Rail transit real-time evaluation system and method

Abstract

Embodiments of the present disclosure provide a rail transit real-time evaluation system, which adopts a hierarchical architecture and includes an integrated external system, a core service layer, a background application layer and a front-end interface layer; the background application layer includes a message engine unit, a data service unit, a rule engine unit and an integrated interface; the integrated interface interacts with the interface of the integrated external system, the rule engine unit unifies the information flow inside the system, the data service unit is used for recording the data, logs and alarm information of the evaluation system, and the message engine unit is used for implementing the internal communication of the evaluation system; the core service layer is used for managing data; the background application layer is used for integrating the running state information and quantitatively evaluating the current operation status of the rail transit based on different angles and dimensions by using a calculation evaluation index mode; and the front-end interface layer is used for interaction with users, user input and viewing of index data of a corresponding operation scheme. Corresponding methods, electronic devices and computer storage media are also disclosed.

Description

Technical Field

[0001] This disclosure relates to the field of rail transit and urban rail transit operation evaluation technology, and in particular to a real-time evaluation system and method for rail transit. Background Technology

[0002] Currently, the evaluation of the quality of rail transit organization and operation is based on personal experience, which lacks scientific and strong support for improving the operation organization. In the event of emergencies or operational failures, the actual effect of adjusting and intervening in the operation based on the personal experience of dispatchers also lacks a real-time analysis method.

[0003] In summary, the shortcomings of an operational and organizational approach based on personal experience are mainly reflected in the following aspects:

[0004] 1) There is a lack of clear criteria for judging the quality of an operational organization. A perfect operational organization is often difficult to replicate, leading to a deviation from actual needs.

[0005] 2) Lack of preparation for emergencies: After an emergency occurs, the operational plan organized by the dispatcher based on personal experience does not perfectly match the situation on site, and subsequent adjustments lack scientific basis.

[0006] 3) Insufficient impact analysis of sudden failures, failing to determine the impact of line failures on operations, such as the scope of the failure point and the duration of the impact, relying entirely on the experience of dispatchers;

[0007] 4) Emergency response lacks scientific basis. Under emergency conditions, dispatchers need to make decisions in a short period of time, often relying on experience to formulate plans and judge the merits of different plans.

[0008] 5) The method of manual evaluation and trial operation is used to roughly assess the differences between the operation plans and evaluate the actual application effect of the plan through trial operation. However, the current and future data are not used to build models and simulate the system operation, which cannot support the optimization of the plan. Summary of the Invention

[0009] This disclosure addresses the above-mentioned problems by providing a real-time evaluation system and method for rail transit. By constructing a real-time evaluation system for rail transit, it collects operational status information from the real world in real time, providing a scientific assessment of the current operational organization and offering scientific support for subsequent operational organization. When a fault occurs, based on real-time on-site operational data of the rail transit system, it provides quantitative analysis in the form of indicators for the operational organization method (which can be an operational organization plan in operation, an operational organization plan under emergency conditions, or a manually formulated operational organization plan) and the actual needs on site. The system inputs a reorganized operational plan and quickly calculates the future (30 minutes, 1 hour, or longer) line operational status under different organization plans. Based on the deduced line status, it calculates relevant indicator data for each plan, providing a basis for subsequent decision-making and ultimately for selecting the optimal plan.

[0010] According to a first aspect of this disclosure, a real-time evaluation system for rail transit is provided, employing a layered architecture, including:

[0011] Integrate external systems, specifically third-party systems, to provide multi-dimensional operational status information for the rail transit system;

[0012] The core service layer includes a message engine unit, a data service unit, a rule engine unit, and an integration interface. The integration interface interacts with the interfaces of the external systems being integrated. The rule engine unit unifies the information flow within the system. The data service unit records the data, logs, and alarm information of the evaluation system. The message engine unit implements the internal communication of the evaluation system. The core service layer manages status data, basic data, and passenger flow data.

[0013] The backend application layer is used to integrate the operational status information and quantitatively evaluate the current operational status of the rail transit based on different angles and dimensions using calculated evaluation indicators. This quantitative evaluation of the current operational status of the rail transit includes managing operational plans, constructing scenarios, performing train operation analysis, passenger flow analysis, and calculating indicators for the operational plans, and evaluating the operational plans from the perspectives of passenger flow, operation, and energy consumption.

[0014] The front-end interface layer, or UI layer, is used to enable interaction with users, allowing them to input and view relevant operational data metrics.

[0015] In addition to the aspects and any possible implementations described above, a further implementation is provided, wherein the evaluation indicators include passenger flow indicators, operational efficiency indicators, driving indicators, and energy consumption indicators.

[0016] In addition to the aspects and any possible implementations described above, a further implementation is provided that evaluates the operation plan based on passenger flow, operational, and energy consumption perspectives, including:

[0017] Evaluate the passenger flow of the network, including: analyzing the spatial and temporal distribution of passenger flow, and evaluating the operation plan from the perspective of passenger flow;

[0018] The evaluation of network operation includes: analyzing the network's operation status and assessing the rationality of the operation organization in conjunction with the evaluation of network passenger flow;

[0019] The assessment of fault event mitigation includes: rapidly analyzing the impact of the latest organized operational plan on the operation of the entire line in the event of a sudden fault, providing support for the selection or further optimization of the operational plan; and

[0020] The operation plan is simulated and calculated, including: proposing new operation plans in response to sudden line failures or human intervention; and quickly deriving and evaluating the operation organization, passenger flow, traffic flow impact, and energy consumption analysis of the new operation plan for the entire line.

[0021] According to a second aspect of this disclosure, a real-time evaluation method for rail transit is provided, comprising:

[0022] S1, determine whether the rail transit is in a normal or abnormal scenario;

[0023] S2, based on the judgment that the scenario is normal, implements the real-time evaluation process for rail transit in normal scenarios, including:

[0024] S21, reads real-time basic information data of the line from the core service layer;

[0025] S22, establish multiple computing models and start the corresponding computing model based on the real-time basic information data;

[0026] S23 showcases the day's operational organization plan and its actual implementation;

[0027] S24, Based on the aforementioned computational model, the backend application layer predicts the operational status of the rail transit lines;

[0028] S25, Based on the comparison results between the predicted rail transit line operation status and the actual rail transit line operation status received from the site, optimize the multiple calculation models;

[0029] S3, based on the judgment that an abnormal scenario is in place, implements a real-time evaluation process for rail transit in abnormal scenarios, including:

[0030] S31, the background application layer evaluates the impact of sudden line failures or emergencies on the line operation status of the rail transit; the external system automatically generates several new operation plans based on the nature of the sudden line failures or emergencies and their impact on the line operation status of the rail transit.

[0031] S32, the external system automatically deduces the operation plan based on the predicted rail transit line operation status and the impact on the rail transit line operation status;

[0032] S33, run the simulation operation plan and calculate the evaluation indicators of the simulation operation plan based on the on-site operation of the simulation operation plan;

[0033] S34, the evaluation indicators of each new operation plan are fed back to the front-end interface layer for display, so that the dispatchers can quantitatively evaluate the merits of each new operation plan.

[0034] In addition to the aspects and any possible implementations described above, a further implementation is provided, wherein the plurality of operational models in S22 include:

[0035] Driving analysis model, energy consumption analysis model, and passenger flow and vehicle flow coupling model.

[0036] In addition to the aspects and any possible implementations described above, a further implementation is provided in which S23, demonstrating the day's operational organization plan and actual execution, includes:

[0037] The real-time evaluation system obtains the daily operational plan from external systems and displays the daily operational plan on the front-end interface layer.

[0038] During the day's operation, the real-time evaluation system obtains data from the rail transit operation site or forwards the actual operation status of the day from external systems, and displays it on the front-end interface in the form of actual operation diagrams and evaluation indicators.

[0039] In addition to the aspects and any possible implementations described above, an implementation is further provided in which S24 includes:

[0040] During the implementation of the day's operational plan, the real-time evaluation system quickly calculates the on-site operational status within a certain range of future events based on on-site driving and status data.

[0041] If an abnormal event affecting operations is predicted to occur within the first threshold time range in the future, it should be promptly reported to the front-end interface layer for display.

[0042] Evaluation indicators are determined for the current operating organization based on the results of the calculations and predictions.

[0043] As described above and in any possible implementation, a further implementation is provided, wherein S32 includes:

[0044] The external system will send the new operating plan and a description of any sudden line failures or incidents to the real-time evaluation system.

[0045] The real-time evaluation system quickly extrapolates the traffic and passenger flow situation under the influence of the new operational plan, based on the on-site conditions at the corresponding moment and the new operational plan.

[0046] According to a third aspect of this disclosure, a train is provided, including the real-time evaluation system for rail transit operation described in the first aspect.

[0047] According to a fourth aspect of this disclosure, an electronic device is provided, including a processor and a memory, the memory storing a plurality of instructions, the processor being configured to read the instructions and execute the method as described in the second aspect.

[0048] According to a fifth aspect of this disclosure, a computer-readable storage medium is provided that stores a plurality of instructions which can be read by a processor and executed as described in the second aspect.

[0049] The beneficial effects of this invention are:

[0050] The real-time evaluation system, method, electronic equipment, and computer-readable storage medium for rail transit have achieved the following beneficial effects:

[0051] (1) By constructing a real-time evaluation system for rail transit, the system collects operational status information from the actual rail operation process in real time, provides a scientific assessment of the current operation organization, and provides scientific support for subsequent operation organization.

[0052] (2) Based on multiple computational models, the implementation and prediction of the operation organization scheme under normal rail transit scenarios are carried out, making the implementation of the operation organization scheme more reasonable. The computational model has self-optimization characteristics and is suitable for the ever-evolving rail transit operation scenarios.

[0053] (3) Integrate evaluation indicators into the implementation process of the operation organization plan under normal operation scenarios to provide a basis for prediction;

[0054] (4) When a fault occurs, based on real-time on-site operation data of rail transit, quantitative analysis is given in the form of indicators for the operation organization mode (which can be the operation organization plan in the process of operation, the operation organization plan in emergency situation, or the operation organization plan formulated manually) and the actual needs on site. The input of the reorganized operation plan is used to quickly calculate the future (30 minutes, 1 hour or more later) line operation status under different organization plans. Based on the deduced line status, the relevant indicator data of each plan are calculated to provide a basis for subsequent decision-making and thus for the selection of the best plan.

[0055] It should be understood that the description in the Summary of the Invention is not intended to limit the key or essential features of the embodiments of this disclosure, nor is it intended to restrict the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0056] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. The drawings are provided for a better understanding of the invention and are not intended to limit the scope of this disclosure. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:

[0057] Figure 1 A diagram illustrating the architecture of a real-time evaluation system for rail transit according to an embodiment of the present disclosure is shown.

[0058] Figure 2 A passenger flow index system for a real-time evaluation system of rail transit according to an embodiment of the present disclosure is shown;

[0059] Figure 3 A flowchart of a real-time evaluation method for rail transit according to an embodiment of the present disclosure is shown;

[0060] Figure 4 A schematic diagram of an electronic device structure according to an embodiment of the present disclosure is shown. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0062] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0063] Example 1

[0064] like Figure 1 As shown, a real-time evaluation system for rail transit adopts a layered architecture, including:

[0065] Integrate external systems, specifically third-party systems, to provide multi-dimensional operational status information for the rail transit system;

[0066] The core service layer includes a message engine unit, a data service unit, a rule engine unit, and an integration interface. The integration interface interacts with the interfaces of the external systems being integrated. The rule engine unit unifies the information flow within the system. The data service unit records the data, logs, and alarm information of the evaluation system. The message engine unit implements the internal communication of the evaluation system. The core service layer manages status data, basic data, and passenger flow data.

[0067] The backend application layer is used to integrate the operational status information and quantitatively evaluate the current operational status of the rail transit based on different angles and dimensions using calculated evaluation indicators. This quantitative evaluation of the current operational status of the rail transit includes managing operational plans, constructing scenarios, performing train operation analysis, passenger flow analysis, and calculating indicators for the operational plans, and evaluating the operational plans from the perspectives of passenger flow, operation, and energy consumption.

[0068] The front-end interface layer, or UI layer, is used to enable interaction with users, allowing them to input and view relevant operational data metrics.

[0069] In addition to the aspects and any possible implementations described above, a further implementation is provided, wherein the evaluation indicators include passenger flow indicators, operational efficiency indicators, driving indicators, and energy consumption indicators.

[0070] Given that rail transit directly serves passengers, passenger-related indicators occupy a core position in the entire system. Here, we will take the passenger indicator system as an example to explain the system indicators.

[0071] The system's operating scenarios are divided into normal scenarios and abnormal scenarios. Evaluation of normal scenarios is a real-time assessment, while evaluation of abnormal scenarios is an offline assessment. Therefore, metrics can also be divided into real-time metrics and offline metrics. For example... Figure 2As shown, real-time indicators include: passenger flow entering the station, passenger flow exiting the station, transfer passenger flow, OD passenger flow, passenger flow entering and exiting the line, passenger flow passing through the line, passenger distribution for waiting time, passenger distribution for waiting number of trips, number of passengers waiting, passenger distribution for missed trains, passenger volume, instantaneous passenger flow, transport capacity, passenger flow, section load factor, and train load factor; offline indicators include section imbalance coefficient, passenger distribution for number of transfers, average number of transfers, passenger distribution for travel distance, average travel distance, passenger turnover, load intensity, passenger distribution for number of stations, average number of stations, passenger distribution for travel time, average travel time, passenger distribution for travel time, average travel time, passenger flow entering the station, passenger flow exiting the station, station imbalance coefficient, transfer passenger flow, passenger volume, OD passenger flow, passenger flow entering and exiting the line, passenger intensity, distribution volume, transfer coefficient, and transfer ratio.

[0072] Meanwhile, the indicator system is divided into two levels. The secondary indicators are a further subdivision of the primary indicators. For example, the secondary indicators included in the primary indicator of passenger flow include: passenger flow entering the station by line, passenger flow entering the line, passenger flow entering the network, and passenger flow entering the physical station.

[0073] See Figure 2 In this embodiment, the primary and secondary indicators in the real-time metrics include:

[0074] (1) Passenger flow entering the station: Passenger flow entering the station by line, passenger flow entering the station by line, passenger flow entering the station by the network, and passenger flow entering the physical station;

[0075] (2) Exit passenger flow: Exit passenger flow of stations by line, exit passenger flow of lines, exit passenger flow of the entire network and exit volume of physical stations;

[0076] (3) Transfer passenger flow: Transfer passenger flow by direction at transfer stations, transfer passenger flow at physical transfer stations, transfer passenger flow by line and transfer passenger flow by road network;

[0077] (4) OD passenger flow: Road network OD passenger flow;

[0078] (5) Passenger flow in and out of the line: Passenger flow in and out of the line itself, passenger flow in and out of the line from other lines, and passenger flow in and out of the line from other lines.

[0079] (6) Passenger traffic along the route: Passenger traffic passing through this route;

[0080] (7) Distribution of people waiting for the train: Distribution of people waiting for the train on the platform;

[0081] (8) Distribution of waiting passengers by number of trains: Distribution of waiting passengers by number of trains at physical stations;

[0082] (9) Number of people waiting for the train: The number of people waiting at the physical station;

[0083] (10) Distribution of people who missed their trains: Distribution of people who missed their trains by the number of people stranded on the platform and distribution of people who missed their trains by the number of people stranded at the physical station;

[0084] (11) Passenger volume: Line passenger volume, road network passenger volume and physical station passenger volume;

[0085] (12) Instantaneous passenger flow: Instantaneous passenger flow of the road network;

[0086] (13) Capacity: Regional capacity;

[0087] (14) Passenger flow: Passenger flow within a certain area;

[0088] (15) Section occupancy rate: None;

[0089] (16) Train load factor: number of passengers on board the train, train load factor, maximum train load factor and average train load factor.

[0090] In addition to the aspects and any possible implementations described above, another implementation is provided in which the primary and secondary indicators in the offline metrics include:

[0091] (1) Inter-regional imbalance coefficient: Inter-regional passenger flow, inter-regional imbalance coefficient, directional imbalance coefficient and time imbalance coefficient;

[0092] (2) Number of passengers transferring: Number of passengers transferring by line and number of passengers transferring across the road network;

[0093] (3) Average number of transfers: average number of transfers per line and average number of transfers per road network;

[0094] (4) Passenger distribution by distance: Passenger distribution by distance along the line and passenger distribution by distance across the road network;

[0095] (5) Average travel distance: Line average travel distance and network average travel distance;

[0096] (6) Passenger turnover: Line passenger turnover and road network passenger turnover;

[0097] (7) Load intensity: line load intensity and network load intensity;

[0098] (8) Distribution of passenger numbers at stations: Distribution of passenger numbers at stations along a line and distribution of passenger numbers at stations across the road network;

[0099] (9) Average number of stops: Average number of stops per line and average number of stops per network;

[0100] (10) Passenger distribution during travel time: Passenger distribution during travel time on the route and passenger distribution during travel time across the road network;

[0101] (11) Average travel time: average travel time of the route and average travel time of the road network;

[0102] (12) Distribution of people traveling during travel time: Distribution of people traveling during travel time on the road network;

[0103] (13) Average travel time: Average travel time of the road network;

[0104] (14) Passenger flow entering the station: passenger flow entering the physical station, passenger flow entering the line, and passenger flow entering the road network;

[0105] (15) Exit passenger flow: Exit passenger flow of physical stations, exit passenger flow of lines and exit passenger flow of the road network;

[0106] (16) Station imbalance coefficient: Physical station entry and exit imbalance coefficient;

[0107] (17) Passenger flow: Passenger flow exiting physical stations, passenger flow exiting line stations, and passenger flow exiting the road network;

[0108] (18) Passenger volume: Line passenger volume and network passenger volume;

[0109] (19) OD passenger flow: Road network OD passenger flow;

[0110] (20) Passenger flow in and out of the line: Passenger flow in and out of the line from other lines and passenger flow in and out of other lines from the line.

[0111] (21) Passenger traffic intensity: Line passenger traffic intensity and network passenger traffic intensity;

[0112] (22) Distribution volume: Distribution volume of physical stations;

[0113] (23) Transfer coefficient: Line transfer coefficient and road network transfer coefficient;

[0114] (24) Transfer ratio: Line transfer ratio and network transfer ratio.

[0115] In addition to the aspects and any possible implementations described above, a further implementation is provided in which the calculation of the passenger flow index includes two categories: one is calculation using statistical methods, and the other is simple calculation based on other indicators. The calculated passenger flow index includes:

[0116] Sectional transport capacity = capacity * number of trains passing through the section within a certain time period;

[0117] Section passenger flow = the sum of the number of passengers on all trains passing through the section within a certain period of time;

[0118] Section occupancy rate = Section passenger flow / Section capacity;

[0119] The calculation methods for the remaining indicators are similar to those for the three indicators mentioned above, and will not be repeated here.

[0120] In addition to the aspects and any possible implementations described above, a further implementation is provided that evaluates the operation plan based on passenger flow, operational, and energy consumption perspectives, including:

[0121] Evaluate the passenger flow of the network, including: analyzing the spatial and temporal distribution of passenger flow, and evaluating the operation plan from the perspective of passenger flow;

[0122] The evaluation of network operation includes: analyzing the network's operation status and assessing the rationality of the operation organization in conjunction with the evaluation of network passenger flow;

[0123] The assessment of fault event mitigation includes: rapidly analyzing the impact of the latest organized operational plan on the operation of the entire line in the event of a sudden fault, providing support for the selection or further optimization of the operational plan; and

[0124] The operation plan is simulated and calculated, including: proposing new operation plans in response to sudden line failures or human intervention; and quickly deriving and evaluating the operation organization, passenger flow, traffic flow impact, and energy consumption analysis of the new operation plan for the entire line.

[0125] Example 2

[0126] See Figure 3 This paper provides a real-time evaluation method for rail transit, including:

[0127] S1, determine whether the rail transit is in a normal or abnormal scenario;

[0128] S2, based on the judgment that the scenario is normal, implements the real-time evaluation process for rail transit in normal scenarios, including:

[0129] S21, reads real-time basic information data of the line from the core service layer;

[0130] S22, establish multiple computing models and start the corresponding computing model based on the real-time basic information data;

[0131] S23 showcases the day's operational organization plan and its actual implementation;

[0132] S24, Based on the aforementioned computational model, the backend application layer predicts the operational status of the rail transit lines;

[0133] S25, Based on the comparison results between the predicted rail transit line operation status and the actual rail transit line operation status received from the site, optimize the multiple calculation models;

[0134] S3, based on the judgment that an abnormal scenario is in place, implements a real-time evaluation process for rail transit in abnormal scenarios, including:

[0135] S31, the background application layer evaluates the impact of sudden line failures or emergencies on the line operation status of the rail transit; the external system (usually an intelligent dispatching system or ATS system) automatically generates several new operation plans based on the nature of the sudden line failures or emergencies and their impact on the line operation status of the rail transit.

[0136] S32, the external system automatically deduces the operation plan based on the predicted rail transit line operation status and the impact on the rail transit line operation status;

[0137] S33, run the simulation operation plan and calculate the evaluation indicators of the simulation operation plan based on the on-site operation of the simulation operation plan;

[0138] S34, the evaluation indicators of each new operation plan are fed back to the front-end interface layer for display, so that the dispatchers can quantitatively evaluate the merits of each new operation plan.

[0139] In addition to the aspects and any possible implementations described above, a further implementation is provided, wherein the plurality of operational models in S22 include:

[0140] Driving analysis model, energy consumption analysis model, and passenger flow and vehicle flow coupling model.

[0141] In addition to the aspects and any possible implementations described above, a further implementation is provided in which S23, demonstrating the day's operational organization plan and actual execution, includes:

[0142] The real-time evaluation system obtains the daily operational plan from external systems and displays the daily operational plan on the front-end interface layer.

[0143] During the day's operation, the real-time evaluation system obtains data from the rail transit operation site or forwards the actual operation status of the day from external systems, and displays it on the front-end interface in the form of actual operation diagrams and evaluation indicators.

[0144] In addition to the aspects and any possible implementations described above, an implementation is further provided in which S24 includes:

[0145] During the implementation of the day's operation plan, the real-time evaluation system quickly calculates the on-site operation status for the next hour based on the on-site driving data and status data (such as changes and distribution of on-site passenger flow, changes in on-site vehicle flow, and the matching of passenger flow and vehicle flow, etc.).

[0146] If an abnormal event affecting operations (such as a sudden surge in passenger flow or abnormal train speed reduction) is predicted to occur within the first threshold time range (in this embodiment, one hour is selected), it will be promptly fed back to the front-end interface layer for display.

[0147] Evaluation indicators are determined for the current operating organization based on the results of the calculations and predictions.

[0148] As described above and in any possible implementation, a further implementation is provided, wherein S32 includes:

[0149] The external system will send the new operating plan and a description of any sudden line failures or incidents to the real-time evaluation system.

[0150] The real-time evaluation system quickly extrapolates the traffic and passenger flow situation under the influence of the new operational plan, based on the on-site conditions at the corresponding moment and the new operational plan.

[0151] See you again Figure 3 The backend application layer continuously loops through the operational plan until the end of the day's operations or a new plan is implemented. The backend application layer and the human-machine interface display the current planned plan, actual operational plan, train status, and track status; it also predicts the line's operational status one hour after the current operating time. The interaction between the backend application layer and the integrated system includes: the backend application layer obtaining the day's planned operational plan, train data, track status information, and on-site passenger flow data from the integrated system; the backend application layer providing timely warnings to the integrated system about abnormal events ahead of operations (within the next hour); and the integrated system sending on-site fault information and corresponding solutions to the backend application layer. The backend application layer displays the on-site faults or events to the human-machine interface and loads the corresponding solutions; it provides feedback on the indicators of each solution across various dimensions, and selects the optimal solution based on a comprehensive indicator; it provides feedback on the optimal solution to the integrated system through the human-machine interface and updates the new operational plan to the backend application layer. The core service layer creates several on-site environments equal to the number of solutions and quickly performs calculations based on the corresponding new operational plan.

[0152] Figure 4 As shown, the present invention also provides an electronic device, including a processor 301 and a memory 302 connected to the processor 301. The memory 302 stores a plurality of instructions, which can be loaded and executed by the processor to enable the processor to perform the method described in Embodiment 2.

[0153] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0154] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0155] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0156] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0157] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0158] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0159] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0160] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A real-time evaluation system for rail transit, adopting a layered architecture, characterized in that, include: It integrates external systems, serving as a third-party system, to provide multi-dimensional operational status information for rail transit; The core service layer includes a message engine unit, a data service unit, a rule engine unit, and an integration interface. The integration interface interacts with the interfaces of the external systems being integrated. The rule engine unit unifies the information flow within the system. The data service unit records the data, logs, and alarm information of the evaluation system. The message engine unit implements the internal communication of the evaluation system. The core service layer manages status data, basic data, and passenger flow data. The backend application layer is used to integrate the operational status information and quantitatively evaluate the current operational status of the rail transit based on different angles and dimensions using calculated evaluation indicators. The quantitative evaluation of the current operational status of the rail transit based on different angles and dimensions using calculated indicators includes managing the operation plan, constructing scenarios, performing train operation analysis, passenger flow analysis, and calculating indicators for the operation plan, and evaluating the network passenger flow, including: analyzing the spatiotemporal distribution of passenger flow and evaluating the operation plan from the perspective of passenger flow. The evaluation of network operation includes: analyzing the network's operation status and assessing the rationality of the operation organization in conjunction with the evaluation of network passenger flow; The assessment of fault event mitigation includes: for sudden faults, quickly analyzing the latest organizational operational plan and evaluating the degree to which the operational plan mitigates the impact on the overall line operation, providing support for the selection or further optimization of the operational plan; and The operational plan is simulated and calculated, including: proposing new operational plans for sudden line failures or human intervention; rapidly deriving and evaluating the impact of the new operational plan on the entire line's operational organization, passenger flow, traffic flow, and energy consumption based on the new operational plan; and... The front-end interface layer, or UI layer, is used to enable interaction with users, allowing them to input and view relevant operational data metrics.

2. The real-time evaluation system for rail transit according to claim 1, characterized in that, The evaluation indicators include passenger flow indicators, operational efficiency indicators, driving indicators, and energy consumption indicators.

3. A real-time evaluation method for rail transit, implemented based on the evaluation system described in any one of claims 1-2, characterized in that, include: S1, determine whether the rail transit is in a normal or abnormal scenario; S2, based on the judgment that the scenario is normal, implements the real-time evaluation process for rail transit in normal scenarios, including: S21, reads real-time basic information data of the line from the core service layer; S22, establish multiple computing models and start the corresponding computing model based on the real-time basic information data; S23 showcases the day's operational organization plan and its actual implementation; S24, Based on the aforementioned computational model, the backend application layer predicts the operational status of the rail transit lines; S25, Based on the comparison results between the predicted rail transit line operation status and the actual rail transit line operation status received from the site, optimize the multiple calculation models; S3, based on the judgment that an abnormal scenario is in place, implements a real-time evaluation process for rail transit in abnormal scenarios, including: S31, the background application layer evaluates the impact of sudden line failures or emergencies on the line operation status of the rail transit; the external system automatically generates several new operation plans based on the nature of the sudden line failures or emergencies and their impact on the line operation status of the rail transit. S32, the external system automatically deduces the operation plan based on the predicted rail transit line operation status and the impact on the rail transit line operation status; S33, run the simulation operation plan and calculate the evaluation indicators of the simulation operation plan based on the on-site operation of the simulation operation plan; S34, the evaluation indicators of each new operation plan are fed back to the front-end interface layer for display, so that the dispatchers can quantitatively evaluate the merits of each new operation plan.

4. The real-time evaluation method for rail transit according to claim 3, characterized in that, The plurality of computational models in S22 include: Driving analysis model, energy consumption analysis model, and passenger flow and vehicle flow coupling model.

5. The real-time evaluation method for rail transit according to claim 3, characterized in that, S23, which demonstrates the day's operational organization plan and its actual implementation, includes: The real-time evaluation system obtains the daily operational plan from external systems and displays the daily operational plan on the front-end interface layer. During the day's operation, the real-time evaluation system obtains data from the rail transit operation site or forwards the actual operation status of the day from external systems, and displays it on the front-end interface in the form of actual operation diagrams and evaluation indicators.

6. The real-time evaluation method for rail transit according to claim 3, characterized in that, S24 includes: During the implementation of the day's operational plan, the real-time evaluation system quickly calculates the on-site operational status within a certain range of future events based on on-site driving and status data. If an abnormal event affecting operations is predicted to occur within the first threshold time range in the future, it should be promptly reported to the front-end interface layer for display. Evaluation indicators are determined for the current operating organization based on the results of the calculations and predictions.

7. The real-time evaluation method for rail transit according to claim 3, characterized in that, S32 includes: The external system will send the new operating plan and a description of any sudden line failures or incidents to the real-time evaluation system. The real-time evaluation system quickly extrapolates the traffic and passenger flow situation under the influence of the new operational plan, based on the on-site conditions at the corresponding moment and the new operational plan.

8. An electronic device, characterized in that, It includes a processor and a memory, the memory storing multiple instructions, and the processor being used to read the instructions and execute the method as described in any one of claims 3-7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a plurality of instructions, which can be read by a processor and executed as described in any one of claims 3-7.

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