、図13の処理(S14)に戻る。この後は、処理(S15)において、記憶・読出部29は、現在時刻tの乗車人数b(t)を更新する。一方、営業が終了した場合には(S19;YES)、運行計画の作成処理が終了する。
Next, the operation plan creation unit 22 determines whether the bus company has ended its operations (S19). If the business has not ended (S19; NO), the process returns to the process of FIG. 13 (S14). After this, in the process (S15), the storage/reading unit 29 updates the number of passengers b(t) at the current time t. On the other hand, if the business has ended (S19; YES), the operation plan creation process ends.
以上により、図12におけるバス運行計画装置2の処理(S3)の説明が終了する。
With this, the explanation of the process (S3) of the bus operation planning device 2 in FIG. 12 is completed.
〔実施形態の主な効果〕
以上説明したように本実施形態によれば、バス運行計画装置2は、停留所における路線の標識柱での待ち時間を目的関数に、待ち行列を制約条件に取り入れた最適化問題を定式化して、待ち行列の人数のセンサ6からの観測値を用いて、内訳を推定して(どの路線に乗るかは分かるが、どこの停留所で降りるかは不明なため推定:1つの停留所で複数路線)、運行会社と乗客の両者のメリットを考慮した最適解を求めることができる。このように、実際の待ち行列の人数を考慮することで、バス等の車両の運行会社のコストと、停留所での待ち時間を含めた乗客のコストとの和を最小化するようなバス等の車両の運行計画を作成することができるという効果を奏する。 [Main effects of the embodiment]
As described above, according to the present embodiment, the busoperation planning device 2 formulates an optimization problem in which the waiting time at the route signpost at the stop is used as the objective function and the queue is incorporated as the constraint. The breakdown is estimated using the observed value from the sensor 6 of the number of people in the queue (we know which route to take, but we do not know which stop to get off at, so it is estimated: multiple routes at one stop), An optimal solution can be found that takes into account the benefits for both the operating company and passengers. In this way, by considering the actual number of people in the queue, we can design a bus that minimizes the sum of the cost for the operating company of the bus and other vehicles and the cost for the passengers, including the waiting time at the stop. This has the effect of making it possible to create a vehicle operation plan.
以上説明したように本実施形態によれば、バス運行計画装置2は、停留所における路線の標識柱での待ち時間を目的関数に、待ち行列を制約条件に取り入れた最適化問題を定式化して、待ち行列の人数のセンサ6からの観測値を用いて、内訳を推定して(どの路線に乗るかは分かるが、どこの停留所で降りるかは不明なため推定:1つの停留所で複数路線)、運行会社と乗客の両者のメリットを考慮した最適解を求めることができる。このように、実際の待ち行列の人数を考慮することで、バス等の車両の運行会社のコストと、停留所での待ち時間を含めた乗客のコストとの和を最小化するようなバス等の車両の運行計画を作成することができるという効果を奏する。 [Main effects of the embodiment]
As described above, according to the present embodiment, the bus
〔補足〕
本発明は上述の実施形態に限定されるものではなく、以下に示すような構成又は処理(動作)であってもよい。 〔supplement〕
The present invention is not limited to the above-described embodiments, and may have the following configuration or processing (operation).
本発明は上述の実施形態に限定されるものではなく、以下に示すような構成又は処理(動作)であってもよい。 〔supplement〕
The present invention is not limited to the above-described embodiments, and may have the following configuration or processing (operation).
バス運行計画装置2の各機能構成は、上述のようにコンピュータとプログラムによって実現できるが、このプログラムを(非一時的な)記録媒体に記録して提要することも、インターネット等のネットワークを通して提供することも可能である。
Each functional configuration of the bus operation planning device 2 can be realized by a computer and a program as described above, but this program can also be recorded on a (non-temporary) recording medium and presented, or it can be provided through a network such as the Internet. It is also possible.
1 通信システム
2 バス運行計画装置(車両運行計画装置の一例)
4 停留所
5a,5b 標識柱
6a,6b センサ
7 営業所
8 バス(車両の一例)
9 通信端末
10 端末位
21 送受信部(送信部の一例、受信部の一例)
22 運行計画作成部
23 待ち行列人数推定部
29 記憶・読出部
31 停留所DB
32 路線DB
33 行列人数DB
34 乗車人数DB
35 需要予測DB
100 通信ネットワーク 1Communication system 2 Bus operation planning device (an example of vehicle operation planning device)
4 Stops 5a, 5b Signposts 6a, 6b Sensor 7 Office 8 Bus (an example of vehicle)
9Communication terminal 10 Terminal position 21 Transmitting/receiving section (an example of a transmitting section, an example of a receiving section)
22 Operationplan creation section 23 Queue number estimation section 29 Storage/reading section 31 Stop DB
32 Route DB
33 Number of people in line DB
34 Number of passengers DB
35 Demand forecast DB
100 Communication network
2 バス運行計画装置(車両運行計画装置の一例)
4 停留所
5a,5b 標識柱
6a,6b センサ
7 営業所
8 バス(車両の一例)
9 通信端末
10 端末位
21 送受信部(送信部の一例、受信部の一例)
22 運行計画作成部
23 待ち行列人数推定部
29 記憶・読出部
31 停留所DB
32 路線DB
33 行列人数DB
34 乗車人数DB
35 需要予測DB
100 通信ネットワーク 1
4 Stops 5a,
9
22 Operation
32 Route DB
33 Number of people in line DB
34 Number of passengers DB
35 Demand forecast DB
100 Communication network
Claims (7)
- 車両運行の計画を行う車両運行計画装置であって、
各停留所の車両の路線毎の現在の観測時刻における待ち行列人数と始発から現在時刻までの乗車人数の累計との和と、一つ前の観測時刻における運行計画の路線選択人数から、出発地別かつ目的地別に集計した各停留所の車両の路線毎の路線選択人数を推定する待ち行列人数推定部と、
現在の観測時刻以降の想定する乗客需要の予測人数及び前記待ち行列人数推定部によって推定された現在の観測時刻における前記路線選択人数から、前記車両の運行会社と乗客が前記現在の観測時刻以降に合理的に行動することを仮定して運行計画を作成する運行計画作成部と、
を有する車両運行計画装置。 A vehicle operation planning device that plans vehicle operation,
Based on the sum of the number of people queuing at each stop for each route at the current observation time and the cumulative number of passengers from the first train to the current time, and the number of people selected for the route in the operation plan at the previous observation time, we calculate and a queuing number estimating unit that estimates the number of people who select a route for each route of vehicles at each stop, tabulated by destination;
Based on the predicted number of passengers for expected passenger demand after the current observation time and the number of people selected for the route at the current observation time estimated by the queue number estimator, the operating company of the vehicle and the number of passengers will be an operation plan creation department that creates an operation plan assuming that people act rationally;
A vehicle operation planning device with - 前記待ち行列人数推定部は、始発から前記一つ前の観測時刻における、出発地別かつ目的地別に集計した各停留所の車両の路線毎の前記路線選択人数の累計に基づいて比例配分することで、前記路線選択人数を推定する、請求項1に記載の車両運行計画装置。 The number of people in the queue is estimated by proportionally distributing the number of people in the queue based on the cumulative total of the number of people who select the route for each route of vehicles at each stop, calculated by departure point and destination, from the first train to the previous observation time. 2. The vehicle operation planning device according to claim 1, wherein the vehicle operation planning device estimates the number of people choosing the route.
- 請求項1又は2に記載の車両運行計画装置であって、
前記各停留所の車両の路線毎に待ち行列人数を観測することで当該観測の結果を示す観測データを送信するセンサから前記観測データを受信する受信部、を有する車両運行計画装置。 The vehicle operation planning device according to claim 1 or 2,
A vehicle operation planning device comprising: a receiving unit that receives observation data from a sensor that observes the number of people queuing for each line of vehicles at each of the stops and transmits observation data indicating the result of the observation. - 請求項1乃至3のいずれか一項に記載の車両運行計画装置であって、
前記運行計画作成部によって作成された運行計画のデータを車両に関わる通信端末に送信する送信部を有する車両運行計画装置。 The vehicle operation planning device according to any one of claims 1 to 3,
A vehicle operation planning device including a transmitting section that transmits data of the operation plan created by the operation plan creating section to a communication terminal related to the vehicle. - 前記車両はオンデマンドの運行が可能なバスである請求項1乃至4のいずれか一項に記載の車両運行計画装置。 The vehicle operation planning device according to any one of claims 1 to 4, wherein the vehicle is a bus capable of on-demand operation.
- 車両運行の計画を行う車両運行計画方法であって、
コンピュータが、
各停留所の車両の路線毎の現在の観測時刻における待ち行列人数と始発から現在時刻までの乗車人数の累計との和と、一つ前の観測時刻における運行計画の路線選択人数から、出発地別かつ目的地別に集計した各停留所の車両の路線毎の路線選択人数を推定し、
現在の観測時刻以降の想定する乗客需要の予測人数及び前記推定された現在の観測時刻における前記路線選択人数から、前記車両の運行会社と乗客が前記現在の観測時刻以降に合理的に行動することを仮定して運行計画を作成する、
車両運行計画方法。 A vehicle operation planning method for planning vehicle operation, the method comprising:
The computer is
Based on the sum of the number of people queuing at each stop for each route at the current observation time and the cumulative number of passengers from the first train to the current time, and the number of people selected for the route in the operation plan at the previous observation time, we calculate Then, estimate the number of people choosing each route for vehicles at each stop, tabulated by destination.
The operating company and passengers of the vehicle should act rationally after the current observation time based on the predicted number of passengers expected to be expected after the current observation time and the number of people who have selected the route at the estimated current observation time. Create an operation plan assuming that
Vehicle operation planning method. - コンピュータに、請求項6に記載の方法を実行させるプログラム。 A program that causes a computer to execute the method according to claim 6.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
PCT/JP2022/011088 WO2023170964A1 (en) | 2022-03-11 | 2022-03-11 | Vehicle service planning device, vehicle service planning assistance method, and program |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
PCT/JP2022/011088 WO2023170964A1 (en) | 2022-03-11 | 2022-03-11 | Vehicle service planning device, vehicle service planning assistance method, and program |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2023170964A1 true WO2023170964A1 (en) | 2023-09-14 |
Family
ID=87936528
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/JP2022/011088 WO2023170964A1 (en) | 2022-03-11 | 2022-03-11 | Vehicle service planning device, vehicle service planning assistance method, and program |
Country Status (1)
Country | Link |
---|---|
WO (1) | WO2023170964A1 (en) |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2010244177A (en) * | 2009-04-02 | 2010-10-28 | Av Planning Center:Kk | Demand bus system |
JP2015184779A (en) * | 2014-03-20 | 2015-10-22 | 株式会社日立製作所 | Operation plan server and train diagram preparation method |
JP2020160605A (en) * | 2019-03-25 | 2020-10-01 | 株式会社日立製作所 | Movement service system and movement service provision method |
JP2021177411A (en) * | 2019-06-28 | 2021-11-11 | 株式会社NearMe | Program, information processing method, and information processor |
-
2022
- 2022-03-11 WO PCT/JP2022/011088 patent/WO2023170964A1/en unknown
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2010244177A (en) * | 2009-04-02 | 2010-10-28 | Av Planning Center:Kk | Demand bus system |
JP2015184779A (en) * | 2014-03-20 | 2015-10-22 | 株式会社日立製作所 | Operation plan server and train diagram preparation method |
JP2020160605A (en) * | 2019-03-25 | 2020-10-01 | 株式会社日立製作所 | Movement service system and movement service provision method |
JP2021177411A (en) * | 2019-06-28 | 2021-11-11 | 株式会社NearMe | Program, information processing method, and information processor |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Taniguchi et al. | Intelligent transportation system based dynamic vehicle routing and scheduling with variable travel times | |
Wallar et al. | Vehicle rebalancing for mobility-on-demand systems with ride-sharing | |
Ashkrof et al. | Understanding ride-sourcing drivers' behaviour and preferences: Insights from focus groups analysis | |
Nourinejad et al. | Vehicle relocation and staff rebalancing in one-way carsharing systems | |
US20190108468A1 (en) | Method and apparatus to operate smart mass transit systems with on-demand rides, dynamic routes and coordinated transfers | |
JP6589499B2 (en) | Action control system and action control method | |
US20100299177A1 (en) | Dynamic bus dispatching and labor assignment system | |
CN109948854B (en) | Intercity network taxi booking order distribution method based on multi-objective optimization | |
JP2002342873A (en) | Bus operation scheduling system | |
Petit et al. | Multiline bus bunching control via vehicle substitution | |
Ishaq et al. | Designing bus rapid transit systems: Lessons on service reliability and operations | |
TWI706339B (en) | Delivery planning system, delivery planning method and program | |
Manasra et al. | Optimization-based operations control for public transportation service with transfers | |
Ebben | Logistic control in automated transportation networks | |
JP7520706B2 (en) | Operation support system and operation support method | |
Ceder | Integrated smart feeder/shuttle transit service: simulation of new routing strategies | |
Takamatsu et al. | Bus timetable design to ensure smooth transfers in areas with low-frequency public transportation services | |
WO2023170964A1 (en) | Vehicle service planning device, vehicle service planning assistance method, and program | |
Beojone et al. | Relocation incentives for ride-sourcing drivers with path-oriented revenue forecasting based on a Markov Chain model | |
Yu et al. | Time window optimization for attended home service delivery under multiple sources of uncertainties | |
Li et al. | Real-time scheduling on a transit bus route: a 0-1 stochastic programming model | |
Chaturvedi et al. | A multi-modal ride sharing framework for last mile connectivity | |
Sánchez-Martínez | Real-time operations planning and control of high-frequency transit | |
Deng et al. | A modelling study of a taxi service operation | |
Galagedera et al. | Airport curbside and parking area operations at BIA–analysis of user behavior |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 22930944 Country of ref document: EP Kind code of ref document: A1 |