Railway passenger station panoramic management and control method and system based on digital twinning

Abstract

The invention provides a railway passenger station panoramic management and control method and system based on digital twinning, and the method comprises the steps: building a digital twinning three-dimensional model according to the graphic data and geographic space data of each entity device collected in real time, and integrating the working data of each entity device and personnel according to the space updating or main body contrast relation, the working data comprises real-time operation data, historical operation data, future plan operation data and external environment data; statistical characteristics are obtained after working parameters are processed and input into a prediction model to obtain a prediction result of the running state of the railway passenger station, a control plan is generated in combination with preset control logic, simulation running simulation is conducted on the digital twin three-dimensional model, and after the control plan is adjusted according to the simulation result, the running state is implemented and displayed on all entity devices. And when the risk index exceeds a preset risk threshold value, an early warning signal is sent out.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of railway passenger station management and control, and particularly relates to a railway passenger station panoramic management and control method and system based on digital twinning. BACKGROUND

[0002] Railway is the main mode of passenger transport in China. The development of the management and control platform relying on the Beijing-Zhangjiakou high-speed railway project has achieved preliminary results in informatization. The information infrastructure is continuously improved, and the data communication network, computing storage resources, and data real-time collection capabilities are continuously improved. The key business information system business coverage has been realized in the construction of railway passenger station information system. However, with the gradual increase of railway passenger flow, the pressure of railway passenger station management and control methods in passenger service and production operation is also increasing, which cannot meet the growing passenger flow demand.

[0003] In the prior art, the passenger flow management and control method of the railway passenger station still has a large amount of manual control. Although the railway passenger station has initially realized the informatization coverage of each system, the integration degree of each system is not high, and the railway passenger station management and control method is relatively backward. The visual display adopts 2D or 2.5D mode, which cannot realize the dynamic real-time twinning display of train operation data and stop station business association and emergency deduction. The railway passenger station lacks a three-dimensional model and business linkage integrated panoramic management and control method, which cannot provide accurate services for passengers, cannot improve production operation efficiency, and is difficult to support the growing passenger flow demand. The train, personnel, equipment, operation, and environment are not strongly integrated, and a closed-loop management and control in use and management has not been formed, resulting in low management efficiency. The railway passenger station has a single mode for processing real-time and emergency events, the risk estimation and judgment strategy is not accurate, and the fine service capability is weak. SUMMARY

[0004] Therefore, the embodiments of the present application provide a railway passenger station panoramic management and control method and system based on digital twinning to eliminate or improve one or more defects in the prior art, and solve the problem that the railway passenger station cannot be panoramically managed and controlled through a three-dimensional model in the prior art.

[0005] One aspect of the present application provides a railway passenger station panoramic management and control method based on digital twinning, which comprises the following steps:

[0006] Based on a building information model and a geographic information system, a digital twin three-dimensional model of the railway passenger station is constructed according to real-time collection of graphic data and geographic spatial data of each entity device in the railway passenger station, working data of each entity device in the railway passenger station is integrated into the digital twin three-dimensional model according to a spatial relationship or a subject contrast relationship, the working data including real-time operation data, historical operation data, future planned operation data and external environment data; the real-time operation data, the historical operation data and the future planned operation data all include personnel allocation data and entity device operation data;

[0007] According to a preset analysis algorithm, the working parameters of each entity device are processed to obtain statistical characteristics, and a pre-trained prediction model is processed to obtain a prediction result of the operation state of the railway passenger station, and a control plan for allocating personnel and entity devices and processing the risk situation of the railway passenger station is generated according to the prediction result combined with a preset control logic;

[0008] The control plan is simulated and run on the digital twin three-dimensional model, and the control plan is adjusted according to the simulation result, and the adjusted control plan is implemented for each entity device in the railway passenger station and the running state is displayed.

[0009] In some embodiments, based on a building information model and a geographic information system, a digital twin three-dimensional model of the railway passenger station is constructed according to real-time collection of graphic data and geographic spatial data of each entity device in the railway passenger station, including:

[0010] The graphic data is input into a building information model to obtain a three-dimensional device model of each entity device, and the geographic spatial data is converted and formatted into a geographic information system to obtain a spatial position relationship and a geographic position relationship of each entity device;

[0011] The three-dimensional device model is fused with the spatial position relationship and the geographic position relationship through a preset data conversion tool, and the digital twin three-dimensional model containing the architectural details and the architectural position relationship of the railway passenger station is obtained;

[0012] The digital twin model is checked for gaps, overlaps or abnormal shapes and adjusted.

[0013] In some embodiments, the working data acquisition step includes:

[0014] Real-time monitoring of train in-transit information, timetables, schedules and actual train arrival and departure times, real-time monitoring of the operation state of each entity device in the railway passenger station when the train arrives and departs, and obtaining worker information according to a preset personnel work plan and a positioning tool;

[0015] Obtaining the passenger flow, passenger flow direction, passenger behavior, queue number, train flow number and personnel allocation in the railway passenger station per hour through video monitoring, ticketing data and ticket checking data, and obtaining the passenger flow, passenger flow direction, passenger behavior, queue number, train flow number and personnel allocation in the railway passenger station per hour in the future according to the passenger flow, passenger flow direction, passenger behavior, queue number, train flow number, personnel allocation in the railway passenger station per hour in the past, ticketing data and ticket checking data.

[0016] In some embodiments, the working data of each entity device in the railway passenger station is integrated into the digital twin three-dimensional model according to a spatial relationship or a subject relationship, including:

[0017] The graphic data and the geographic spatial data of each entity device are transmitted to an edge computing node, and after data cleaning, format conversion, noise filtering and data compression are performed on the edge computing node, they are transmitted to a cloud computing platform;

[0018] The processed graphic data and geographic spatial data are time-correlated and spatially-positioned with the real-time operation data, the historical operation data, the future planned operation data and the external environment data, and are integrated into the corresponding entity device in the digital twin three-dimensional model using data merging algorithm and data correlation algorithm.

[0019] In some embodiments, the working parameters of each entity device are processed according to a preset analysis algorithm to obtain statistical features, and a pre-trained prediction model is used to obtain a prediction result of the operation state of the railway passenger station, including:

[0020] The real-time operation data, the historical operation data, the future planned operation data and the external environment data are formatted;

[0021] Features are extracted by correlation analysis method or principal component analysis method, and the extracted features are standardized to obtain the statistical features.

[0022] In some embodiments, the pre-training process of the prediction model includes:

[0023] Obtaining a training sample set, the training sample set containing a plurality of samples, each sample containing a statistical feature obtained by processing the working parameters of an entity device; the statistical feature taking a true value of the operation state of the railway passenger station as a label;

[0024] The initial neural network model is trained by the training sample set, the initial neural network model takes a sample in the training sample set as input and takes a running state prediction value as output, a loss function is constructed by a deviation between the running state prediction value and a running state true value, and the initial neural network model is iteratively updated in parameters to minimize the loss function until a preset termination condition is reached to obtain the prediction model.

[0025] In some embodiments, adjusting the management and control plan according to the simulation result, and implementing the adjusted management and control plan on each entity device in the railway passenger station and displaying the running state further include:

[0026] According to the running state, a risk index is obtained by identifying potential risks, and the risk index is compared with a preset risk threshold, and a warning signal is issued when the risk index approaches or exceeds the preset risk threshold;

[0027] The device state and passenger flow of each entity device and the warning signal are marked and displayed by means of text marking and color classification.

[0028] On the other hand, the present application also provides a panoramic management and control system for a railway passenger station based on digital twinning, which is used to execute any one of the above-mentioned panoramic management and control methods for a railway passenger station based on digital twinning, and the system comprises:

[0029] A physical data collection module is configured to collect graphic data and geospatial data of each entity device in the railway passenger station in real time;

[0030] A digital twinning model construction module is configured to construct a digital twinning three-dimensional model of the railway passenger station based on a building information model and a geographic information system according to the graphic data and geospatial data of each entity device in the railway passenger station collected in real time, and integrate working data of each entity device in the railway passenger station into the digital twinning three-dimensional model according to spatial relationships or subject contrast relationships; the working data includes real-time running data, historical running data, future planned running data and external environment data; the real-time running data, the historical running data and the future planned running data all include personnel allocation data and entity device operation data;

[0031] An analysis and prediction module is configured to process the working parameters of each entity device according to a preset analysis algorithm to obtain statistical characteristics, input a pre-trained prediction model to process a prediction result of a running state of the railway passenger station, and generate a management and control plan for allocating personnel and entity devices and processing risk conditions of the railway passenger station according to the prediction result and a preset control logic;

[0032] The application module is used to simulate the operation of the control plan on the digital twin 3D model, adjust the control plan according to the simulation results, implement the adjusted control plan on each physical equipment in the railway passenger station, and display the operation status.

[0033] On the other hand, the present invention also provides a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implement the steps of any of the methods described above.

[0034] On the other hand, the present invention also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of any of the methods described above.

[0035] The beneficial effects of the present invention are at least as follows:

[0036] The panoramic management and control method and system for railway passenger stations based on digital twins described in this invention utilizes Building Information Modeling (BIM) and Geographic Information System (GIS) to construct a digital twin 3D model of the railway passenger station based on real-time collected graphic data and geospatial data of various physical equipment. This allows for an intuitive understanding of the station's operational status. The system processes the operating parameters of each physical equipment using a preset analysis algorithm to obtain statistical characteristics, which are then input into a pre-trained prediction model to obtain a prediction of the station's operational status. Based on the prediction results and preset control logic, a management and control plan is generated for allocating personnel and physical equipment and handling risks at the railway passenger station. This plan ensures efficient operation of the railway passenger station by rationally allocating personnel and equipment, improving resource utilization, and accurately allocating station service resources to provide personalized service information to passengers. By predicting risks at the passenger station, contingency plans for emergencies can be developed in advance to reduce the impact of emergencies on station operations. The digital twin 3D model is used to simulate and run the control plan, dynamically adjust the control plan, flexibly respond to the development and changes of emergencies, improve the station's ability to deal with complex situations, improve the speed and accuracy of emergency response, and effectively handle various risk situations. The digital twin 3D model realizes the deep integration of physical entities and virtual models, realizes intelligent and refined management of railway passenger stations, realizes automated allocation and linkage control of personnel and physical equipment, improves the standardization and consistency of management and the overall operation and management level of the station. Furthermore, the digital twin 3D model provides a unified visualization platform for different physical equipment in the station, promotes information sharing and collaborative operation among various physical equipment, and improves overall work efficiency.

[0037] Additional advantages, objects, and features of the invention will be set forth in part in the description which follows, and will also become apparent in part to those skilled in the art upon studying the description, or may be learned by practice of the invention. The objects and other advantages of the invention can be realized and obtained by means of the structures specifically pointed out in the description and drawings.

[0038] Those skilled in the art will understand that the objectives and advantages achievable with the present invention are not limited to those specifically described above, and that the above and other objectives achievable with the present invention will become clearer from the following detailed description. Attached Figure Description

[0039] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, are not intended to limit the scope of the invention. In the drawings:

[0040] Figure 1 This is a flowchart illustrating a panoramic management and control method for railway passenger stations based on digital twins, as described in an embodiment of the present invention.

[0041] Figure 2 This is a schematic diagram of the structure of a panoramic management and control system for railway passenger stations based on digital twins, as described in an embodiment of the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the embodiments and accompanying drawings. Here, the illustrative embodiments and descriptions of this invention are used to explain the invention, but are not intended to limit the invention.

[0043] It should also be noted that, in order to avoid obscuring the invention with unnecessary details, only the structures and / or processing steps closely related to the solution according to the invention are shown in the accompanying drawings, while other details that are not closely related to the invention are omitted.

[0044] It should be emphasized that the term "including / comprises" as used herein refers to the presence of a feature, element, step, or component, but does not exclude the presence or addition of one or more other features, elements, steps, or components.

[0045] It should also be noted that, unless otherwise specified, the term "connection" in this article can refer not only to a direct connection, but also to an indirect connection involving an intermediary.

[0046] In the following description, embodiments of the invention will be illustrated with reference to the accompanying drawings. In the drawings, the same reference numerals represent the same or similar parts, or the same or similar steps.

[0047] In existing technologies, passenger flow management in railway passenger stations still relies heavily on manual control. Although railway passenger stations have achieved initial information coverage of various systems, the integration level of these systems is low, and the management methods are relatively outdated. Visualization displays use 2D or 2.5D methods, which cannot achieve dynamic, real-time twin-like displays that link train operation data with business operations such as stops and emergency simulations. This invention proposes a panoramic management method and system for railway passenger stations based on digital twins. Based on Building Information Modeling (BIM) and Geographic Information System (GIS), a digital twin 3D model of the railway passenger station is constructed using real-time collected graphic data and geospatial data of various physical equipment. The working data of each physical equipment in the railway passenger station are integrated into the digital twin 3D model according to spatial relationships or subject-specific correspondences. The model includes operational data such as real-time operation data, historical operation data, planned future operation data, and external environment data. The real-time operation data, historical operation data, and planned future operation data all include personnel allocation data and physical equipment operation data. Statistical features are obtained by processing the operational parameters of each physical equipment using a preset analysis algorithm, and then input into a pre-trained prediction model to obtain a prediction result of the railway passenger station's operational status. Based on the prediction result and preset control logic, a management and control plan is generated for allocating personnel and physical equipment and handling risks at the railway passenger station. The management and control plan is simulated on the digital twin 3D model, and the plan is adjusted based on the simulation results. The adjusted management and control plan is then implemented on each physical equipment in the railway passenger station, and its operational status is displayed.

[0048] Figure 1 This is a flowchart illustrating a panoramic management and control method for railway passenger stations based on digital twins, as described in an embodiment of the present invention. Specifically, one aspect of the present invention provides a panoramic management and control method for railway passenger stations based on digital twins, which includes the following steps S101 to S103:

[0049] Step S101: Based on Building Information Modeling (BIM) and Geographic Information System (GIS), construct a digital twin 3D model of the railway passenger station using real-time collected graphic data and geospatial data of each physical equipment. Integrate the operational data of each physical equipment in the railway passenger station into the digital twin 3D model according to spatial relationships or subject-specific correspondences. The operational data includes real-time operation data, historical operation data, future planned operation data, and external environment data. Real-time operation data, historical operation data, and future planned operation data all include personnel allocation data and physical equipment operation data.

[0050] Step S102: Process the working parameters of each physical device according to the preset analysis algorithm to obtain statistical features, and input them into the pre-trained prediction model to obtain the prediction results of the railway passenger station's operating status. Based on the prediction results and the preset control logic, generate a management and control plan for allocating personnel and physical devices and handling the risk situation of the railway passenger station.

[0051] Step S103: Simulate the operation of the control plan on the digital twin 3D model, adjust the control plan according to the simulation results, implement the adjusted control plan on each physical equipment in the railway passenger station, and display the operation status.

[0052] In step S101, in some embodiments, based on Building Information Modeling (BIM) and Geographic Information System (GIS), a digital twin 3D model of the railway passenger station is constructed according to the graphic data and geospatial data of each physical equipment in the railway passenger station collected in real time, including steps S1011 to S1013:

[0053] Step S1011: Input the graphic data into the building information model to obtain the three-dimensional equipment model of each entity equipment. After performing coordinate system transformation and format conversion on the geospatial data, input it into the geographic information system to obtain the spatial position relationship and geographical location relationship of each entity equipment.

[0054] Step S1012: Using a preset data conversion tool, the 3D equipment model is fused with spatial and geographical relationships to obtain a digital twin 3D model containing the architectural details and architectural location relationships of the railway passenger station.

[0055] Step S1013: Check the digital twin model for gaps, overlaps, or abnormal shapes and make adjustments.

[0056] Specifically, the graphic data includes the geometry, size, and material of each physical device in the railway passenger station; the geospatial data includes the spatial relationships between these devices and the geographical relationships surrounding the railway passenger station; the Building Information Model (BIM) constructs a 3D model of the internal equipment of the railway passenger station using the geometric and attribute information of each physical device; the Geographic Information System (GIS) performs coordinate system transformation on the collected geospatial data to ensure consistency with the actual geographical location of the railway passenger station, for example, transforming the geographic coordinate system to a Cartesian coordinate system; then, through data encoding, decoding, and compression, the data is converted into a format that the GIS can recognize and process before being input into the GIS; preset conversion tools align and match the 3D equipment model with the spatial and geographical relationships, ensuring that each physical device accurately corresponds to a digital twin 3D model in the 3D equipment model and the GIS, which includes the building structure and equipment layout; furthermore, adjustments are made to digital twin 3D models with gaps, overlaps, or abnormal shapes to ensure complete synchronization with the railway passenger station. Building information models include, but are not limited to, Autodesk Revit, Bentley Architecture, and Archicad; geographic information systems include, but are not limited to, ArcGIS Desktop, QGIS, and Global Mapper.

[0057] In some embodiments, the working data of various physical equipment in a railway passenger station are integrated into a digital twin 3D model according to spatial relationships or subject-to-subject correspondence relationships, including steps S11 to S12:

[0058] Step S11: Transmit the graphic data and geospatial data of each physical device to the edge computing node, and then transmit the data to the cloud computing platform after data cleaning, format conversion, noise filtering and data compression at the edge computing node.

[0059] Step S12: Perform time and spatial correlation between the processed graphic data and geospatial data and real-time operation data, historical operation data, future planned operation data and external environment data, and use data merging algorithm and data correlation algorithm to merge and integrate the data into the corresponding physical device in the digital twin 3D model.

[0060] Furthermore, each physical device is associated with its corresponding operational data for each time period. The operational data includes data from different sources and in different formats. Data of different formats is converted into data formats through image compression and video frame extraction. Sequence data from different times are synchronized through time alignment. External environmental data includes, but is not limited to, light intensity, air quality, temperature, and humidity. Personnel allocation data and physical equipment operation data enable the monitoring of personnel elements and physical equipment operation elements in railway passenger stations. Physical equipment includes, but is not limited to, trains, station buildings, turnstiles, broadcasting equipment, Bluetooth, guidance screens, radio frequency modules (RFID), elevators, sensors, end alarm devices, water supply equipment, sewage suction equipment, and cameras. In some embodiments, the steps for acquiring operational data include: real-time monitoring of train on-the-go information, timetables, schedules, and actual train arrival and departure times; real-time monitoring of the operational status of each physical device in the railway passenger station when trains arrive and depart; and obtaining staff information based on preset personnel work plans and positioning tools.

[0061] By using video surveillance, ticketing data, and ticket checking data, we can obtain hourly passenger flow, passenger flow direction, passenger behavior, number of people queuing, number of people moving on trains, and personnel allocation within railway passenger stations. Based on historical hourly passenger flow, passenger flow direction, passenger behavior, number of people queuing, number of people moving on trains, personnel allocation, and future hourly passenger flow, passenger flow direction, passenger behavior, number of people queuing, number of people moving on trains, and personnel allocation within railway passenger stations, we can obtain future hourly passenger flow, passenger flow direction, passenger behavior, number of people queuing, number of people moving on trains, and personnel allocation within railway passenger stations.

[0062] In step S102, in some embodiments, the working parameters of each physical device are processed according to a preset analysis algorithm to obtain statistical features, which are then input into a pre-trained prediction model to obtain the prediction result of the railway passenger station's operating status, including steps S1021 to S1022:

[0063] Step S1021: Format the real-time running data, historical running data, future planned running data, and external environment data.

[0064] Step S1022: Extract features using correlation analysis or principal component analysis, and standardize the extracted features to obtain statistical features.

[0065] Specifically, formatting includes standardizing data formats, data cleaning, and data transformation; correlation analysis methods calculate correlation coefficients between different data and identify features highly correlated with the operational status of railway passenger stations. Examples include calculating the correlation coefficient between passenger flow and train delays / weather conditions, and the correlation coefficient between equipment malfunctions and equipment operating time / ambient temperature. Principal component analysis projects data into a new coordinate system through linear transformation, maximizing the variance along the principal component directions in the new coordinate system. This reduces high-dimensional data to a low-dimensional space and extracts the most important features. Examples include reducing features affecting passenger flow to a few principal components, and reducing features affecting the operational status of various equipment to a few principal components. Feature standardization methods include Z-score standardization and Min-Max standardization.

[0066] Furthermore, the prediction results of the railway passenger station's operational status include, but are not limited to, passenger flow prediction, usage status prediction of various physical equipment, train arrival and departure time prediction, and staff allocation prediction. The preset control logic is set based on the railway passenger station's operational rules and association rules. Examples include increasing or decreasing security checkpoints, transfer channels, and staff based on passenger flow prediction results; conducting equipment maintenance in advance based on equipment failure prediction results; and evacuating passengers and adjusting train timetables based on risk prediction results. In some embodiments, the pre-training process of the prediction model includes steps S21 to S22:

[0067] Step S21: Obtain a training sample set, which contains multiple samples. Each sample contains a statistical feature obtained by processing the working parameters of the physical device. The statistical feature is labeled with the actual value of the railway passenger station's operating status.

[0068] Step S22: Train the initial neural network model using the training sample set. The initial neural network model takes the samples in the training sample set as input and the predicted running state as output. Construct a loss function based on the deviation between the predicted running state and the actual running state. Iterate and update the parameters of the initial neural network model with the goal of minimizing the loss function until the preset termination condition is reached to obtain the prediction model.

[0069] In step S103, the control plan is simulated in a digital twin 3D model, including personnel deployment simulation, physical equipment deployment simulation, and risk handling simulation. Based on feedback data from the real-time simulation results, the control plan is adjusted according to preset control logic. The control plan includes, but is not limited to, changing the number of security checkpoints and staff, adjusting the distribution of staff in different areas, adjusting the layout of waiting areas, adjusting the number of ticket gates, and arranging physical equipment maintenance and preparing backup equipment in advance. In some embodiments, after adjusting the control plan based on the simulation results and implementing the adjusted control plan for each physical equipment in the railway passenger station and displaying its operational status, the plan further includes: identifying potential risks based on the operational status to obtain a risk index, comparing the risk index with a preset risk threshold, and issuing a warning signal when the risk index approaches or exceeds the preset risk threshold. The equipment status, passenger flow, and warning signals of each physical equipment are marked and displayed using text labels and color classification. Specifically, the operating status includes, but is not limited to, equipment operating parameters, equipment fault status, and passenger flow distribution status; the risk index is used to quantify the severity of risk situations, and the risk threshold is set through the operating rules and safety standards of railway passenger stations; the warning signal includes the risk type, risk location, and risk severity; for example, equipment status is marked as normal, faulty, and under maintenance using text labels, passenger flow is marked as low, medium, and high, and warning signals are marked as general warnings and special warnings, and different equipment statuses, passenger flows, and warning signals are classified and marked with different colors using color labels.

[0070] On the other hand, the present invention also provides a panoramic management and control system for railway passenger stations based on digital twins, the system comprising:

[0071] The physical data collection module is used to collect graphic and geospatial data of various physical equipment in railway passenger stations in real time.

[0072] The digital twin model construction module is used to construct a digital twin 3D model of a railway passenger station based on Building Information Modeling (BIM) and Geographic Information System (GIS), using real-time collected graphic and geospatial data of various physical equipment. It integrates the operational data of each physical equipment in the railway passenger station into the digital twin 3D model according to spatial relationships or subject-specific correspondences. The operational data includes real-time operational data, historical operational data, planned future operational data, and external environmental data; real-time operational data, historical operational data, and planned future operational data all include personnel deployment data and physical equipment operation data.

[0073] The analysis and prediction module is used to process the working parameters of each physical device according to the preset analysis algorithm to obtain statistical characteristics, and input them into the pre-trained prediction model to obtain the prediction results of the railway passenger station's operating status. Based on the prediction results and the preset control logic, a management and control plan is generated for allocating personnel and physical devices and handling the risks of the railway passenger station.

[0074] The application module is used to simulate the operation of the control plan on the digital twin 3D model, adjust the control plan according to the simulation results, implement the adjusted control plan on each physical equipment in the railway passenger station, and display the operation status.

[0075] On the other hand, the present invention also provides a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implements the steps of any of the above methods.

[0076] On the other hand, the present invention also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of any of the above methods.

[0077] The present invention will now be described with reference to a specific embodiment:

[0078] Figure 2 This is a schematic diagram of the structure of a panoramic management and control system for railway passenger stations based on digital twins, as described in an embodiment of the present invention. The present invention provides a panoramic management and control method and system for railway passenger stations based on digital twins. Through the perception of all elements of the railway passenger station and the construction of a digital twin 3D model of the railway passenger station using a 3D building information model and a geographic information system, a panoramic management and control method is achieved, enabling virtual-real interaction and precise control between the physical passenger station and the virtual model. Station operations and analysis results are dynamically displayed on the digital twin 3D model, helping railway passenger station personnel to anticipate potential problems and take timely measures. This achieves panoramic management and control based on digital twins, contributing to efficient passenger transport operations and precise passenger services at railway passenger stations. The core architecture of the panoramic management and control method for railway passenger stations based on digital twins consists of a physical data collection module, a digital twin model construction module, an analysis and prediction module, and an application module.

[0079] 1. The physical data collection module is responsible for collecting and monitoring the parameter information of each physical device in real time; the parameter information includes graphic data and geospatial data; physical devices include, but are not limited to, trains, station buildings, turnstiles, broadcasting equipment, Bluetooth, guidance screens, radio frequency modules (RFID), elevators, environmental sensors, positioning sensors, end alarm devices, water supply equipment, sewage suction equipment, and cameras.

[0080] 2. The digital twin model construction module constructs a digital twin 3D model based on Building Information Modeling or Geographic Information System, dynamically mapping the real-time status of the railway passenger station; the digital twin 3D model integrates multi-source heterogeneous data, including real-time operation data, historical operation data, future planned operation data and external environment data, and realizes interactive mapping between the railway passenger station and the virtual model through edge computing or cloud computing.

[0081] 3. The analysis and prediction module relies on the comprehensive analysis of real-time operation data, historical operation data, future planned operation data such as train schedules, work schedules, and passenger data of railway passenger stations in the digital twin layer, as well as external environmental data. It uses various data analysis algorithms and models to perform statistical analysis and trend prediction on the data to obtain the prediction results of the railway passenger station's operation status, study the dynamic allocation of passenger service resources, and provide control plans for the management of railway passenger stations.

[0082] 4. The application module develops applications that meet the business needs of railway passenger stations based on the decision support information provided by the analysis and prediction module. It simulates real-time scenarios of railway passenger stations, deduces the station's operational status, makes accurate decisions, and displays a real-time three-dimensional dynamic panorama of the railway passenger station, realizing panoramic management and control, as well as virtual and real mutual control of the safe operation of railway passenger stations.

[0083] 5. The core functions of the panoramic management and control method for railway passenger stations based on digital twins include full-element twin monitoring of railway passenger stations, panoramic simulation based on building information model or geographic information system, prediction of railway passenger station operation status, and precise decision-making and model management of railway passenger stations.

[0084] 5.1. Comprehensive twin monitoring of all elements of railway passenger stations, including personnel, physical equipment operations, and environment.

[0085] (1) Personnel monitoring: Personnel monitoring includes passenger and staff monitoring. Passengers are monitored in real time throughout the day and every hour through manual counting and video surveillance, including passenger flow, passenger flow direction, passenger behavior, number of people queuing, and number of people boarding / disembarking / transferring; staff are monitored in their work through Bluetooth and video surveillance.

[0086] (2) Monitoring of physical equipment operation: Real-time monitoring of physical equipment operation, including changes in the operation status of physical equipment when trains arrive and depart, changes in business processes, and normal fault status of equipment; Real-time monitoring of train information and flow at this station is achieved through train on-the-way information, timetable, basic plan, daily plan, and actual train arrival and departure data.

[0087] (3) Environmental monitoring: Monitor the external environmental data of railway passenger stations, including light intensity, air quality, temperature and humidity and PM2.5 concentration.

[0088] 5.2. Panoramic simulation based on building information modeling or geographic information system: Simulate all elements of railway passenger stations based on building information modeling or geographic information system, simulate railway passenger station areas, display different areas of railway passenger stations in layers, and support the display of personnel information, equipment distribution, environmental simulation, passenger flow simulation in waiting areas, passenger organization simulation, and safety control module display.

[0089] (1) Personnel Information Display: Provides basic information display function for railway passenger station staff, including name, age, position and responsibilities, as well as the number of staff and personnel information in each position at the current railway passenger station.

[0090] (2) Equipment distribution display: Based on the equipment history information, the equipment in different areas is simulated and simulated. At the same time, the equipment status marking and detailed information association viewing functions are supported.

[0091] (3) Environmental simulation and safety prediction: Based on environmental monitoring data, environmental elements in different regions are marked and displayed in the map of the geographic information system using text and color markings. At the same time, it supports the function of reminding based on risk index and risk threshold.

[0092] (4) Passenger flow simulation: Simulate the passenger routes, convection detection, passenger flow in different time periods and passenger flow in different areas of the station on the map of the geographic information system, and display the heat map of passenger flow distribution.

[0093] (5) Passenger transport organization simulation: Combining personnel information, passenger transport personnel are simulated and displayed in different areas of the geographic information system map, including but not limited to platforms, waiting rooms and exits. At the same time, it supports the marking of passenger transport operation status for different personnel.

[0094] (6) Emergency simulation: For railway passenger station emergency simulation, simulation is conducted on passenger station risk situations including large-scale delays, large passenger flow congestion, external natural disasters and station equipment failures.

[0095] 5.3. Prediction and projection of railway passenger station operation status: Comprehensive analysis of real-time operation data, historical operation data, future planned operation data and external environment data of railway passenger stations, combined with big data analysis and artificial intelligence models, to predict and project the operation status of railway passenger stations, assisting railway passenger stations in optimizing operation management, improving service efficiency and preventing potential risks.

[0096] (1) Passenger flow trend prediction: By integrating historical passenger flow data, real-time passenger flow data from multiple sources, future passenger flow data and external data, historical passenger flow data includes passenger flow data during holidays, weekdays and different weather conditions, as well as train timetable execution rate; real-time passenger flow data includes ticket sales data, number of people entering and exiting the station through security check and real-name ticket gates, queuing speed at the entrance captured by cameras in the station, and real-time passenger flow in the waiting hall; future passenger flow data includes train arrival and departure plans; external data includes weather information and transportation connection information, and time-segmented predictions are made for the number of people in the station and the passenger flow trends in key areas of the railway passenger station such as waiting room, platform, entrance, exit and transfer gate.

[0097] (2) Risk prediction: The control plan after analysis is dynamically displayed through the digital twin three-dimensional model and the effects of personnel allocation and physical equipment allocation are simulated. The risk situations that may occur in the operation of railway passenger stations are predicted and the risk situations including but not limited to abnormal operation on the same platform, abnormal operation of water supply and sewage suction, abnormal passenger behavior, abnormal passenger flow, large-scale delays, and end intrusion are classified and early warnings are issued.

[0098] 5.4. Precise Decision-Making in Railway Passenger Stations: Through dynamic panoramic simulation and analysis of digital twin 3D models, the station provides corresponding control plans for potential problems and coordinates personnel in different positions to complete real-time emergency response loops. This enables decision-making and handling of passenger congestion and risk warnings, and the station conducts panoramic simulations of the results after handling in the digital twin 3D model.

[0099] (1) Decision-making and response to passenger flow congestion: Based on passenger flow trend prediction, service resources are scientifically and rationally allocated in advance. For example, the number of real-name verification channels and security check channels are adjusted, and the effect of the adjustment is dynamically simulated and displayed through digital twin 3D model.

[0100] (2) Risk situation early warning and handling: Through the risk simulation model and safety situation simulation constructed by intelligent analysis algorithm, different handling strategy suggestions are provided for different types and levels of risks, providing decision support for passenger transport panoramic command, and the effects of different risk control plans are simulated through digital twin three-dimensional model.

[0101] 5.5. Model management includes data management of the digital twin 3D model and business behavior model management. Data management is used to manage the model data in the digital twin 3D model, including the 3D geometric parameters of personnel and physical equipment; business behavior model management uniformly manages all models related to trains, personnel, and physical equipment according to behavioral rules that are linked by business operations.

[0102] In summary, this invention provides a panoramic management and control method and system for railway passenger stations based on digital twins. Based on Building Information Modeling (BIM) and Geographic Information System (GIS), a digital twin 3D model of the railway passenger station is constructed using real-time collected graphic data and geospatial data of various physical equipment within the station. The operational data of each physical equipment is integrated into the digital twin 3D model according to spatial relationships or subject-specific correspondences. This operational data includes real-time operational data, historical operational data, future planned operational data, and external environment data. The real-time operational data, historical operational data, and future planned operational data all include personnel allocation data and physical equipment operation data. The operational parameters of each physical equipment are processed using a preset analysis algorithm to obtain statistical characteristics, which are then input into a pre-trained prediction model to obtain a prediction result of the railway passenger station's operational status. Based on the prediction result and preset control logic, a management and control plan is generated for allocating personnel and physical equipment and handling risks at the railway passenger station. The management and control plan is simulated on the digital twin 3D model, and the plan is adjusted based on the simulation results. The adjusted management and control plan is then implemented for each physical equipment in the railway passenger station, and its operational status is displayed.

[0103] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the aforementioned edge computing server deployment method. The computer-readable storage medium can be a tangible storage medium, such as random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, floppy disks, hard disks, removable storage disks, CD-ROMs, or any other form of storage medium known in the art.

[0104] Those skilled in the art will understand that the exemplary components, systems, and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software, or a combination of both. Whether implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention. When implemented in hardware, it can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this invention are programs or code segments used to perform the desired tasks. The programs or code segments can be stored in a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried in a carrier wave.

[0105] It should be clarified that the present invention is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of the present invention.

[0106] In this invention, features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, and / or combined with or in place of features of other embodiments.

[0107] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. For those skilled in the art, various modifications and variations can be made to the embodiments of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A panoramic management and control method for railway passenger stations based on digital twins, characterized in that, The method includes the following steps: Based on Building Information Modeling (BIM) and Geographic Information System (GIS), a digital twin 3D model of the railway passenger station is constructed using real-time collected graphic and geospatial data of various physical equipment. The operational data of each physical equipment in the railway passenger station is integrated into the digital twin 3D model according to spatial relationships or subject-specific correspondences. This operational data includes real-time operational data, historical operational data, planned future operational data, and external environment data. The real-time operational data, historical operational data, and planned future operational data all include personnel allocation data and physical equipment operation data. The operating parameters of each physical device are processed according to a preset analysis algorithm to obtain statistical characteristics, which are then input into a pre-trained prediction model to obtain a prediction result of the railway passenger station's operating status. Based on the prediction result and a preset control logic, a management and control plan is generated for allocating personnel and physical devices and handling risks at the railway passenger station. The control plan is simulated and run on the digital twin 3D model. The control plan is adjusted according to the simulation results. The adjusted control plan is implemented on each physical equipment in the railway passenger station and the operating status is displayed.

2. The panoramic management and control method for railway passenger stations based on digital twins according to claim 1, characterized in that, Based on Building Information Modeling (BIM) and Geographic Information System (GIS), a digital twin 3D model of the railway passenger station is constructed using real-time collected graphic data and geospatial data of various physical equipment within the station, including: The graphic data is input into the building information model to obtain the three-dimensional equipment models of each physical device. After the geospatial data is converted into a coordinate system and a format, it is input into the geographic information system to obtain the spatial and geographical location relationships of each physical device. By using a preset data conversion tool, the three-dimensional device model is fused with the spatial location relationship and the geographical location relationship to obtain the digital twin three-dimensional model containing the architectural details and architectural location relationship of the railway passenger station; Check the digital twin model for gaps, overlaps, or abnormal shapes and make adjustments.

3. The panoramic management and control method for railway passenger stations based on digital twins according to claim 1, characterized in that, The steps for acquiring the working data include: Real-time monitoring of train information, timetables, schedules, and actual arrival and departure times; real-time monitoring of the operational status of various physical equipment at the railway passenger station during train arrival and departure; and obtaining staff information based on preset personnel work plans and positioning tools. By using video surveillance, ticketing data, and ticket checking data, we can obtain hourly passenger flow, passenger flow direction, passenger behavior, number of people queuing, number of people moving on trains, and personnel allocation within railway passenger stations. Based on historical hourly passenger flow, passenger flow direction, passenger behavior, number of people queuing, number of people moving on trains, personnel allocation, and future hourly passenger flow, passenger flow direction, passenger behavior, number of people queuing, number of people moving on trains, and personnel allocation within railway passenger stations, we can obtain future hourly passenger flow, passenger flow direction, passenger behavior, number of people queuing, number of people moving on trains, and personnel allocation within railway passenger stations.

4. The panoramic management and control method for railway passenger stations based on digital twins according to claim 1, characterized in that, The operational data of each physical device in the railway passenger station are integrated into the digital twin 3D model according to spatial relationships or subject-specific correspondence relationships, including: The graphic data and geospatial data of each physical device are transmitted to the edge computing node, and after data cleaning, format conversion, noise filtering and data compression are performed at the edge computing node, the data is transmitted to the cloud computing platform. The processed graphic data and geospatial data are correlated with the real-time operation data, historical operation data, future planned operation data and external environment data in terms of time and spatial location. Then, data merging and data association algorithms are used to merge and integrate the data into the corresponding physical device in the digital twin 3D model.

5. The panoramic management and control method for railway passenger stations based on digital twins according to claim 1, characterized in that, The operating parameters of each physical device are processed according to a preset analysis algorithm to obtain statistical characteristics, which are then input into a pre-trained prediction model to obtain prediction results of the railway passenger station's operating status, including: The real-time operating data, the historical operating data, the future planned operating data, and the external environment data are formatted. Features are extracted using correlation analysis or principal component analysis, and the extracted features are then standardized to obtain the statistical features.

6. The panoramic management and control method for railway passenger stations based on digital twins according to claim 1, characterized in that, The pre-training process of the prediction model includes: A training sample set is obtained, which contains multiple samples, each of which contains a statistical feature obtained by processing the working parameters of the physical equipment; the statistical feature is labeled with the actual value of the railway passenger station's operating status. The initial neural network model is trained using the training sample set, with the samples in the training sample set as input and the predicted running state as output. A loss function is constructed based on the deviation between the predicted running state and the actual running state. The parameters of the initial neural network model are iteratively updated with the goal of minimizing the loss function until a preset termination condition is reached, thereby obtaining the prediction model.

7. The panoramic management and control method for railway passenger stations based on digital twins according to claim 1, characterized in that, After adjusting the control plan based on the simulation results, implementing the adjusted control plan on each physical device in the railway passenger station, and displaying the operational status, the process also includes: Based on the operating status, potential risks are identified to obtain a risk index. The risk index is compared with a preset risk threshold. When the risk index approaches or exceeds the preset risk threshold, a warning signal is issued. The equipment status of each physical device, passenger flow, and the aforementioned warning signals are marked and displayed using text labels and color classification.

8. A panoramic management and control system for railway passenger stations based on digital twins, characterized in that, The system includes: The physical data collection module is used to collect graphic and geospatial data of various physical equipment in railway passenger stations in real time; The digital twin model construction module is used to construct a digital twin 3D model of the railway passenger station based on building information modeling and geographic information system (BIMS) and according to the real-time collected graphic data and geospatial data of various physical equipment in the railway passenger station. The module integrates the operational data of each physical equipment in the railway passenger station into the digital twin 3D model according to spatial relationships or subject-specific correspondence relationships. The operational data includes real-time operational data, historical operational data, future planned operational data, and external environment data. The real-time operational data, historical operational data, and future planned operational data all include personnel allocation data and physical equipment operation data. The analysis and prediction module is used to process the working parameters of each physical device according to a preset analysis algorithm to obtain statistical characteristics, and input them into a pre-trained prediction model to obtain the prediction results of the railway passenger station's operating status. Based on the prediction results and preset control logic, a management and control plan is generated for allocating personnel and physical devices and handling the risk situation of the railway passenger station. The application module is used to simulate the operation of the control plan on the digital twin 3D model, adjust the control plan according to the simulation results, implement the adjusted control plan on each physical equipment in the railway passenger station, and display the operation status.

9. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method as described in any one of claims 1 to 7.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 7.

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