Public transportation system scheduling method, device and equipment based on activated stations and medium

Abstract

The invention discloses a bus system scheduling method, device and equipment based on activated stations and a medium, and relates to the field of vehicle scheduling, and the method comprises the steps: for any iteration step, according to the activation state of each current station, updating the activation states of all stations based on a preset constraint condition, calculating a target function value under the condition that the current station is activated; if the target function value is smaller than the set threshold value, the current station activation condition serves as the optimal station activation condition, and otherwise, the next iteration step is carried out; and determining the next destination station of the bus and the shortest space-time path from the bus to the next destination station according to the activation condition of the optimal station. According to the invention, the cost of a bus company is reduced, the waiting time of the passengers on the bus stations and the buses is reduced without changing the travel mode of the passengers, the actual road network pressure is reduced, and the urban traffic efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle scheduling, and in particular, to a bus system scheduling method, device, equipment and medium based on activated stations. Background Art

[0002] While the demand for urban travel increases, the travel modes are becoming more and more diversified. New transportation modes such as subways, customized bus systems, and carpooling systems have a great impact on the traditional bus system. The problems presented by the traditional bus system are basically in the following two aspects: it is unable to flexibly adjust the timetable according to time-dependent demands, and unable to flexibly adjust the route according to the traffic starting and ending points of passengers, especially showing obvious disadvantages when serving long-distance demands. The existing solutions to the problems of the traditional bus system are to propose some new customized bus systems (demand-responsive bus systems) to serve passengers with common demands or to improve the per-passenger fare for travel-as-a-service. However, improving the service quality of the entire bus system by increasing the number of buses will not only increase the costs of bus companies, but also increase the pressure on the actual road network, causing unnecessary congestion and reducing the passing efficiency of buses. At the same time, the reservation-based travel mode is different from the timetable-based travel mode, and passengers need to learn and adapt to the new mode, increasing their travel burden. Summary of the Invention

[0003] The purpose of the present application is to provide a bus system scheduling method, device, equipment and medium based on activated stations, which can reduce the waiting time of passengers at bus stops and on buses without changing the travel mode of passengers, reduce the pressure on the actual road network, and improve the urban passing efficiency.

[0004] To achieve the above purpose, the present application provides the following solutions:

[0005] In a first aspect, the present application provides a bus system scheduling method based on activated stations, including:

[0006] For any iteration step, based on the activation status of current stations and preset constraint conditions, update the activation status of all stations, and calculate the objective function value under the current station activation situation; wherein, the preset constraint conditions include the time constraint for buses to leave stations, the time constraint for buses to arrive at stations, the forced activation constraint, the station service time constraint, and the station waiting passenger constraint; the objective function value includes the passenger waiting time cost, the passenger travel time cost on the bus, and the operator operation cost;

[0007] If the objective function value is less than the set threshold, then take the current station activation situation as the optimal station activation situation, otherwise proceed to the next iteration step;

[0008] Based on the optimal station activation situation, determine the next destination station of the bus and the spatio-temporally shortest path for the bus to reach the next destination station.

[0009] In a second aspect, the present application provides a bus system scheduling device based on activated stations, including:

[0010] An activation status update module, configured to, for any iteration step, update the activation status of all stations based on the preset constraint conditions according to the current activation status of each station, and calculate the objective function value under the current station activation situation; wherein, the preset constraint conditions include the time constraint for the bus to leave the station, the time constraint for the bus to reach the station, the forced activation constraint, the station service time constraint, and the station waiting passenger constraint; the objective function value includes the passenger waiting time cost, the passenger in-vehicle travel time cost, and the operator operation cost;

[0011] An iteration module, configured to, when the objective function value is less than the set threshold, use the current station activation situation as the optimal station activation situation, otherwise proceed to the next iteration step;

[0012] A path determination module, configured to, based on the optimal station activation situation, determine the next destination station of the bus and the spatio-temporally shortest path for the bus to reach the next destination station.

[0013] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the above-mentioned bus system scheduling method based on activated stations.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned bus system scheduling method based on activated stations is implemented.

[0015] According to the specific embodiments provided by the present application, the present application has the following technical effects:

[0016] The present application provides a bus system scheduling method, device, equipment and medium based on activation sites. Based on the time constraints for buses to leave sites, the time constraints for buses to arrive at sites, mandatory activation constraints, site service time constraints and site waiting passenger constraints, with the goal of minimizing the sum of the passenger waiting time cost, the passenger travel time cost on the bus and the operator operation cost, the activation status of each site is updated, and then the next destination site of the bus and the spatio-temporal shortest path for the bus to reach the next destination site are determined, which reduces the cost of the bus company while improving the efficiency of the bus company, and reduces the waiting time of passengers at bus stops and on buses without changing the passenger travel mode, reduces the actual road network pressure, and improves the urban traffic efficiency. Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required to be used in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0018] Figure 1 It is an application environment diagram of a bus system scheduling method based on activation sites in an embodiment of the present application;

[0019] Figure 2 It is a flowchart of a bus system scheduling method based on activation sites provided in an embodiment of the present application;

[0020] Figure 3 It is a product structure diagram of a bus system scheduling method based on activation sites provided in an embodiment of the present application;

[0021] Figure 4 It is a functional module diagram of a bus system scheduling device based on activation sites provided in an embodiment of the present application;

[0022] Figure 5 It is a structure diagram of a computer device provided in an embodiment of the present application. Detailed Embodiments

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present application belong to the scope of protection of the present application.

[0024] Starting from the original infrastructure of traditional buses, this application proposes a semi-flexible bus system scheduling method based on activated stops without the need for advance reservation, which basically covers the functions of various bus systems such as traditional bus systems, demand-responsive bus systems, and feeder bus systems. At the same time, in response to uneven demand distribution and the actual road network situation, stop and between-stop control is adopted to solve the problem of large-scale multi-level route optimization.

[0025] To make the above objects, features, and advantages of this application more obvious and understandable, the following further details this application in conjunction with the accompanying drawings and specific embodiments.

[0026] The bus system scheduling method based on activated stops provided by the embodiments of this application can be applied to an application environment such as Figure 1 shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the activation status of each current stop to the server 104. After receiving the activation status of each current stop, the server 104 updates the activation status of all stops based on preset constraint conditions, and calculates the objective function value in the case of the current stop activation. If the objective function value is less than the set threshold, the current stop activation situation is used as the optimal stop activation situation; otherwise, the next iteration step is performed; according to the optimal stop activation situation, the next destination stop of the bus and the spatio-temporal shortest path for the bus to reach the next destination stop are determined. The server 104 can feedback the next destination stop of the bus and the spatio-temporal shortest path for the bus to reach the next destination stop to the terminal 102. In addition, in some embodiments, the bus system scheduling method based on activated stops can also be implemented separately by the server 104 or the terminal 102.

[0027] Among them, the terminal 102 can be, but is not limited to, various desktop computers, laptop computers, smartphones, tablets, Internet of Things devices, and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented by an independent server or a server cluster composed of multiple servers, and can also be a cloud server.

[0028] In an exemplary embodiment, as Figure 2 shown, a bus system scheduling method based on activated stops is provided. This method is executed by a computer device, and can be specifically executed alone by a computer device such as a terminal or a server, or jointly executed by a terminal and a server. In the embodiments of this application, taking this method as being applied to Figure 1Taking the server 104 in [as an example], the following steps 201 to 203 are included.

[0029] Step 201, for any iteration step, based on the activation status of each current site and the preset constraint conditions, update the activation status of all sites and calculate the objective function value under the condition that the current site is activated.

[0030] In a specific application example, first initialize and activate the starting site of each shift of buses and all the already activated sites, activate the sites that meet the preset constraint conditions, and calculate the objective function value under the condition that the current site is activated. In each iteration step, all sites are sampled through the Bernoulli distribution, the activation probability of the current site is updated through sampling, a new activation situation is obtained by rounding, and then the activation status of all sites is updated based on the preset constraint conditions, and the objective function value under the condition that the current site is activated is calculated.

[0031] Among them, the preset constraint conditions include the time constraint for buses to leave the site, the time constraint for buses to arrive at the site, the forced activation constraint, the site service time constraint, and the site waiting passenger constraint.

[0032] (1) For the time D when the i-th bus leaves the (j + 1)-th site i,j+1 , if the (j + 1)-th site is not activated, D i,j+1 is equal to the time D when the i-th bus leaves the j-th site i,j ; if the (j + 1)-th site is activated, D i,j+1 is equal to the time A when the i-th bus arrives at the (j + 1)-th site i,j+1 plus the stop time τ of the i-th bus at the (j + 1)-th site i,j+1 , that is, the time constraint for the bus to leave the site is:

[0033]

[0034] Among them, D i,j+1 is the time when the i-th bus leaves the (j + 1)-th site, D i,j is the time when the i-th bus leaves the j-th site, x i,j+1 is the activation status of the (j + 1)-th site for the i-th bus. If the (j + 1)-th site is activated, then x i,j+1 = 1, otherwise x i,j+1 = 0, A i,j+1 is the time when the i-th bus arrives at the (j + 1)-th site, BT is the earliest departure time of the bus, f is the departure frequency from the starting station, τ i,j+1 is the stop time of the i-th bus at the (j + 1)-th site, i is the bus number, and j is the site number.

[0035] (2) For the arrival time A of the i-th bus at the (j + 1)-th stop i,j+1 , if the (j + 1)-th stop is not activated, A i,j+1 equals the arrival time A of the i-th bus at the j-th stop i,j ; if the (j + 1)-th stop is activated, A i,j+1 equals the departure time of the i-th bus from the j-th stop plus the travel time r from the last activated stop (the k-th stop) before the (j + 1)-th stop to the (j + 1)-th stop j,k (D i,j ), that is, the time constraint for the bus to arrive at the stop is:

[0036]

[0037] where A i,j+1 is the arrival time of the i-th bus at the (j + 1)-th stop, A i,j is the arrival time of the i-th bus at the j-th stop, D i,j is the departure time of the i-th bus from the j-th stop, x i,j+1 is the activation status of the (j + 1)-th stop for the i-th bus. If the (j + 1)-th stop is activated, then x i,j+1 = 1, otherwise x i,j+1 = 0, r k,j+1 (D i,j ) is the travel time from the k-th stop to the (j + 1)-th stop at time D i,j . The k-th stop represents the last activated stop before the (j + 1)-th stop, and x i,k is the activation status of the k-th stop for the i-th bus, and x i,h is the activation status of the h-th stop for the i-th bus.

[0038] (3) The forced activation constraints are the activation of the starting stop of the bus, the activation of the terminal stop of the bus, and the activation of the stops where there is a demand for passengers to get off. The existing method sets a penalty function to avoid the stops where passengers get off from not being served. This application strictly stipulates that the stops with the demand for getting off passengers must be served, which is more in line with the actual situation.

[0039] (4) Define the constraint conditions generated by clarifying the relationship between two adjacent buses (the $a$-th bus and the $b$-th bus) at the same station. To avoid a station not being served for a long time, set a time threshold $T_0$ to represent the unserved time threshold of the $j$-th station, and require that stations exceeding the set time threshold must be served. At the same time, to avoid buses gathering, set a minimum headway $H_0$, and require that a station cannot be served twice in a short time. The above conditions are equivalent to the $j$-th station must be served within the time window $[H_0, T_0]$, that is, the station service time constraint is:

[0040] $H_0\leq A$ a,j $-D$ b,j $\leq T_0$;

[0041] where $H_0$ is the minimum headway, $T_0$ is the set time threshold, $A$ a,j is the arrival time of the $a$-th bus at the $j$-th station, $D$ b,j is the departure time of the $b$-th bus from the $j$-th station, and the $a$-th bus and the $b$-th bus are two adjacent buses.

[0042] (5) Define the constraint conditions generated by clarifying the composition of the number of waiting passengers at the station when the $a$-th bus serves the $j$-th station. The first part of the station waiting passenger constraint is the passengers arriving during the time interval from the departure of the $a$-th bus from the $j$-th station to the arrival of the $b$-th bus at the $j$-th station; the second part is the passengers not served by the $a$-th bus at the $j$-th station. The station waiting passenger constraint is:

[0043]

[0044]

[0045] where $W$ a,j is the number of people waiting for the $a$-th bus at the $j$-th station, $N$ is the total number of stations, $D$ a,j is the departure time of the $a$-th bus from the $j$-th station, $t$ a,j and $t$ b,j are auxiliary variables, $U$ j,m $(t)$ is the number of people from the $j$-th station to the $m$-th station at time $t$, $F$ a,j is the number of people who did not board the $a$-th bus at the $j$-th station, $M$ a,j is the number of people on the $a$-th bus when it arrives at the $j$-th station, $V$ a,j is the number of people getting off the $a$-th bus at the $j$-th station, $C$ a is the capacity of the $a$-th bus, $P$ a,j is the ratio of the passengers boarding the $a$-th bus at the $j$-th station to the waiting passengers, $U$ a,j,n$U_{aj}^n$ is the number of passengers getting on the $a$-th bus at the $j$-th stop and getting off at the $n$-th stop. j,n $U_{j}^n(t)$ is the number of people from the $j$-th stop to the $n$-th stop at time $t$. a,j $U_{aj}^j$ is the actual number of passengers getting on the $a$-th bus at the $j$-th stop. a,n,j $U_{an}^j$ is the number of passengers getting on the $a$-th bus at the $n$-th stop and getting off at the $j$-th stop.

[0046] Assume that the bus service stops follow the first-come, first-served rule. Then the $a$-th bus can serve the passengers before time $t$ at the $j$-th stop. Since the passenger arrival rate follows a Poisson distribution, the ratio of $(t - t_{j}^a)$ to $D - t_{j}^a$ is equal to the ratio of the passengers served by the $a$-th bus at the $j$-th stop to all the passengers waiting at the $j$-th stop. If the $a$-th bus serves all the passengers at the $j$-th stop, i.e., when $P = 1$, then $t = D$. a,j before time $t$, since the passenger arrival rate follows a Poisson distribution, $t$ h,j $-t$ b,j occupies $D$ a,j $-t$ b,j The ratio is equal to the ratio of the passengers served by the $a$-th bus at the $j$-th stop to all the passengers waiting at the $j$-th stop. If the $a$-th bus serves all the passengers at the $j$-th stop, i.e., when $P = 1$, then $t = D$. a,j $= 1$ when $t$ a,j $= D$ a,j .

[0047] Assume that the number of passengers arriving at the $j$-th stop follows a Poisson distribution with an arrival rate of . Then the original Poisson stream arriving at the $j$-th stop can be divided into multiple independent Poisson sub-streams. Each Poisson sub-stream corresponds to the passenger stream from the $j$-th stop to the $m$-th stop. The average arrival rate of each Poisson sub-stream is equal to the original arrival rate divided by the number of destinations $(N - j)$, i.e., When the $a$-th bus serves the origin station $t$ a,j from time to $D$ a,j The sum of the number of passengers from the $j$-th stop to the $N$-th stop at time is the number of passengers $W$ waiting for the $a$-th bus at the $j$-th stop. a,j When the number of passengers waiting for the $a$-th bus at the $j$-th stop is less than the remaining seats on the $a$-th bus after passengers get off, then all passengers can get on, i.e., the number of passengers not getting on the $a$-th bus at the $j$-th stop is equal to 0. Otherwise, it is equal to the waiting number minus the number of passengers getting on according to the first-come, first-served rule and the remaining seats after passengers get off.

[0048] Since bus boarding and alighting occur simultaneously, the waiting time at the stop is expressed as the maximum of the boarding time and the alighting time: where $\tau$ i,j is the docking time of the $i$-th bus at the $j$-th stop. i,j is the actual number of passengers getting on the $i$-th bus at the $j$-th stop. i,jLet \(d_{ij}\) be the number of passengers getting off the \(i\)-th bus at the \(j\)-th stop, \(c\) be the boarding time per passenger, and \(d\) be the alighting time per passenger.

[0049] The objective function value includes the passenger waiting time cost, the passenger in-vehicle travel time cost, and the operator's operation cost:

[0050] \(\min g=\alpha_1g_1 + \alpha_2g_2+\alpha_3g_3\);

[0051]

[0052]

[0053]

[0054] where \(g_1\) is the passenger waiting time cost, \(g_2\) is the passenger in-vehicle travel time cost, \(g_3\) is the operator's operation cost, \(\alpha_1\) is the importance of the passenger waiting time cost, \(\alpha_2\) is the importance of the passenger in-vehicle travel time cost, \(\alpha_3\) is the importance of the operator's operation cost, \(M\) is the total number of buses, \(U\) i,j is the actual number of passengers boarding the \(i\)-th bus at the \(j\)-th stop, \(t\) i,j and \(t\) b,j are auxiliary variables, \(F\) i,j is the number of passengers who did not board the \(i\)-th bus at the \(j\)-th stop, \(D\) i,j is the time when the \(i\)-th bus leaves the \(j\)-th stop, \(x\) i,k is the activation status of the \(k\)-th stop for the \(i\)-th bus, \(x\) a,j is the activation status of the \(j\)-th stop for the \(a\)-th bus.

[0055] Step 202: If the objective function value is less than the set threshold, then take the current stop activation situation as the optimal stop activation situation; otherwise, proceed to the next iteration step.

[0056] In a specific application example, when the objective function value \(g\) s calculated in the \(s\)-th iteration step is less than the set threshold \(g^*\), take the current stop activation situation as the optimal stop activation situation, and let \(g^* = g\) s . If the number of iteration steps is greater than the maximum number of iteration steps or \(|g\) s - \(g^*|\lt10\) -3 , then output the optimal stop activation situation.

[0057] Step 203: According to the optimal stop activation situation, determine the next destination stop of the bus and the spatio-temporally shortest path for the bus to reach the next destination stop.

[0058] In a specific application example, the next destination station is fed back to the GPS of the bus driver terminal, and the spatio-temporal shortest distance from the current station to the next destination station is planned through the shortest path algorithm to assist the driver to go to the next destination station.

[0059] In another exemplary embodiment, the bus system scheduling method provided by the present application is based on Figure 3 the structure shown. The scheduling host module 301 includes a database server 305 and a scheduling algorithm 306. The database server 305 stores the data obtained by the card readers 310 in the station data acquisition module 303 and the vehicle terminal device module 304, and transmits the data to the scheduling algorithm 306 to generate a scheduling strategy. The generated scheduling strategy is fed back to the vehicle-mounted positioning system 309 in the vehicle terminal device module 304 through the communication network module 302 to help the driver with transportation. The communication network module 302 includes a cellular network 307 and an Ethernet network 308.

[0060] The present application also compares the traditional bus system with the present application. The results are shown in Table 1. It can be seen from Table 1 that when the service rate is the same, the number of buses required by the present application is less; when the number of buses is the same, the service rate of the present application is higher; under other indicators, the present application has a slight advantage.

[0061] Table 1 Comparison between the traditional bus system and the present application

[0062]

[0063] The present application uses a mixed integer programming model (including the above-mentioned constraint conditions and the calculation formula of the objective function value) to solve the optimal station activation problem of buses. The mixed integer programming model determines the optimal station activation sequence set in continuous iteration according to the station service conditions of the previous buses, the passenger demand information in the buses, the global station information, and the historical data of passenger demand, so as to determine the next destination station, and feeds back the next destination station to the vehicle-mounted GPS of the bus driver terminal to assist the driver to reach the next activated bus station.

[0064] The present application adopts the activation mechanism of stations to form an intelligent bus system, which has the functions of the traditional bus system and some customized bus systems, improves the efficiency of the bus company while reducing the costs of the bus company. And it reduces the waiting time of passengers at bus stops and on buses without changing the travel mode of passengers. The present application formulates the optimal bus routes at the macro level and the optimal bus trajectories on some congested sections at the micro level, reduces the actual road network pressure, and improves the urban traffic efficiency.

[0065] Based on the same inventive concept, an embodiment of the present application further provides a bus system scheduling device for implementing the bus system scheduling method involved above. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the bus system scheduling device provided below can refer to the limitations on the bus system scheduling method in the above text and will not be elaborated here.

[0066] In an exemplary embodiment, as Figure 4 shown, a bus system scheduling device based on activation sites includes: an activation status update module 401, an iteration module 402, and a path determination module 403.

[0067] The activation status update module 401 is used for any iteration step to update the activation status of all sites based on the preset constraint conditions according to the current activation status of each site, and calculate the objective function value under the current site activation situation.

[0068] Among them, the preset constraint conditions include the time constraint for the bus to leave the site, the time constraint for the bus to arrive at the site, the forced activation constraint, the site service time constraint, and the site waiting passenger constraint. The objective function value includes the passenger waiting time cost, the passenger travel time cost in the vehicle, and the operator operation cost.

[0069] The iteration module 402 is used to take the current site activation situation as the optimal site activation situation when the objective function value is less than the set threshold, otherwise proceed to the next iteration step.

[0070] The path determination module 403 is used to determine the next destination site of the bus and the spatio-temporally shortest path of the bus to the next destination site according to the optimal site activation situation.

[0071] In an exemplary embodiment, a computer device is provided. This computer device can be a server or a terminal, and its internal structure diagram can be as Figure 5As shown in the figure. The computer device includes a processor, a memory, an input / output interface (Input / Output, I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the activation status of each current site. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a bus system scheduling method based on activated sites.

[0072] Those skilled in the art can understand that Figure 5 the structure shown in the figure is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0073] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, it implements the steps in the above method embodiments.

[0074] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, it implements the steps in the above method embodiments.

[0075] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data that have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0076] In this application, all actions of obtaining signals, information, or data are carried out on the premise of complying with the corresponding data protection regulations and policies of the country where it is located and obtaining authorization from the owner of the corresponding device.

[0077] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the various embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0078] The databases involved in the various embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the various embodiments provided in this application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logics, data processing logics based on quantum computing, etc., without limitation.

[0079] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0080] Specific examples are used in this article to elaborate on the principles and implementation methods of this application. The descriptions of the above embodiments are only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A bus system scheduling method based on activation sites, characterized in that The method includes: For any iteration step, based on the activation status of current stations and preset constraint conditions, update the activation status of all stations and calculate the objective function value when the current station is activated; wherein, the preset constraint conditions include the time constraint for a bus to leave a station, the time constraint for a bus to arrive at a station, the forced activation constraint, the station service time constraint, and the station waiting passenger constraint; the objective function value includes the passenger waiting time cost, the passenger travel time cost on the bus, and the operator operation cost; If the objective function value is less than the set threshold, take the current station activation situation as the optimal station activation situation; otherwise, proceed to the next iteration step; Based on the optimal station activation situation, determine the next destination station of the bus and the spatio-temporal shortest path for the bus to reach the next destination station.

2. The bus system scheduling method based on an activation site according to claim 1, wherein The time constraint for a bus to leave a station is: Among them, D i,j+1 is the departure time of the $i$-th bus from the $(j + 1)$-th stop, and D i,j is the departure time of the $i$-th bus from the $j$-th stop. $x$ i,j+1 is the activation status of the $(j + 1)$-th stop for the $i$-th bus. If the $(j + 1)$-th stop is activated, then $x$ i,j+1 = 1; otherwise $x$ i,j+1 = 0. $A$ i,j+1 is the arrival time of the $i$-th bus at the $(j + 1)$-th stop, and $\tau$ i,j+1 is the stop time of the $i$-th bus at the $(j + 1)$-th stop.

3. The bus system scheduling method based on an activation site according to claim 1, wherein The time constraint for a bus to arrive at a station is: Among them, A i,j+1 is the arrival time of the i-th bus at the (j + 1)-th stop, and A i,j is the arrival time of the i-th bus at the j-th stop. D i,j is the departure time of the i-th bus from the j-th stop. x i,j+1 is the activation status of the (j + 1)-th stop for the i-th bus. If the (j + 1)-th stop is activated, then x i,j+1 = 1; otherwise, x i,j+1 = 0. r k,j+1 (D i,j ) is the travel time from the k-th stop to the (j + 1)-th stop at time D i,j . The k-th stop represents the last activated stop before the (j + 1)-th stop. x i,k is the activation status of the k-th stop for the i-th bus, and x i,h is the activation status of the h-th stop for the i-th bus.

4. The bus system scheduling method based on an activation site according to claim 1, wherein The forced activation constraint is the activation of the bus departure station, the activation of the bus terminal station, and the activation of stations where there are passenger disembarkation requirements.

5. The bus system scheduling method based on an activation site according to claim 1, wherein The station service time constraint is: H0 ≤ A a,j -D b,j ≤ T0; where H0 is the minimum headway, T0 is the set time threshold, A a,j is the arrival time of the a-th bus at the j-th stop, D b,j is the departure time of the b-th bus from the j-th stop, and the a-th bus and the b-th bus are two adjacent buses.

6. The bus system scheduling method based on an activation site according to claim 1, wherein The station waiting passenger constraint is: Among them, W a,j is the number of people waiting for the ath bus at the jth station, N is the total number of stations, D a,j is the time when the ath bus leaves the jth station, t a,j and t b,j are auxiliary variables, U j,m (t) is the number of people from the jth station to the mth station at time t, F a,j is the number of people who did not board the ath bus at the jth station, M a,j is the number of people on the ath bus when it arrives at the jth station, V a,j is the number of people getting off the ath bus at the jth station, C a is the capacity of the ath bus, P a,j is the ratio of the passengers getting on the ath bus at the jth station to the waiting passengers, U a,j,n is the number of passengers getting on the ath bus from the jth station and getting off at the nth station, U j,n (t) is the number of people from the jth station to the nth station at time t, U a,j is the actual number of people getting on the ath bus at the jth station, U a,n,j is the number of passengers getting on the ath bus from the nth station and getting off at the jth station.

7. The bus system scheduling method based on an activation site according to claim 1, wherein Use the following formula to calculate the objective function value when the current station is activated: ming = α1g1 + α2g2 + α3g3; Among them, g1 is the passenger waiting time cost, g2 is the passenger in-vehicle travel time cost, g3 is the operator operation cost, α1 is the importance of the passenger waiting time cost, α2 is the importance of the passenger in-vehicle travel time cost, α3 is the importance of the operator operation cost, M is the total number of buses, U i,j is the actual number of passengers boarding the i-th bus at the j-th stop, t i,j and t b,j are auxiliary variables, F i,j is the number of people who did not board the i-th bus at the j-th stop, D i,j is the time when the i-th bus leaves the j-th stop, x i,k is the activation status of the k-th stop for the i-th bus, x a,j is the activation status of the j-th stop for the a-th bus.

8. An activation-site-based bus system scheduling device, which is applied to the activation-site-based bus system scheduling method according to any one of claims 1-7, and is characterized in that, The device includes: An activation status update module, configured to, for any iteration step, based on the activation status of current stations and preset constraint conditions, update the activation status of all stations and calculate the objective function value when the current station is activated; wherein, the preset constraint conditions include the time constraint for a bus to leave a station, the time constraint for a bus to arrive at a station, the forced activation constraint, the station service time constraint, and the station waiting passenger constraint; the objective function value includes the passenger waiting time cost, the passenger travel time cost on the bus, and the operator operation cost; An iteration module, configured to, when the objective function value is less than the set threshold, take the current station activation situation as the optimal station activation situation; otherwise, proceed to the next iteration step; A path determination module, configured to, based on the optimal station activation situation, determine the next destination station of the bus and the spatio-temporal shortest path for the bus to reach the next destination station.

9. A computer device, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the bus system scheduling method based on activated stations according to any one of claims 1 - 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the bus system scheduling method based on activated stations according to any one of claims 1 - 7.

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