Methods, devices and electronic equipment for coordinated passenger flow control of one-way rail transit lines

Abstract

This application provides a passenger flow collaborative control method, device, and electronic equipment for a one-way rail transit line. It includes: acquiring train operation parameters and station information for each station on the one-way rail transit line; determining the entry demand, passenger waiting time cost, and station capacity pressure for each station based on the train operation parameters and station information; constructing a passenger flow collaborative control model for each station based on the entry demand, passenger waiting time cost, station capacity pressure, train operation parameters, and station information; and using the passenger flow collaborative control model to regulate the train passenger capacity at each station, with the objectives being that the passenger waiting time cost is the same at all stations or the difference in waiting time cost is within a preset time range, and / or that the entry demand is the same at all stations or the difference in entry demand is within a preset demand range. This solves the problem of poor matching between train capacity and station demand in existing technologies, leading to long-term passenger congestion at some stations.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of passenger flow coordination control of one-way rail transit lines, in particular to a passenger flow coordination control method and device of one-way rail transit lines, a computer readable storage medium and an electronic device. BACKGROUND

[0002] In recent years, the total supply of urban rail transit network capacity, reliability and accessibility have been greatly improved, but the supply and demand contradiction in specific areas and time periods is still acute, becoming the difficulty of urban rail transit industry operation and emergency and the focus of intelligent rail construction. In order to alleviate the game and confrontation between passenger flow and capacity, targeted capacity adjustment and allocation is carried out according to the actual situation, which can play a multiplier effect in two types of scenarios of sudden large passenger flow and normal large passenger flow. The former type of measures mainly includes size adjustment, spare car and running temporary passenger, which is obviously characterized by emergency and rescue, and plays an important role, but the probability of occurrence is relatively small. The latter type focuses on solving the problem of system balance in the process of total supply and demand of urban rail transit, and the contradiction of local network supply and demand in some time periods, such as peak tidal type into the city on the main line, planned and continuous large-scale activities, etc. Compared with the former, operation scheduling needs to be normal in daily operation, which is under great pressure and needs technical support. It also needs to consider more economic cost of operation enterprise, passenger travel fairness and efficiency, social public opinion and other factors, which has more practical significance.

[0003] Rail transit is a typical complex system, whose network transportation capacity and safe operation level not only depends on the physical conditions of the original hardware system, but also depends on the scientificity and systematicness of management, organization and coordination control during operation, which is the key to whether a city or even a regional rail transit can maximize its value, and is the core of urban group, metropolitan area and cross-provincial rail transit emergency command system construction. From the nature of the system, the normal large passenger flow multi-station coordination flow control of urban rail transit is actually a problem of optimal allocation of line capacity and coordinated use of station capacity. The current research focuses in this field include multi-point flow coordination control model, control target and solution algorithm, etc. Among them, the control target is the core and premise, which plays a role in determining the control tone and process direction.

[0004] From the actual situation, several super large communities, satellite cities formed by high-density development around large cities, including cross-provincial rail, commuter traffic around the region is a hard demand. In recent years, first, the dumbbell type reflected by the cross-section distribution inferred by the data path is more prominent, and second, the out-of-network flow restriction contradiction reflected by the actual investigation of the data collection blind area has not been alleviated. Traffic travel is a typical group self-organizing behavior, and active control is the key to maximize the use of transport capacity resources. The timed supply and timed decline of transport capacity have their technical rules, and the maximum matching of demand-transport capacity is guaranteed in a specific period, which has special value for the combination of high-density development around large cities. SUMMARY

[0005] The main purpose of the present application is to provide a passenger flow cooperative control method, device, computer readable storage medium and electronic equipment of a one-way rail transit line, so as to at least solve the problem that the train carrying capacity and station demand matching degree of the prior art in the urban rail transit network is poor, resulting in long-time passenger gathering and retention in some stations.

[0006] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a passenger flow cooperative control method of a one-way rail transit line is provided, comprising: acquiring train running parameters of a one-way rail transit line and station information of each station, wherein the station information comprises maximum carrying passenger flow of each region of each station, real-time passenger flow of each region, queue number of a platform waiting area and actual boarding number, the region comprises an outdoor queuing area, an indoor waiting area and the platform waiting area, and the train running parameters comprise train capacity, adjacent train arrival time interval and stop duration; determining in-station demand, passenger waiting time cost and station carrying pressure of each station according to the train running parameters and the station information of each station, and constructing a passenger flow cooperative control model of each station based on the in-station demand, the passenger waiting time cost, the station carrying pressure, the train running parameters and the station information of each station, wherein the in-station demand represents the number of passengers to be boarded at the station; taking the same passenger waiting time cost or a waiting time cost difference within a preset time range of all stations, and / or the same in-station demand or an in-station demand difference within a preset demand range of all stations as the goal, and using the passenger flow cooperative control model of each station to regulate and control the train carrying capacity of each station.

[0007] Optionally, the in-station demand and the station carrying pressure of each station are determined according to the station information of each station, including: determining the in-station demand of each station according to a difference between a sum of real-time passenger flow of the in-station waiting area and the platform waiting area and the actual boarding number; and determining the station carrying pressure of each station according to a ratio of real-time passenger flow of each area of the station to a maximum carrying passenger flow of each area, wherein the station carrying pressure includes carrying pressures of the out-station queuing area, the in-station waiting area and the platform waiting area.

[0008] Optionally, the passenger waiting time cost of each station is determined according to the train operation parameter and the station information of each station, including: determining the passenger waiting time cost of each station according to a first formula: , wherein, is the passenger waiting time cost considering only one train interval stay of passengers, is a time interval of arrival of adjacent trains, is the stop duration, is a sum of real-time passenger flow of the in-station waiting area and the platform waiting area, and is the actual boarding number.

[0009] Optionally, the passenger waiting time cost of each station is determined according to the train operation parameter and the station information of each station, including: determining the passenger waiting time cost of each station according to a second formula: , wherein, is the passenger waiting time cost considering multiple train interval stays of passengers, is a time interval of arrival of adjacent trains, is the stop duration, k represents a kth train interval stay period, is a sum of real-time passenger flow of the in-station waiting area and the platform waiting area, and is the actual boarding number.

[0010] Optionally, the train passenger carrying capacity of each station is regulated by using the passenger flow coordination control model of each station, including: determining a first deviation factor according to the passenger waiting time cost of a target station and all stations, wherein the target station represents a station to be regulated in the train passenger carrying capacity; determining a second deviation factor according to the in-station demand of the target station and all stations; and regulating the train passenger carrying capacity of the target station by using the passenger flow coordination control model, with the first deviation factor and the second deviation factor being minimum as a target.

[0011] Optionally, the first deviation factor is determined according to the passenger waiting time cost of the target station and the passenger waiting time cost of all stations, including: determining the first deviation factor according to a third formula: , wherein, is the first deviation factor, is the multiple deviation of the passenger waiting time cost of the target station, is the average multiple deviation of the passenger waiting time cost of all stations, is the number of stations, , is the passenger waiting time cost of the target station considering that passengers stay for multiple intervals, is the passenger waiting time cost of the target station considering that passengers stay for one interval.

[0012] Optionally, the second deviation factor is determined according to the determination of the boarding demand of the target station and the boarding demand of all stations, including: determining the second deviation factor according to a fourth formula: , wherein, is the second deviation factor, is the boarding demand of the target station, is the average value of the boarding demand of all stations, is the number of stations.

[0013] According to another aspect of the present application, a passenger flow coordination control device for a one-way rail transit line is provided, including: an acquisition unit configured to acquire train operation parameters of the one-way rail transit line and station information of each station, wherein the station information includes maximum carrying passenger flow of each region of each station, real-time passenger flow of each region, number of people queuing in a platform waiting area, and actual number of people boarding, the region includes an off-station queuing area, an in-station waiting area, and the platform waiting area, and the train operation parameters include train capacity, adjacent train arrival time interval, and stop duration; a determination unit configured to determine boarding demand, passenger waiting time cost, and station carrying pressure of each station according to the train operation parameters and the station information of each station, and construct a passenger flow coordination control model of each station based on the boarding demand, the passenger waiting time cost, the station carrying pressure, the train operation parameters, and the station information of each station, wherein the boarding demand represents the number of passengers to be boarded at the station; and a regulation and control unit configured to take each station as a target, and adopt the passenger flow coordination control model of each station to regulate and control train carrying capacity of each station, with the same passenger waiting time cost or a passenger waiting time cost difference within a preset time range of all stations, and / or the same boarding demand or a boarding demand difference within a preset demand range of all stations.

[0014] According to still another aspect of the present application, a computer readable storage medium is provided, the computer readable storage medium comprising a stored program, wherein the computer readable storage medium is caused to perform any one of the passenger flow coordination control methods of the single-direction rail transit line when the program is run.

[0015] According to still another aspect of the present application, an electronic device is provided, comprising one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs comprise a program for performing any one of the passenger flow coordination control methods of the single-direction rail transit line.

[0016] By applying the technical solution of the present application, train operation parameters of the single-direction rail transit line and station information of each station are obtained, wherein the station information comprises maximum carrying passenger flow of each region of each station, real-time passenger flow of each region, number of passengers queuing in the platform waiting area, and actual boarding number of passengers, the region comprises an out-of-station queuing area, an in-station waiting area, and a platform waiting area, and the train operation parameters comprise train capacity, adjacent train arrival time interval, and stop duration; based on the train operation parameters and the station information of each station, the in-station demand quantity, passenger waiting time cost, and station carrying pressure of each station are determined, and a passenger flow coordination control model of each station is constructed based on the in-station demand quantity, passenger waiting time cost, station carrying pressure, train operation parameters, and station information of each station, wherein the in-station demand quantity represents the number of passengers waiting to board at the station; the train passenger carrying capacity of each station is regulated by the passenger flow coordination control model of each station, with the goal of the same passenger waiting time cost or the difference in waiting time cost within a preset time range of all stations, and / or the same in-station demand quantity or the difference in in-station demand quantity within a preset demand range of all stations. By collecting and analyzing train operation parameters and station information, the passenger flow state and the carrying capacity of each station can be accurately mastered, thereby providing a data basis for subsequent coordination control. By monitoring the real-time passenger flow of the out-of-station queuing area, the in-station waiting area, and the platform waiting area, it can be known in time which regions are close to or exceed the maximum carrying passenger flow, and then corresponding regulation measures are taken. In addition, the consideration of parameters such as train capacity, arrival time interval, and stop duration helps to evaluate the carrying capacity and operation efficiency of the train, ensuring balanced passenger service among different stations. Through the combination of these technical features, the present application solves the passenger flow management problem caused by information asymmetry in traditional rail transit, realizes efficient and accurate control of the single-direction line, and improves the passenger travel experience and the overall operation efficiency of the system. Therefore, the problem of poor matching between train capacity and station demand in the existing technology in the urban rail transit network is solved, which leads to long-term gathering and retention of passengers in some stations. BRIEF DESCRIPTION OF DRAWINGS

[0017] The drawings constituting a part of the specification illustrate the preferred embodiments of the present application and the explanatory views used to explain the present application, and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 A hardware structure block diagram of a mobile terminal for performing a passenger flow collaborative control method of a one-way rail transit line is shown according to an embodiment of the present application;

[0019] Figure 2 A flowchart of a passenger flow collaborative control method of a one-way rail transit line is shown according to an embodiment of the present application;

[0020] Figure 3 A process diagram of passenger waiting cumulative time cost generation is shown according to an embodiment of the present application;

[0021] Figure 4 A diagram of station-by-period inbound demand is shown according to an embodiment of the present application;

[0022] Figure 5 A diagram of passenger flow pressure distribution before regulation is shown according to an embodiment of the present application;

[0023] Figure 6 A diagram of passenger flow pressure distribution after regulation is shown according to an embodiment of the present application;

[0024] Figure 7 A structure block diagram of a passenger flow collaborative control device of a one-way rail transit line is shown according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] It should be noted that the embodiments and features in the present application can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0026] In order to enable persons skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by persons skilled in the art without creative work should fall within the protection scope of the present application.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] As described in the background section, the existing technology in urban rail transit networks has a poor match between train capacity and station demand, resulting in long-term passenger congestion and delays at some stations. To address this issue, embodiments of this application provide a passenger flow coordination control method, apparatus, computer-readable storage medium, and electronic device for unidirectional rail transit lines.

[0029] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0030] The methods and embodiments provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Taking running on a mobile terminal as an example, Figure 1 This is a hardware structure block diagram of a mobile terminal for a passenger flow coordination control method for a one-way rail transit line according to an embodiment of the present invention. Figure 1 As shown, a mobile terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the mobile terminal described above. For example, the mobile terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0031] The memory 104 can be used to store computer programs, such as software programs of application software and modules, such as the computer program of the passenger flow coordination control method of the one-way rail transit line in the embodiments of the present application. The processor 102 can execute various functional applications and data processing, i.e., implement the above method, by running the computer program stored in the memory 104. The memory 104 can include a high-speed random access memory, and can further include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory 104 can further include memories remotely arranged with respect to the processor 102, which can be connected to the mobile terminal through a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The transmission device 106 is used to receive or send data through a network. The specific examples of the above network can include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet in a wireless manner.

[0032] In the embodiments, a passenger flow coordination control method of a one-way rail transit line running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that herein.

[0033] Figure 2 is a flowchart of the passenger flow coordination control method of the one-way rail transit line according to the embodiments of the present application. As shown in Figure 2 , the method includes the following steps:

[0034] In step S201, train operation parameters of the one-way rail transit line and station information of each station are obtained, wherein the station information includes maximum carrying passenger flow of each area of each station, real-time passenger flow of each area, number of people queuing in a platform waiting area and actual boarding number, the area includes a station queuing area, a station waiting area and the platform waiting area, and the train operation parameters include train capacity, adjacent train arrival time interval and stop duration.

[0035] Specifically, in the implementation process, the number of passengers entering and leaving the station can be displayed and automatically controlled by the entrance and exit gates of the rail station AFC system.

[0036] In step S202, the train running parameters and the station information of each station are used to determine the number of passengers entering the station, the passenger waiting time cost, and the station carrying pressure of each station, and a passenger flow coordination control model of each station is constructed based on the number of passengers entering the station, the passenger waiting time cost, the station carrying pressure, the train running parameters, and the station information of each station. The number of passengers entering the station represents the number of passengers waiting to board the train at the station.

[0037] Specifically, the most direct manifestation of the imbalance between demand and supply during peak hours is the gathering and retention of passengers inside and outside the station, and the increase in passenger waiting time cost resulting therefrom. To represent this time cost, various indicators such as average stay and total delay can be used. Considering the cost of individual passengers as independent units, when the capacity is less than the demand or the station entry is controlled, the individual waiting time of the passengers will be different, and the waiting time cost corresponding to any moment should be the cumulative sum of the waiting time of all different passenger groups at the station at that moment, which is used as the passenger waiting time cost.

[0038] In step S203, the passenger waiting time cost of all stations is the same or the difference in waiting time cost is within a preset time range, and / or the number of passengers entering all stations is the same or the difference in the number of passengers entering is within a preset demand range, and the train carrying capacity of each station is regulated and controlled by using the passenger flow coordination control model of each station.

[0039] Through the above steps S201, S202, and S203, the passenger flow state and the carrying capacity of the train at each station can be accurately mastered by collecting and analyzing the train running parameters and the station information, thereby providing a data basis for subsequent coordinated control. By monitoring the real-time passenger flow in the queue area outside the station, the waiting area inside the station, and the platform waiting area, it can be known in time which areas are close to or exceed the maximum carrying passenger flow, and then appropriate control measures can be taken. In addition, the consideration of parameters such as train capacity, arrival time interval, and stop length helps to evaluate the carrying capacity and running efficiency of the train, and ensures balanced passenger service between different stations. Through the combination of these technical features, the present application solves the passenger flow management problem caused by information asymmetry in traditional rail transit, realizes efficient and accurate control of one-way lines, and improves the passenger travel experience and the overall operation efficiency of the system. Therefore, the problem of poor matching between train capacity and station demand in the existing technology in urban rail transit network is solved, which leads to the gathering and retention of passengers in some stations for a long time.

[0040] In the implementation process, the station entry demand and station carrying pressure of each station are determined according to the station information of each station, including: determining the station entry demand of the station according to the difference between the sum of the real-time passenger flow of the station waiting area and the platform waiting area and the actual boarding number; determining the station carrying pressure of the station according to the ratio of the real-time passenger flow of each area of the station to the maximum carrying passenger flow of each area, wherein the station carrying pressure includes the carrying pressure of the station waiting area, the platform waiting area and the station waiting area.

[0041] The method can accurately calculate the station entry demand, i.e. the number of passengers waiting to board, by comparing the real-time passenger flow of the station waiting area and the platform waiting area with the actual boarding number. At the same time, the carrying pressure of the station can be quantified by the ratio of the real-time passenger flow to the maximum carrying passenger flow, helping decision makers intuitively understand the degree of congestion of the station. This real-time data-based analysis method can quickly respond to changes in passenger flow and avoid safety hazards and passenger dissatisfaction caused by excessive congestion. For example, when the real-time passenger flow of the platform waiting area approaches its maximum carrying passenger flow, the system will automatically adjust the train stopping strategy, increase the train stopping time or adjust the departure interval to relieve the platform pressure. This technical feature of the present application effectively solves the contradiction between the carrying capacity of the station and the actual demand through real-time monitoring and data analysis, improving the safety and passenger satisfaction of the rail transit system. In practical application, the evaluation of station carrying pressure can also combine historical data, prediction models, etc. for more accurate prediction and control, including but not limited to using machine learning algorithms to predict passenger flow trends in future time periods.

[0042] Specifically, the passenger waiting time cost of each station is determined according to the train operation parameters and the station information of each station, including: determining the passenger waiting time cost of each station according to the first formula: , wherein, is the passenger waiting time cost considering only one train interval of the passenger, is the time interval between the arrival of adjacent trains, is the length of the stop, is the sum of the real-time passenger flow of the station waiting area and the platform waiting area, is the actual boarding number.

[0043] The passenger waiting time cost calculated by the first formula reflects the waiting time of the station under the current train operation parameters and is one of the important indicators for measuring passenger experience. For example, if the real-time passenger flow of the station is much larger than the actual boarding number, it means that many passengers need to wait for the next train, which will increase their waiting time cost. By introducing this calculation formula, the invention can quantify the waiting time of passengers and provide a scientific basis for subsequent passenger capacity regulation. By adjusting the passenger capacity of the train, the waiting time of passengers can be effectively shortened, and the service quality can be improved. The realization of this technical feature solves the problem of long waiting time of passengers in traditional rail transit and improves the efficiency and comfort of passengers.

[0044] More specifically, according to the above train operation parameters and the above station information of each of the above stations, the passenger waiting time cost of each of the above stations is determined, including: according to the second formula: , the passenger waiting time cost of each of the above stations is determined, , the above passenger waiting time cost considering multiple train interval stays, is the interval between the arrival times of adjacent trains, is the station stay time, and k represents the kth train interval stay period, is the sum of the real-time passenger flow of the station waiting area and the platform waiting area, is the actual boarding number.

[0045] The second formula of the method takes into account the possibility of passengers staying in multiple train intervals, which is particularly important during peak hours, as passengers may need to wait for multiple trains to board. By calculating the passenger waiting time cost, the system can more comprehensively evaluate the overall waiting time of passengers and make more reasonable train scheduling decisions. For example, when it is detected that the passenger waiting time cost of a certain station is significantly higher than that of other stations, the boarding number of the station can be increased to reduce the waiting time cost of the station. The introduction of this technical feature solves the problem of passenger stay during peak hours and ensures that the efficiency of passenger travel is not significantly affected.

[0046] Further, the train passenger capacity of each of the above stations is regulated by using the passenger flow coordination control model of each of the above stations, including: determining a first deviation factor according to the passenger waiting time cost of the target station and all stations, wherein the target station represents the station to be regulated in terms of train passenger capacity; determining a second deviation factor according to the boarding demand of the target station and all stations; and regulating the train passenger capacity of the target station by the passenger flow coordination control model, with the first deviation factor and the second deviation factor being minimized as the target.

[0047] The method can comprehensively consider the passenger waiting time cost and the difference in the boarding demand by defining the first deviation factor and the second deviation factor, and realize dynamic adjustment of the train passenger carrying capacity. For example, if the boarding demand of a target station is much higher than that of other stations, but the passenger waiting time cost is relatively low, the system may appropriately reduce the train passenger carrying capacity of the station to provide more opportunities for getting on at other stations, so as to balance the overall passenger waiting time cost. The implementation of this technical feature solves the problem of train capacity allocation caused by uneven demand between stations in a one-way line, and improves the operation efficiency and passenger satisfaction of the entire line.

[0048] Further, the first deviation factor is determined according to the passenger waiting time cost of the target station and all stations, including: determining the first deviation factor according to a third formula: , wherein, is the first deviation factor, is the multiple deviation of the passenger waiting time cost of the target station, is the average value of the multiple deviation of the passenger waiting time cost of all stations, is the number of stations, , is the passenger waiting time cost of the target station considering that passengers stay for multiple intervals, is the passenger waiting time cost of the target station considering that passengers stay for only one interval.

[0049] The method can determine whether the waiting time cost of the target station needs to be adjusted by comparing the passenger waiting time cost of the target station with that of other stations, and provide a basis for dynamically adjusting the train passenger carrying capacity. For example, if the passenger waiting time cost of the target station is much higher than that of other stations, it indicates that the operation efficiency of the station is low, and the train stopping time and passenger carrying capacity may need to be increased to reduce the waiting time of passengers. By determining the first deviation factor, the operation efficiency of the target station can be more accurately evaluated, so as to realize dynamic adjustment of the train passenger carrying capacity, effectively balance the passenger waiting time and boarding demand of each station, and improve the overall operation efficiency and passenger experience.

[0050] Specifically, the second deviation factor is determined according to the boarding demand of the target station and all stations, including: determining the second deviation factor according to a fourth formula: , wherein, is the second deviation factor, is the boarding demand of the target station, is the average value of the boarding demand of all stations, is the number of stations.

[0051] The method can determine whether the target station's inbound demand needs to be adjusted by comparing the target station's inbound demand with that of other stations, providing a basis for dynamically adjusting train passenger capacity. For example, if the target station's inbound demand is much larger than that of other stations, it indicates that the station has a large passenger flow pressure, and the train's stopping time and passenger capacity need to be increased to reduce passenger waiting time. By determining the second deviation factor, the passenger flow pressure of the target station can be more accurately assessed, thereby achieving dynamic adjustment of train passenger capacity, effectively balancing passenger waiting time and inbound demand at each station, and improving overall operational efficiency and passenger experience.

[0052] In addition, the present embodiment also includes the introduction of intelligent prediction and dynamic learning models. Specifically, by constructing a machine learning model, historical data is used to learn and predict future passenger flow trends, and at the same time, real-time passenger flow data is combined to dynamically adjust the parameters of the prediction model to adapt to dynamic changes at different times. In this way, not only can possible passenger flow peaks be predicted in advance, but the prediction results can also be corrected in real time according to the latest data feedback, making the control strategy more accurate. Specifically, in addition to predicting the inbound demand, the number of waiting passengers, and the train full load rate at each station based on real-time passenger flow data and historical data, deep learning algorithms such as Long Short-Term Memory (LSTM) or Variational Autoencoder (VAE) can also be introduced to analyze the time series features in historical data and predict future passenger flow. For example, by analyzing the passenger arrival patterns during the morning peak period in the past few weeks, it can be learned that the number of inbound passengers on Mondays and Fridays is often higher than on other days, and is related to factors such as weather and holidays, so that measures can be planned in advance in the control strategy. This method enhances the system's ability to adapt to future uncertainties, shortens response time, and effectively prevents improper allocation of transport capacity due to prediction errors.

[0053] The present embodiment also includes personalized travel recommendations and guidance. Through a mobile app or other digital platform, personalized travel recommendations based on real-time transport capacity and individual preferences are provided to passengers, including but not limited to recommending off-peak travel times, providing alternative route information, and informing estimated waiting times, to disperse passenger flow and reduce pressure on specific stations. Through a communication interface with passenger mobile devices, personalized travel recommendations are pushed, such as when passengers plan to go to a station with severe congestion, the system can send messages to passengers near these stations, suggesting they take the adjacent station or use other transportation, while also providing the most suitable alternative based on the passenger's past travel habits and preferences. In practical applications, the personalized travel recommendations and guidance mechanism helps passengers make informed choices, effectively dispersing passenger flow and reducing the burden on some stations.

[0054] In order for those skilled in the art to more clearly understand the technical solutions of the present application, the implementation process of the passenger flow coordination control method of the one-way rail transit line will be described in detail below in conjunction with specific embodiments.

[0055] The present embodiment relates to a specific passenger flow coordination control method of a one-way rail transit line, which specifically comprises the following steps:

[0056] Step S1: regarding the rail transit single line as a graph structure composed of a plurality of nodes, a line and node space dynamic model is established;

[0057] Step S2: by combining real-time passenger flow data and historical data, the boarding demand, the number of waiting passengers and the train full load rate of each station are predicted, and a cumulative time cost model of each station is established;

[0058] Step S3: based on the actual bearing pressure and cumulative cost of each station, a dynamic allocation algorithm is designed to optimize the passenger flow coordination control between multiple stations.

[0059] Step S4: using the control model to simulate the number of boarding passengers, the dynamic length of the queue, the waiting time cost and other parameters of each station, the control strategy is dynamically adjusted according to the real-time monitoring feedback, and global optimization is realized.

[0060] Taking a simple example: in a line, there are a plurality of stations, among which A5, A6 and A7 in the middle have the following data at the morning peak period: , , If only the number of passengers boarding at each station is considered at this moment, A5 is 60, A6 is 40, and A7 is 30; then most of the people in each batch at each station are left on the platform, and the waiting time of the people outside the station will gradually increase with the time, especially the number of people at A6 station. Taking only these three stations as the control scheme, in order to average the waiting time, the number of passengers boarding at A5 and A6 is controlled, so that the waiting time of passengers at A7 is reduced, of course, in the specific implementation, the number of passengers boarding at A1-A4 should be controlled to average the waiting time of passengers at each station.

[0061] Specifically, in step S1, it includes:

[0062] For each station, it is divided into an outdoor queuing area, an indoor waiting area and a platform waiting area, and the physical capacity and passenger flow dynamic parameters of each area are defined, wherein the one-way rail transit line is selected as the edge of the graph, the station is selected as the point of the graph, and the n station nodes are respectively represented as ;

[0063] ;

[0064] Outside the station, inside the station and the platform queue area are respectively represented by , , It is shown that the corresponding bearing physical upper limit , , Absolute index: ;

[0065] The actual number of passengers in each node in each area is represented by V, and the actual number of passengers in each node in each area is , , Time vector: ;

[0066] In response to the spatial characteristics of the single track, the matrix of each node on the track line is obtained in the form of:

[0067] ;

[0068] Define L as the bearing pressure, Relative index:

[0069] ;

[0070] Each node controls the total number of people entering the station by optimization, which can be displayed by the automatic fare collection system of the rail station and automatically controlled by the automatic fare collection system of the rail station.

[0071] At the same time, the flow from the previous node station to the current node station also needs to be considered:

[0072] The arrival vector of each node at each time point is represented by PDV:

[0073] PDV(k)=[PDV1(k),PDV2(k),...,PDVi(k),...,PDVn(k)]T;

[0074] The control law (dispersion amount) of each node at each time point is represented by PDI:

[0075] PDI (k)=[PDI1(k),PDI2(k),...,PDIi(k),...,PDIn(k)]T;

[0076] The demand for entering the station of each node at each time point is represented by PDL:

[0077] PDL(k)=[PDL1(k),PDL2(k),...,PDLi(k),...,PDLn(k)]T;

[0078] Arrival quantity and demand quantity are time-dependent, and the demand quantity at any time point is actually the cumulative quantity between arrival quantity and control law:

[0079] ;

[0080] T includes the train tracking interval constant TC and the station stop time TS (constant, i.e. theoretically assigned to two door opening and closing and boarding and alighting operation limit time). The passenger waiting time cost vector of each node is represented by PWTC:

[0081] ;

[0082] PWTC is the explicit form of the total time consumption of the system, which is interchangeable with PDL. The former focuses on cost representation, and the latter focuses on safety.

[0083] In step S2: The most direct manifestation of the imbalance between operation and demand during peak hours is the appearance of passenger aggregation and retention inside and outside the station, and the increase in passenger waiting and alighting operation time cost resulting therefrom. To represent this time cost, various indicators such as average stay and total delay can be used, but such indicators are actually repetitive in meaning with the number of people in line. Taking the passenger as an independent unit for cost consideration, when the capacity is less than the demand or the station entry is controlled, the individual waiting time of the passengers who stay and take the train will be different, and the waiting time cost at any time should be the cumulative sum of the waiting time of all different passenger groups in the station at that time;

[0084] Any k time constitutes PDL passenger individuals, some of which are newly arrived and participate in forming the queue, and some of which are still in the queue without taking the train for several cycles. The above passengers are treated differently, and individual waiting time is calculated and accumulated to more accurately express the cost, represented by PWTCC, which is distinguished from PWTC and called the implicit form.

[0085] ;

[0086] ;

[0087] The arrival time outside the station is divided to design the PWTCC cumulative time index to represent the time cost of passengers staying for at least one train interval. Using the "divide and conquer, combine two as one" approach, first, the apparent queue passengers formed at any time point are divided into at least once-staying passengers and newly participating queue passengers, as shown in Figure 3 .

[0088] The waiting cost of the staying passengers is calculated separately and iteratively, and then combined with the waiting cost of the new queue passengers, as shown in Table 1:

[0089] Table 1

[0090]

[0091] PWTCC=0 represents all passengers from entering the station to the cost of a ride to leave a running interval; as PWTCC>0, indicating waiting more than a running interval, the emergence of stay passengers. PWTCC / PWTC>1 indicates the emergence of additional travel time costs, design a parameter CCT represents the multiple deviation of this special time cost:

[0092] .

[0093] In S3 step: for passenger travel, the line train service level is the most direct experience of capacity coordination control effect. Through the control, so that all controlled trains of the specific line connection open at the right level of load factor; as for the station passenger transport organization, control needs to make all passenger waiting time at each station as short as possible. As to how to coordinate the distribution to each station, it is necessary to consider the load state PDL(k) of the passenger queue under the premise that S(C) is not exceeded, and to use PWTCC(k), CCT(k) and other parameters representing deviation as control variables to fully represent the fairness of the allocation of line capacity resources in meeting the passenger demand of each station; due to the different carrying capacities of the three parts of each node station, the cost is not suitable for absolute quantity representation, and in the research, PDL(k), S(C), L(V), and CCT(k) are used to calculate the dynamic cost of each controlled unit, and the load is regarded as the cost borne, and the maximum balance of relative dynamic impedance of all nodes is taken as the target to design the coordinated control equation according to the principle of "cost sharing".

[0094] Under the premise that the total amount of capacity and demand is constant, the goal of coordinated control is equivalent to the minimum dissipation time, and the accumulated waiting time between each node is also minimized to achieve high efficiency and safety. A multi-point coordinated control equation is established, which contains the state variables L(k) of each station node, the demand variables PDL(k) (PDV is converted to PDL to represent the bearing pressure level synchronously), and the control variables PDI(k), as shown in the formula:

[0095] ;

[0096] ;

[0097] ;

[0098] Among them, PDL(k) S(C), and is the impedance balance factor designed: among them the meaning is to represent the deviation of the queue length of a specific station node from the average queue length of each station node in any period is the smallest; The meaning of the cumulative time of the specific station node is the minimum deviation of the average cumulative waiting time of each station node.

[0099] In the S4 step, the control strategy of the line is controlled in advance before the peak period:

[0100] Input data:

[0101] 1) Historical passenger flow data and real-time passenger arrival at each site;

[0102] 2) The capacity and carrying capacity of each station;

[0103] 3) Train operation parameters: car capacity, train interval, and stop time;

[0104] 4) Initialization data: the current queue length of each area at each site;

[0105] Model simulation:

[0106] 1) Calculate the dynamic length of the queue: update the queuing situation at each site according to the above formula,

[0107] 2) Calculate the passenger waiting time cost at each site.

[0108] Dynamic feedback and optimization control: according to the time cost of each site, form a control strategy for the number of passengers at each site.

[0109] Simulation verification and iterative adjustment:

[0110] Simulate the control strategy multiple times, analyze the influence of different control parameters on the system operation effect, and gradually optimize the strategy. In this case, the real-time number of passengers at each station will affect the change of the control strategy.

[0111] The following is an example of a train in a certain area, including A station, B station, C station, D station, E station, F station, G station, and H station. The inbound passenger flow demand of each station is compared during the typical morning peak period in the downlink direction. According to the actual capacity and passenger flow as input, MATLAB+VBA is used for accelerated processing, and the changes of control parameters at each station are compared. The inbound demand data of each station is shown in Figure 4 .

[0112] Compare indicators such as passenger flow carrying pressure PDL(k) of each related station, and compare the changes before and after control Figure 5 , Figure 6The first station priority conforms to common sense in the self-organizing state. When there is no control, the time for matching the transport capacity with the demand will be prolonged, and the fair order of sharing the transport capacity by multiple stations will be destroyed. The pressure of the first station is fully represented, and the remote station can only take measures to limit the flow outside the station. The passive backlog in the data blind area cannot be reflected through the monitoring data, and the pressure cannot be reflected through the monitoring data, as shown in Figure 5 The pressure representation quality is improved after control, as shown in Figure 6 .

[0113] Select one of the stations to develop a matrix form of the section of the peak period in time sequence. The comparison of the monitoring parameters before and after control is shown in Table 2.

[0114] Table 2

[0115]

[0116] The embodiment can effectively reduce the number of queuing passengers and the stagnation situation, ensure dynamic matching of supply and demand, and relieve the contradiction between transport and demand by modeling the station nodes and regions of the one-way line and dynamically adjusting the bearing pressure of each node. Through scientific and reasonable modeling, control strategies and optimization objectives, the embodiment can realize collaborative control of multiple stations and efficient allocation of transport resources, improve passenger experience, safety and fairness, and take into account the economy and operability of the system. These effects directly meet the direction of the development of smart rail transit and provide a new technical path for the collaborative management of complex giant systems.

[0117] The embodiment of the application also provides a passenger flow collaborative control device for a one-way rail transit line. It should be noted that the passenger flow collaborative control device for a one-way rail transit line provided in the embodiment of the application can be used to execute the passenger flow collaborative control method for a one-way rail transit line provided in the embodiment of the application. The device is used to realize the above-mentioned embodiments and preferred embodiments, and will not be described again. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware or a combination of software and hardware is also possible and is contemplated.

[0118] The passenger flow collaborative control device for a one-way rail transit line provided in the embodiment of the application is described below.

[0119] Figure 7 is a schematic diagram of the passenger flow collaborative control device for a one-way rail transit line according to the embodiment of the application. As shown in Figure 7 , the device includes:

[0120] The acquisition unit 71 is configured to acquire train operation parameters of a one-way rail transit line and station information of each station, wherein the station information includes maximum carrying passenger flow of each region of each station, real-time passenger flow of each region, queuing number of a platform waiting area, and actual boarding number, the regions include an off-station queuing area, an in-station waiting area, and the platform waiting area, and the train operation parameters include train capacity, adjacent train arrival time interval, and stop duration;

[0121] The determination unit 72 is configured to determine, according to the train operation parameters and the station information of each station, an arrival demand of each station, a passenger waiting time cost, and a station carrying pressure, and to construct a passenger flow coordination control model of each station based on the arrival demand, the passenger waiting time cost, the station carrying pressure, the train operation parameters, and the station information of each station, wherein the arrival demand represents a number of passengers to be boarded at the station.

[0122] The regulation and control unit 73 is configured to regulate and control train carrying capacity of each station by using the passenger flow coordination control model of each station, with the same passenger waiting time cost or a time cost difference within a preset time range of all stations, and / or the same arrival demand or a demand difference within a preset demand range of all stations, as a target.

[0123] In this embodiment, the acquisition unit is configured to acquire train operation parameters of a one-way rail transit line and station information of each station, wherein the station information comprises maximum carrying passenger flow of each area of each station, real-time passenger flow of each area, queue number of a platform waiting area, and actual boarding number, the areas include an off-site queue area, an on-site waiting area, and the platform waiting area, and the train operation parameters include train capacity, adjacent train arrival time interval, and stop duration; the determination unit is configured to determine, according to the train operation parameters and the station information of each station, boarding demand of each station, passenger waiting time cost, and station carrying pressure, and construct a passenger flow coordination control model of each station based on the boarding demand of each station, the passenger waiting time cost, the station carrying pressure, the train operation parameters, and the station information, wherein the boarding demand represents the number of passengers to be boarded at the station; and the regulation and control unit is configured to regulate and control train carrying capacity of each station by using the passenger flow coordination control model of each station, with the same passenger waiting time cost or a difference in the passenger waiting time cost within a preset time range of all stations, and / or the same boarding demand or a difference in the boarding demand within a preset demand range of all stations. Through collection and analysis of the train operation parameters and the station information, the passenger flow state and the carrying capacity of each station can be accurately mastered, thereby providing a data basis for subsequent coordination control. Through monitoring of the real-time passenger flow of the off-site queue area, the on-site waiting area, and the platform waiting area, it can be known in a timely manner which areas are close to or exceed the maximum carrying passenger flow, and then corresponding regulation and control measures can be taken. In addition, consideration of parameters such as the train capacity, the arrival time interval, and the stop duration helps to evaluate the carrying capacity and operation efficiency of the train, and ensures balanced passenger service between different stations. Through the combination of these technical features, the application solves the passenger flow management problem caused by information asymmetry in traditional rail transit, realizes efficient and accurate control of the one-way line, and improves the passenger travel experience and the overall operation efficiency of the system. Therefore, the problem of poor matching between train carrying capacity and station demand in the existing technology in the urban rail transit network, which leads to long-term gathering and retention of passengers at some stations, is solved.

[0124] As an optional solution, the determination unit comprises a first determination module and a second determination module; the first determination module is configured to determine the boarding demand of the station according to a difference between a sum of the real-time passenger flow of the on-site waiting area and the platform waiting area and the actual boarding number; and the second determination module is configured to determine the station carrying pressure of the station according to a ratio of the real-time passenger flow of each area of the station to the maximum carrying passenger flow of each area, wherein the station carrying pressure comprises carrying pressures of the off-site queue area, the on-site waiting area, and the platform waiting area.

[0125] As an optional solution, the determination unit further comprises a third determination module configured to determine the boarding demand of the station according to a first formula: determining a passenger waiting time cost of each of the stations, wherein, the passenger waiting time cost of the target station considering that the passenger exists multiple train interval stays, the time interval of the adjacent trains arriving at the station, the stop duration, the sum of the real-time passenger flow of the waiting area in the station and the platform waiting area, the actual number of passengers boarding the train.

[0126] In an optional solution, the determining unit further includes a fourth determining module configured to determine the passenger waiting time cost of each of the stations according to a second formula: determining a passenger waiting time cost of each of the stations, wherein, the passenger waiting time cost of the target station considering that the passenger exists multiple train interval stays, the time interval of the adjacent trains arriving at the station, the stop duration, k represents a kth train interval stay period, the sum of the real-time passenger flow of the waiting area in the station and the platform waiting area, the actual number of passengers boarding the train.

[0127] In an optional solution, the regulating unit includes a fifth determining module, a sixth determining module and a regulating module. The fifth determining module is configured to determine a first deviation factor according to the passenger waiting time cost of the target station and all the stations, wherein the target station represents a station to be regulated in the train carrying capacity. The sixth determining module is configured to determine a second deviation factor according to the boarding demand of the target station and all the stations. The regulating module is configured to regulate the train carrying capacity of the target station through the passenger flow coordination control model, with the first deviation factor and the second deviation factor being minimized as the target.

[0128] In an optional solution, the fifth determining module includes a first determining submodule configured to determine the first deviation factor according to a third formula: determining a passenger waiting time cost of each of the stations, wherein, the first deviation factor, a multiple deviation of the passenger waiting time cost of the target station, an average value of the multiple deviations of the passenger waiting time cost of all the stations, the number of the stations, , the passenger waiting time cost of the target station considering that the passenger exists multiple train interval stays, the passenger waiting time cost of the target station considering that the passenger exists multiple train interval stays.

[0129] An alternative solution, the fifth determining module comprises a second determining sub-module, configured to determine the second deviation factor according to a fourth formula: , wherein, is the second deviation factor, is the inbound demand of the target station, is the average value of the inbound demand of all stations, is the number of stations.

[0130] The passenger flow coordination control device of the one-way rail transit line comprises a processor and a memory, the acquisition unit, the determining unit and the regulation and control unit are all stored in the memory as program units, and the corresponding functions are realized by the processor executing the program units stored in the memory. The modules are all located in the same processor, or the modules are respectively located in different processors in any combination.

[0131] The processor comprises a core, and the core calls the corresponding program units in the memory. The core can be one or more, and the matching degree of train capacity and station demand in the existing technology in the urban rail transit network is poor, which causes passengers to gather and stay for a long time in some stations by adjusting the core parameters.

[0132] The memory can comprise a non-permanent memory in a computer readable medium, a random access memory (RAM) and / or a non-volatile memory such as a read-only memory (ROM) or a flash memory (flash RAM), and the memory comprises at least one memory chip.

[0133] The embodiment of the present application provides a computer readable storage medium, the computer readable storage medium comprises a stored program, wherein the computer readable storage medium controls the device to execute the passenger flow coordination control method of the one-way rail transit line when the program runs.

[0134] The embodiment of the present application provides a processor, the processor is used for running a program, wherein the processor executes the passenger flow coordination control method of the one-way rail transit line when the program runs.

[0135] The embodiment of the present application provides an electronic device, the device comprises a processor, a memory and a program stored in the memory and capable of running on the processor, and the processor executes the steps of the passenger flow coordination control method of the one-way rail transit line when the program runs.

[0136] The device in the present application can be a server, a PC, a PAD, a mobile phone and the like.

[0137] The application also provides a computer program product, which is suitable for executing the program of the passenger flow coordination control method of the at least one-way rail transit line when executed on a data processing device.

[0138] It is apparent that those skilled in the art should understand that the modules or steps of the application described above can be realized by general computing devices, which can be centralized on a single computing device or distributed on a network composed of multiple computing devices, and can be realized by program codes executable by the computing devices, so that they can be stored in storage devices and executed by the computing devices, and in some cases, the steps shown or described can be executed in different orders, or they can be respectively manufactured into individual integrated circuit modules, or multiple modules or steps among them can be manufactured into a single integrated circuit module. Thus, the application is not limited to any specific combination of hardware and software.

[0139] Those skilled in the art should understand that the embodiments of the application can be provided as a method, a system, or a computer program product. Therefore, the application can adopt a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the application can adopt a computer program product implemented on one or more computer usable storage media containing computer usable program codes (including but not limited to disk storage, CD-ROM, optical storage, etc.).

[0140] The application is described with reference to flowcharts and / or block diagrams according to the methods, devices (systems), and computer program products of the embodiments of the application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be realized by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one or more flows and / or blocks. Figure 1 The functions specified in one or more flows and / or blocks.

[0141] These computer program instructions can also be stored in a computer readable storage medium, which can guide the computer or other programmable data processing devices to work in a specific way, so that the instructions stored in the computer readable storage medium produce a manufactured product including instruction devices, which implement the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one or more flows and / or blocks. Figure 1 The functions specified in one or more flows and / or blocks.

[0142] These computer program instructions can also be loaded into a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 Figure 1 Figure 1

[0143] In one typical configuration, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0144] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) about which the processor can execute instructions. The memory can also include non-volatile memory, such as read only memory (ROM), electrically programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), flash memory, or other memory technologies, about which the processor can execute instructions. The memory is an example of computer readable media.

[0145] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically programmable read only memory (EEPROM), flash memory or other memory technologies, compact disc read only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to computing devices. According to the definition herein, computer readable media does not include transitory media, such as modulated data signals and carrier waves.

[0146] It should also be noted that the terms "comprising," "including," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements recited, but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without limitation, an element preceded by "comprises a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0147] ​​The above descriptions are only the preferred embodiments of the present application, and are not intended to limit the present application. The present application can have various modifications and changes for those skilled in the art. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A passenger flow coordination control method for a one-way rail transit line, characterized in that, The method comprises: obtaining train operation parameters of a one-way rail transit line and station information of each station, wherein the station information comprises maximum carrying passenger flow of each area of each station, real-time passenger flow of each area, queue number of a platform waiting area and actual boarding number, the area comprises an outdoor queuing area, an indoor waiting area and the platform waiting area, and the train operation parameters comprise train capacity, adjacent train arrival time interval and stop duration; determining in-station demand, passenger waiting time cost and station carrying pressure of each station according to the train operation parameters and the station information of each station, and constructing a passenger flow coordination control model of each station based on the in-station demand, the passenger waiting time cost, the station carrying pressure, the train operation parameters and the station information of each station, wherein the in-station demand represents the number of passengers to be boarded at the station; controlling train carrying capacity of each station by using the passenger flow coordination control model of each station, with the same passenger waiting time cost or a difference in passenger waiting time cost within a preset time range of all stations, and / or the same in-station demand or a difference in in-station demand within a preset demand range of all stations as the target; determining passenger waiting time cost of each station according to the train operation parameters and the station information of each station, comprising: According to a first formula: , a passenger waiting time cost of each station is determined, wherein, is the passenger waiting time cost considering only one train interval stay of the passenger, is a time interval of arrival of adjacent trains, is a stop duration, and k represents a kth train interval stay period, is a sum of real-time passenger flow of the waiting area in the station and the platform waiting area, is the actual number of passengers boarding. According to the second formula: , the passenger waiting time cost of each station is determined, the passenger waiting time cost considering that the passenger stays for multiple train intervals, the interval of the arrival time of the adjacent trains, the stop duration, k represents the kth train interval stay period, the sum of the real-time passenger flow of the waiting area in the station and the platform waiting area, the actual number of passengers boarding.

2. The method of claim 1, wherein, determining in-station demand and station carrying pressure of each station according to the station information of each station, comprising: determining the in-station demand of the station according to a difference between a sum of real-time passenger flows of the indoor waiting area and the platform waiting area and the actual boarding number; determining the station carrying pressure of the station according to a ratio of real-time passenger flow of each area to maximum carrying passenger flow of each area, wherein the station carrying pressure comprises carrying pressure of the outdoor queuing area, the indoor waiting area and the platform waiting area.

3. The method of claim 1, wherein, controlling train carrying capacity of each station by using the passenger flow coordination control model of each station, comprising: determining a first deviation factor according to passenger waiting time cost of a target station and all stations, wherein the target station represents a station to be controlled in train carrying capacity; determining a second deviation factor according to in-station demand of the target station and all stations; controlling the train carrying capacity of the target station by the passenger flow coordination control model, with the first deviation factor and the second deviation factor being the minimum as the target.

4. The method of claim 3, wherein, determining a first deviation factor according to passenger waiting time cost of a target station and all stations, comprising: According to a third formula: , determining the first bias factor, wherein, is the first bias factor, is a multiple bias of a passenger waiting time cost of the target station, is an average of the multiple bias of the passenger waiting time cost of all stations, is the number of stations, , is the passenger waiting time cost of the target station considering that a passenger stays for multiple train intervals, is the passenger waiting time cost of the target station considering that a passenger stays for only one train interval.

5. The method of claim 3, wherein, determining a second deviation factor according to in-station demand of the target station and all stations, comprising: According to a fourth formula: , determining the second bias factor, wherein, is the second bias factor, is the inbound demand of the target station, is the average of the inbound demand of all stations, is the number of stations.

6. A passenger flow coordination control device for a one-way rail transit line, characterized in that, The method comprises: An acquisition unit is configured to acquire train operation parameters of a one-way rail transit line and station information of each station, wherein the station information includes maximum carrying passenger flow of each area of each station, real-time passenger flow of each area, queuing number of a platform waiting area, and actual boarding number, the areas include an off-station queuing area, an in-station waiting area, and the platform waiting area, and the train operation parameters include train capacity, adjacent train arrival time interval, and stop duration; A determination unit is configured to determine, according to the train operation parameters and the station information of each station, an inbound demand amount, a passenger waiting time cost, and a station carrying pressure of each station, and to construct a passenger flow coordination control model of each station based on the inbound demand amount, the passenger waiting time cost, the station carrying pressure, the train operation parameters, and the station information of each station, wherein the inbound demand amount represents a number of passengers to be boarded at the station. A regulation and control unit is configured to regulate and control train carrying capacity of each station by using the passenger flow coordination control model of each station, with the same passenger waiting time cost or a preset time range of a waiting time cost difference of all stations, and / or the same inbound demand amount or a preset demand range of an inbound demand amount difference of all stations. The determining unit comprises a third determining module and a fourth determining module, the third determining module is configured to determine the passenger waiting time cost of each station according to a first formula: , wherein, is the passenger waiting time cost considering only one interval of the passenger, is the interval of the arrival time of the adjacent trains, is the stop duration, is the sum of the real-time passenger flow of the waiting area in the station and the platform waiting area, is the actual number of passengers boarding. The fourth determining module is configured to determine the passenger waiting time cost of each station according to a second formula: , wherein, is the passenger waiting time cost considering that the passenger stays for multiple intervals, is the interval of the arrival time of the adjacent trains, is the stop time, k represents the kth interval stay period, is the sum of the real-time passenger flow of the waiting area in the station and the platform waiting area, is the actual number of passengers boarding.

7. A computer readable storage medium characterized in that, The computer readable storage medium includes a stored program, wherein the program controls a device where the computer readable storage medium is located to perform the passenger flow coordination control method of the one-way rail transit line according to any one of claims 1 to 5 when the program is executed.

8. An electronic device, comprising: It includes: One or more processors, memories, and one or more programs, wherein the one or more programs are stored in the memories and configured to be executed by the one or more processors, and the one or more programs include a program for performing the passenger flow coordination control method of the one-way rail transit line according to any one of claims 1 to 5.

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