Turn-back control system based on virtual coupling train marshalling

Abstract

The invention discloses a turn-back control system based on virtual coupling train marshalling, and relates to the technical field of train turn-back automatic control, the turn-back control system comprises a turn-back control center, the turn-back control center is in communication connection with the following modules: a local information sensing module, a local information sending module, a local information receiving module and a local information sending module through a vehicle-mounted multi-source sensor and a train-to-train communication technology; acquiring environment sensing information around the train; and the distributed path planning module is used for calculating an optimal path according to the environment perception information of each train and coordinating path planning of each train. Through the distributed path planning module, each train can autonomously calculate the optimal turn-back path according to local information, compared with traditional centralized scheduling, the trains can quickly respond to path changes, the system response speed is remarkably improved, especially in the peak period or under the sudden failure condition, the train operation strategy can be adjusted in time, and the train return path planning efficiency is improved. Operation interruption is avoided, and continuity and stability of railway transportation are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic control for train turning-back, and particularly to a turning-back control system based on a virtual coupled train formation. Background Art

[0002] In railway transportation, train turning-back is a common operation. Especially at the terminal station or when there is no further forward movement, the train needs to return to the starting point. With the development of intelligent dispatching and big data technologies, modern railway systems have become increasingly dependent on automatic dispatching management. By integrating various intelligent devices and systems, full-process automatic control can be achieved, reducing human intervention and improving the flexibility and accuracy of dispatching.

[0003] For example, in the turning-back control method and control system for virtual formation of multiple trains with the Chinese patent publication number: CN114074696A, the frequency of sending turning-back control information by the ground control center is reduced, and the turning-back control information is transmitted through vehicle-to-vehicle communication between adjacent two trains, effectively saving the transmission time required for each train to transmit the turning-back control information separately to the ground control center.

[0004] In the prior art, the turning-back control information is transmitted between adjacent two trains through vehicle-to-vehicle communication, effectively saving the transmission time required for each train to transmit the turning-back control information separately to the ground control center. However, due to the need to process various situations such as path allocation, speed synchronization, and resource conflicts in real time for multi-train collaborative turning-back, during peak hours or in case of sudden failures, the system response speed is slow, easily leading to operation interruption. Therefore, how to adopt a distributed path planning algorithm, each train autonomously adjusts its operation strategy according to local information, reduces the pressure of centralized dispatching, and simulates the multi-train collaborative turning-back scenario in the digital twin system to verify the logical rationality of path allocation and speed synchronization, and optimize the control algorithm is the problem we need to solve. For this reason, a turning-back control system based on a virtual coupled train formation is proposed herein. Summary of the Invention

[0005] The purpose of the present invention is to provide a turning-back control system based on a virtual coupled train formation to solve the problems raised in the above background art.

[0006] To solve the above technical problems, the technical solution adopted by the present invention is: A turning-back control system based on a virtual coupled train formation includes a turning-back control center, and the turning-back control center is communicatively connected to the following modules, wherein: The turning-back control center, as the top-level control unit of the system, is responsible for global status monitoring, issuing resource allocation strategies, and intervening in abnormal situations, receiving real-time data from each module, and displaying the train operation situation through a visualization interface; The local information perception module is used to obtain the environmental perception information around the train through in-vehicle multi-source sensors and vehicle-to-vehicle communication technology, reduce the dependence on global information, and improve the adaptability of the system in complex environments; The distributed path planning module is used to calculate the optimal path according to the environmental perception information of each train and coordinate the path planning of each train; The digital twin simulation module is used to construct a virtual train model and an operation scenario library, simulate the multi-train collaborative reversal process, and verify the rationality of the path allocation and speed synchronization logic; The speed synchronization control module is used to adjust the speed of the train autonomously according to the local information of the train and the simulation results, monitor the speed and acceleration data of each train, and make it coordinated with other trains to achieve speed synchronization.

[0007] A further improvement of the technical solution of the present invention lies in that: the local information perception module specifically includes: Deploy in-vehicle multi-source sensors on the train, including radar, lidar, cameras, speed sensors, acceleration sensors, etc. Each in-vehicle multi-source sensor collects the environmental information around the train in real time according to the preset sampling frequency. At the same time, through vehicle-to-vehicle communication technology, receive the operation status information sent by adjacent trains; Preprocess the sensor data collected by the in-vehicle multi-source sensors and the vehicle-to-vehicle communication data, including data cleaning, noise filtering, and format unification, eliminate error data and redundant information, ensure the accuracy and consistency of the data, and use a multi-source information fusion algorithm to fuse the preprocessed sensor data and vehicle-to-vehicle communication data to form complete environmental perception information. Then integrate the fused data into a unified data packet and transmit the data packet to the database of the reversal control center through the train communication network for storage.

[0008] A further improvement of the technical solution of the present invention lies in that: the distributed path planning module includes a local path planning unit and a path coordination unit; Among them, the local path planning unit is used to independently calculate the optimal reversal path according to the environmental perception information of each train; The path coordination unit is used to coordinate the path planning of each train during the multi-train collaborative reversal, avoid path conflicts, and ensure the safe distance between trains.

[0009] A further improvement of the technical solution of the present invention lies in that: the local path planning unit specifically includes: Obtain the environmental perception information around the train from the local information perception module, including the environmental information around the train and the operation status information sent by adjacent trains, and set the goal of path planning as the shortest travel time according to the current position, target position of the train and the requirements of the return task, and determine the constraints of path planning, including avoiding collisions and conflicts, complying with track restrictions and considering the dynamics of adjacent trains. Then, construct a dynamic model of the train's surrounding environment based on the environmental perception information around the train, including track topology, obstacle positions, signal light states, and the positions and movement trends of adjacent trains; Select the Dijkstra algorithm as the path planning algorithm, model the track network as a graph structure, where nodes represent key positions, edges represent track segments, and the weight is the time for the train to pass through this track segment. Set the algorithm parameters according to the dynamic characteristics of the train and environmental constraints. Among them, the dynamic characteristics of the train are the maximum acceleration, maximum deceleration and turning radius limit, and the environmental constraints are signal light limits and obstacle avoidance; Input the dynamic model of the train's surrounding environment, the current position of the train, and the position of the target return point into the Dijkstra algorithm, and calculate multiple feasible return paths according to the track topology and environmental constraints; Calculate the total travel time of each return path, and then calculate the comprehensive score of the return path according to the travel time and safety. Select the path with the highest comprehensive score of the return path as the optimal return path.

[0010] A further improvement of the technical solution of the present invention lies in that: the calculation process of the comprehensive score of the return path is as follows: For each candidate path, calculate the total travel time for the train to pass through this path according to the track segment length and the train speed limit, find the minimum travel time and average travel time among all paths, calculate the average speed of the train on this path, and at the same time obtain the maximum allowable speed of the train on this path; Calculate the ratio of the minimum travel time to the total travel time to obtain the minimum travel time ratio function, calculate the ratio of the average travel time to the total travel time, add 1 and take the logarithm function to obtain the average travel time ratio function, then calculate the ratio of the average speed to the maximum allowable speed, multiply by the speed utilization adjustment coefficient to obtain the speed ratio function. Then, multiply the minimum travel time ratio function by the average travel time ratio function, and add the speed ratio function to obtain the travel time score; For each candidate path, analyze the relative position and distance change situation with obstacles, determine the minimum safety distance and average safety distance from obstacles, and evaluate whether the train meets the signal light requirements on this candidate path according to the signal light position and state, calculate the degree of meeting the signal light requirements, determine the maximum satisfaction degree of the signal light requirements. Then, combine the operation status information of adjacent trains to calculate the minimum safety distance and average safety distance from adjacent trains; Calculate the ratio of the minimum safety distance to the average safety distance to obtain the minimum safety distance ratio function, and calculate the ratio of the average safety distance to the minimum safety distance, add 1 and take the logarithm function to obtain the average safety distance ratio function. Then calculate the ratio of the degree of meeting the signal light requirements to the maximum satisfaction degree of the signal light requirements, multiply by the satisfaction adjustment coefficient to obtain the satisfaction ratio function. At the same time, calculate the ratio of the minimum safety distance to the average safety distance, multiply by the distance adjustment coefficient to obtain the distance ratio function. Furthermore, multiply the minimum safety distance ratio function by the average safety distance ratio function, add the satisfaction ratio function and the distance ratio function to obtain the safety score; According to the local path planning requirements, determine the travel time score and the safety score respectively, and calculate the weighted sum of the travel time score and the safety score to obtain the comprehensive score of the return path.

[0011] A further improvement of the technical solution of the present invention lies in that: the path coordination unit specifically includes: Collect the return path planning information of each train, including the current position, target position, current speed, planned path and estimated travel time of each train, and through vehicle-to-vehicle communication technology, obtain the return path planning information of adjacent trains in real time. Based on the collected information, analyze the return paths of all trains to detect whether there are return path conflicts, and then record the detected conflict information, including the numbers of the conflicting trains, conflict time, conflict location, conflict type, etc.; According to the urgency and task priority factors of the trains, assign priorities to each train, formulate conflict resolution strategies, and select corresponding coordination plans according to the priorities and conflict types; According to the coordination plan, adjust the return paths of each train, update the return path planning information, ensure that the adjusted return paths avoid conflict points, meet the requirements of operation safety and efficiency, and then feedback the adjusted return path information to the local path planning units of each train. Through vehicle-to-vehicle communication technology, synchronize the adjusted path information to adjacent trains to ensure coordinated operation, and continuously monitor the train operation status after the return path is adjusted, and further dynamically adjust the return path according to real-time information.

[0012] A further improvement of the technical solution of the present invention lies in that: the digital twin simulation module includes a virtual train modeling unit and a cooperative return simulation unit; Among them, the virtual train modeling unit is used to construct a virtual coupled train model including tracks, signal systems, trains and control centers, and map the operation status of physical trains in real time; The collaborative reverse simulation unit is used to simulate the multi - vehicle collaborative reverse scenario by combining a preset operation scenario library and a virtual train model, verify the logical rationality of path allocation and speed synchronization. Through collaborative reverse simulation, the rationality of the collaborative reverse process can be verified in a virtual environment, and potential problems can be discovered and solved in advance.

[0013] A further improvement of the technical solution of the present invention is that: the virtual train modeling unit specifically includes: Collect the actual geometric data of the track, including physical parameters such as geometric shape, length, gradient and curve radius, obtain the topological structure of the track, including turnouts, intersections and station positions, and collect information on the position, type and display status of signal lights, obtain the control logic and operation rules of the signal system. Furthermore, collect the physical parameters of the train, obtain the dynamic characteristics of the train, synchronously collect the dispatching plan, operation diagram and emergency handling plan information of the reverse control center, and digitally convert the collected various types of information to form a standardized data format; According to the collected track information, construct a virtual track model, including the geometric shape, topological structure, etc. of the track. According to the signal system information, construct a virtual signal system model, including the position, type, display status, etc. of signal lights. According to the train information, construct a virtual train model, including the physical parameters, dynamic characteristics, etc. of the train, and according to the information of the reverse control center, construct a virtual control center model, including the dispatching plan, operation diagram, etc. Furthermore, integrate the virtual models of the track, signal system, train and reverse control center to form a complete virtual coupled train model; Through sensors and communication technologies, real - time obtain the operation status information of the physical train, map the real - time obtained physical train status information to the virtual coupled train model, update the operation status of the virtual coupled train model, and dynamically update the operation status of the virtual coupled train model according to the real - time operation status information to ensure that the virtual coupled train model is always consistent with the physical system. When an abnormal situation (fault, emergency) in the system is detected, update the virtual coupled train model and trigger the corresponding early warning mechanism.

[0014] A further improvement of the technical solution of the present invention is that: the collaborative reverse simulation unit specifically includes: Pre - collect the multi - vehicle collaborative reverse requirements under different operation conditions, including peak hours, off - peak hours and special weather operation conditions, and accordingly preset an operation scenario library. According to the actual requirements, select an operation scenario that meets the current simulation requirements from the preset operation scenario library. At the same time, load the constructed virtual coupled train model, which contains detailed information such as the track, signal system, train and control center, and perform initialization settings on the loaded operation scenario and virtual coupled train model, including setting the start time of the simulation, the initial positions and states of each train, to ensure that the simulation environment meets the preset requirements; After completing the loading preparation of the operation scenario and the virtual coupled train model, the coordinated return simulation is started. Based on the preset path allocation and speed synchronization logic, the coordinated return process of multiple trains in the virtual environment is simulated. During the simulation, the control rules of the signal system and the dynamic characteristics of the train are followed, and key data such as the running trajectory, speed changes and position information of each train are recorded in real time. Through data monitoring and analysis, the operation of the trains is coordinated to avoid collisions, path conflicts and other problems, ensuring the smooth progress of the simulation process. After the simulation, the data recorded during the coordinated return process is analyzed, and the logical rationality of the path allocation and speed synchronization is verified. It is checked whether the train is traveling according to the planned path, whether the speed meets the synchronization requirements, and whether the key indicators of the safety distance are met. If there are logical irrationalities, such as the risk of path conflict, speed asynchrony leading to low operating efficiency, etc., the scene, time and relevant train information where the problem occurs are recorded, and adjustments and optimizations are made. The simulation verification is carried out again until the logic of path allocation and speed synchronization is completely reasonable, ensuring that potential problems are discovered and resolved in advance in the virtual environment, and improving the safety and efficiency of multi-vehicle coordinated return.

[0015] A further improvement of the technical solution of the present invention is that the speed synchronization control module specifically includes: Continuously monitor the operating status of each train, acquiring real-time train speed and acceleration data. Simultaneously, through the communication interface between the train and the system, collect local train information and obtain simulation data from the digital twin simulation module, including key parameters such as the train's speed and safety distance under ideal operating conditions. The real-time monitored train operating data is integrated with the simulation results provided by the simulation unit to build a comprehensive train operating status information database. Based on the integrated train operation status information, the actual speed of each train is compared with the ideal speed in the simulation results. The difference between each train and the ideal speed is calculated. In combination with the dynamic characteristics of the train, a targeted speed adjustment plan is formulated. According to the formulated speed adjustment plan, speed adjustment instructions are sent to relevant trains through the communication system. During the execution of the instructions, the train's response to the adjustment instructions is continuously monitored, and feedback data on train speed and acceleration are collected in real time. The feedback data is compared and analyzed with the expected adjustment effect. If it is found that the train speed is not adjusted as expected, or there is still a speed difference after the adjustment, the speed adjustment instruction is corrected, and the speed adjustment strategy is optimized based on the feedback information.

[0016] Due to the adoption of the above technical solution, the present invention has the following technical advancements compared to the prior art: 1. The present invention provides a reverse control system based on a virtual coupled train formation. Through a distributed path planning module, each train can independently calculate the optimal reverse path according to local information. Compared with traditional centralized scheduling, the train can quickly respond to path changes, significantly improving the system response speed. Especially during peak hours or in case of sudden failures, it can timely adjust the train operation strategy, avoid service interruptions, and ensure the continuity and stability of railway transportation.

[0017] 2. The present invention provides a reverse control system based on a virtual coupled train formation. By using the path coordination unit in the distributed path planning module, when multiple trains cooperate in reverse, it can coordinate the path planning of each train, avoid path conflicts, and ensure the safe distance between trains. Through path coordination, the system can more reasonably allocate track resources and improve the overall operation efficiency. In addition, the digital twin simulation module verifies the logical rationality of path allocation and speed synchronization in a virtual environment, discovers and solves potential problems in advance, and ensures the efficient and stable operation of the train during the reverse process. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0019] Figure 1 It is a schematic diagram of the working process of the present invention; Figure 2 It is a schematic diagram of the system function modules of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0021] Example 1, as Figure 1 、 2 shown, the present invention provides a reverse control system based on a virtual coupled train formation, including a reverse control center. The reverse control center is communicatively connected to the following modules, where: The return control center, as the top-level control unit of the system, is responsible for global status monitoring, resource allocation strategy distribution, and intervention in abnormal situations. It receives real-time data from each module and displays the train operation situation through a visual interface; The local information perception module is used to obtain the environmental perception information around the train through on-vehicle multi-source sensors and vehicle-to-vehicle communication technology, reduce the dependence on global information, and improve the adaptability of the system in complex environments. On-vehicle multi-source sensors are deployed on the train, including radar, lidar, cameras, speed sensors, acceleration sensors, etc. Each on-vehicle multi-source sensor collects the environmental information around the train in real time according to the preset sampling frequency. At the same time, through vehicle-to-vehicle communication technology, it receives the operation status information sent by adjacent trains. Among them, the data collected by the on-vehicle multi-source sensors includes track status, signal light status, the position and speed of the train ahead, obstacle information, and the operation status of the train itself. The vehicle-to-vehicle communication data includes the position, speed, acceleration, and braking status information of adjacent trains. The geometric shape of the track, obstacles, etc. are detected by lidar and cameras. The color and status of signal lights are identified by cameras. The dynamic information of the train ahead is detected by radar and lidar. Obstacles on the track are identified by lidar and cameras. Information such as the speed and acceleration of the train is obtained through speed sensors and acceleration sensors. The position, speed, and acceleration of adjacent trains are used to understand the dynamics of surrounding trains. The braking status information is used to judge the braking status of adjacent trains to make an early response. The sensor data collected by the on-vehicle multi-source sensors and the vehicle-to-vehicle communication data are preprocessed, including data cleaning, noise filtering, and format unification, to eliminate error data and redundant information, ensure the accuracy and consistency of the data, and use a multi-source information fusion algorithm to fuse the preprocessed sensor data and vehicle-to-vehicle communication data to form complete environmental perception information. Then, the fused data is integrated into a unified data packet, and the data packet is transmitted through the train communication network to the database of the return control center for storage; The distributed path planning module is used to calculate the optimal path according to the environmental perception information of each train and coordinate the path planning of each train. The distributed path planning module includes a local path planning unit and a path coordination unit; Among them, the local path planning unit is used to autonomously calculate the optimal reverse path according to the environmental perception information of each train. Through local path planning, each train can quickly respond to path changes, reduce the dependence on centralized scheduling, improve the system response speed, obtain the environmental perception information around the train from the local information perception module, including the environmental information around the train and the operation status information sent by adjacent trains, and set the goal of path planning as the shortest travel time according to the current position, target position of the train and the requirements of the reverse task, determine the constraints of path planning, including avoiding collisions and conflicts, complying with track restrictions and considering the dynamics of adjacent trains, and then construct a dynamic model of the train's surrounding environment according to the environmental perception information around the train, including the track topology structure, obstacle positions, signal light states and the positions and movement trends of adjacent trains, select the Dijkstra algorithm as the path planning algorithm, model the track network as a graph structure, where nodes represent key positions, edges represent track segments, and the weight is the time for the train to pass through this section of the track, and set the algorithm parameters according to the dynamic characteristics of the train and environmental constraints, where the dynamic characteristics of the train are the maximum acceleration, maximum deceleration and turning radius limit, and the environmental constraints are signal light restrictions and obstacle avoidance, input the dynamic model of the train's surrounding environment, the current position of the train and the position of the target reverse point into the Dijkstra algorithm, calculate multiple feasible reverse paths according to the track topology structure and environmental constraints, calculate the total travel time of each reverse path, including the time to pass through the track segment, evaluate the safety of each path, the distance from obstacles, whether it meets the signal light requirements and whether it violates the safety distance of adjacent trains, and then calculate the comprehensive score of the reverse path according to the travel time and safety, and select the path with the highest comprehensive score of the reverse path as the optimal reverse path; In addition, the calculation process of the comprehensive score of the reverse path is as follows: For each candidate path, according to the track segment length and the train speed limit, calculate the total running time of the train passing through this path, and find the minimum running time and the average running time among all paths. Calculate the average speed of the train on this path, and at the same time obtain the maximum allowable speed of the train on this path. Among them, the total running time of the train passing through this path is calculated according to the path length and the train speed limit. The path length is obtained through the track topology, and the speed limit is determined according to the track design and the train performance. The average speed of the train on this path is calculated according to the path length and the total running time of the train passing through this path, that is, the path length divided by the total running time of the train passing through this path. The maximum allowable speed of the train on this path is determined according to the train performance parameters and provided by the train manufacturer. The total running time of the train passing through this path is calculated according to the path length and the train speed limit. The path length is obtained through the track topology, and the speed limit is determined according to the track design and the train performance. The average speed of the train on this path is calculated according to the path length and the total running time of the train passing through this path, that is, the path length divided by the total running time of the train passing through this path. The maximum allowable speed of the train on this path is determined according to the train performance parameters and provided by the train manufacturer. Calculate the ratio of the minimum running time to the total running time to obtain the minimum running time ratio function, and calculate the ratio of the average running time to the total running time, then add 1 and take the logarithm function to obtain the average running time ratio function. Then calculate the ratio of the average speed to the maximum allowable speed, multiply by the speed utilization adjustment coefficient to obtain the speed ratio function. Furthermore, multiply the minimum running time ratio function by the average running time ratio function, and add the speed ratio function to obtain the running time score. For each candidate path, analyze its relative position and distance change with respect to the obstacles, determine the minimum safety distance and the average safety distance from the obstacles, and evaluate whether the train meets the signal light requirements on this candidate path according to the signal light position and status. Calculate the degree of meeting the signal light requirements and determine the maximum satisfaction of the signal light requirements. Furthermore, combine the operation status information of adjacent trains to calculate the minimum safety distance and the average safety distance from adjacent trains. Among them, the minimum safety distance from the obstacles is determined by analyzing the relative position and distance change between the train and the obstacles, and the distance information is provided by the local information perception module. The degree of meeting the signal light requirements is determined by evaluating whether the train meets the signal light requirements on this path according to the signal light position and status through the interaction between the train control system and the signal system. The maximum satisfaction of the signal light requirements is determined according to the design requirements of the signal light system and is the maximum satisfaction in the ideal state. The minimum safety distance from adjacent trains is obtained by using vehicle-to-vehicle communication technology to obtain the position information of adjacent trains and combining with the train's own position. The average safety distance is the average calculation of the distance between the train and adjacent trains, and the distance information is obtained by vehicle-to-vehicle communication technology. The minimum safety distance from the obstacles is determined by analyzing the relative position and distance change between the train and the obstacles, and the distance information is provided by the local information perception module.The degree of meeting the signal light requirements is evaluated based on the position and status of the signal lights to determine whether the train meets the signal light requirements on this path through the interaction between the train control system and the signal system. The maximum satisfaction degree of the signal light requirements is determined according to the design requirements of the signal light system, which is the maximum satisfaction degree in the ideal state. The minimum safe distance from adjacent trains is obtained by using vehicle-to-vehicle communication technology to acquire the position information of adjacent trains and calculating it in combination with the train's own position. The average safe distance is calculated by averaging the distances between the train and adjacent trains, and the distance information is obtained by vehicle-to-vehicle communication technology. Calculate the ratio of the minimum safe distance to the average safe distance to obtain the minimum safe distance ratio function, and calculate the ratio of the average safe distance to the minimum safe distance, add 1 and take the logarithmic function to obtain the average safe distance ratio function. Then calculate the ratio of the degree of meeting the signal light requirements to the maximum satisfaction degree of the signal light requirements, multiply it by the satisfaction adjustment coefficient to obtain the satisfaction ratio function. At the same time, calculate the ratio of the minimum safe distance to the average safe distance, multiply it by the distance adjustment coefficient to obtain the distance ratio function. Furthermore, multiply the minimum safe distance ratio function by the average safe distance ratio function, add the satisfaction ratio function and the distance ratio function to obtain the safety score. According to the local path planning requirements, determine the travel time score and the safety score respectively, and calculate the weighted sum of the travel time score and the safety score to obtain the comprehensive score of the return path; The calculation expression of the comprehensive score of the return path is: ; ; ; In the formula, is the comprehensive score of the return path, and are the weights of the travel time score and the safety score respectively, , is the travel time score, is the minimum travel time among all paths, is the total travel time of the current path, is the average travel time among all paths, is the average speed of the train on this path, is the maximum allowable speed of the train on this path, is the speed utilization adjustment coefficient, The value of tends to When increases, it indicates that the travel time of this path is shorter and the time efficiency is high. If tends to , then also increases correspondingly, which means that the train can run at a higher speed on this path, further improving the time efficiency. is the safety score. is the minimum safety distance from the obstacle. is the average safety distance from the obstacle. is the degree of meeting the signal lamp requirements. is the maximum satisfaction degree of the signal lamp requirements. is the minimum safety distance from the adjacent train. is the average safety distance from the adjacent train. is the satisfaction adjustment coefficient. is the distance adjustment coefficient. The values are all 0.5. If approaches , it indicates that the distance from the obstacle on this path is relatively stable and safe. The value of increases. When approaches , it means that the train can well meet the signal lamp requirements on this path. approaches , it means that the distance from the adjacent train is moderate and safe. The value of increases. When the running time of a reverse path is short and the safety is high, the comprehensive score of its reverse path will be relatively high, indicating that this reverse path is excellent in both time and safety. On the contrary, if the running time is long or the safety is low, the comprehensive score of the reverse path is relatively low, indicating that this reverse path is not an ideal choice for the reverse path. A path coordination unit is used to coordinate the path planning of each train during the collaborative reverse operation of multiple trains, avoid path conflicts, ensure the safe distance between trains. Through path coordination, path conflicts can be effectively avoided, and the overall operation efficiency and safety of the system can be improved. It collects the reverse path planning information of each train, including the current position, target position, current speed, planned path and estimated travel time of each train, and through vehicle-to-vehicle communication technology, it obtains the reverse path planning information of adjacent trains in real time. Based on the collected information, it analyzes the reverse paths of all trains to detect whether there are reverse path conflicts. Reverse path conflicts include, but are not limited to: multiple trains occupying the same track section simultaneously, conflicts in cross-track sections, etc. Furthermore, it records the detected conflict information, including the train numbers, conflict times, conflict locations, and conflict types of the conflicting trains. According to the urgency of the trains and task priority factors, it assigns priorities to each train. Emergency trains (rescue trains) or trains with high task priorities (first trains) have higher priorities. It formulates conflict resolution strategies and selects corresponding coordination schemes according to the priorities and conflict types. Coordination schemes include, but are not limited to: adjusting the train speed, changing the path, adjusting the departure time, etc., to ensure that the adjusted path can still meet the operation safety requirements of each train. According to the coordination scheme, it adjusts the reverse paths of each train, updates the reverse path planning information, ensures that the adjusted reverse path avoids the conflict points, and meets the operation safety and efficiency requirements. Furthermore, it feeds back the adjusted reverse path information to the local path planning units of each train, and through vehicle-to-vehicle communication technology, synchronizes the adjusted path information to adjacent trains to ensure coordinated operation. After the reverse path is adjusted, it continuously monitors the train operation status and further dynamically adjusts the reverse path according to real-time information; A digital twin simulation module is used to construct a virtual train model and an operation scenario library, simulate the multi-train collaborative reverse process, and verify the rationality of the path allocation and speed synchronization logic; A speed synchronization control module is used to adjust the speed of the train autonomously according to the local information of the train and the simulation results, and monitor the speed and acceleration data of each train to keep it coordinated with other trains to achieve speed synchronization, ensure that the trains maintain a consistent speed during the reverse process, and reduce the safety hazards caused by speed differences.

[0022] Embodiment 2, as Figure 1 、 2 shown. On the basis of Embodiment 1, the present invention provides a technical solution: Preferably, the digital twin simulation module includes a virtual train modeling unit and a collaborative reverse simulation unit; Among them, the virtual train modeling unit is used to build a virtual coupled train model including tracks, signal systems, trains, and control centers, map the operating states of physical trains in real time, collect the actual geometric data of the tracks, including physical parameters such as geometric shapes, lengths, gradients, and bend radii, obtain the topological structures of the tracks, including turnouts, intersections, and station positions, and collect information on the positions, types (inbound signal lights, outbound signal lights), and display states (red, yellow, green) of signal lights, obtain the control logics and operating rules of the signal systems, and then collect the physical parameters of trains, including lengths, widths, heights, weights, maximum speeds, accelerations, decelerations, etc., obtain the dynamic characteristics of trains, including tractive forces, braking forces, turning radii, etc., synchronously collect the dispatching plans, operation diagrams, and emergency handling plan information of the reverse control center, digitally convert the various types of information collected, form a standardized data format, build a virtual track model according to the collected track information, including the geometric shapes, topological structures, etc. of the tracks, build a virtual signal system model according to the signal system information, including the positions, types, display states, etc. of signal lights, build a virtual train model according to the train information, including the physical parameters, dynamic characteristics, etc. of trains, and build a virtual control center model according to the information of the reverse control center, including dispatching plans, operation diagrams, etc., and then integrate the virtual models of tracks, signal systems, trains, and reverse control centers to form a complete virtual coupled train model, obtain the operating state information of physical trains in real time through sensors and communication technologies, map the real-time obtained physical train state information into the virtual coupled train model, update the operating state of the virtual coupled train model, and dynamically update the operating state of the virtual coupled train model according to the real-time operating state information to ensure that the virtual coupled train model is always consistent with the physical system. When abnormal situations (faults, emergencies) in the system are detected, update the virtual coupled train model and trigger the corresponding early warning mechanism; A collaborative reverse simulation unit is used to simulate the multi-train collaborative reverse scenario by combining a preset operation scenario library and a virtual train model, verify the logical rationality of path allocation and speed synchronization. Through collaborative reverse simulation, the rationality of the collaborative reverse process can be verified in a virtual environment, potential problems can be discovered and solved in advance, and the multi-train collaborative reverse requirements under different operation conditions can be collected in advance, including peak hours, off-peak hours, and special weather operation conditions. During peak hours, the passenger flow is large and the train departure interval is short. During off-peak hours, the passenger flow is stable and the train operation rhythm is relatively loose. Special weather such as heavy rain and fog will interfere with the train operation speed and reverse interval. Based on this, a preset operation scenario library is set up. According to actual needs, an operation scenario that meets the current simulation requirements is selected from the preset operation scenario library. At the same time, a constructed virtual coupled train model is loaded, including detailed information such as tracks, signal systems, trains, and control centers. An initial setting is performed on the loaded operation scenario and virtual coupled train model, including setting the start time of the simulation, the initial positions and states of each train, to ensure that the simulation environment meets the preset requirements. After completing the loading preparation of the operation scenario and virtual coupled train model, start the collaborative reverse simulation. According to the preset path allocation and speed synchronization logic, simulate the collaborative reverse process of multiple trains in a virtual environment. During the simulation process, follow the control rules of the signal system and the dynamic characteristics of the trains, and record the key data of the running trajectories, speed changes, and position information of each train in real time. Through data monitoring and analysis, ensure that the operations between trains are coordinated with each other, avoid problems such as collisions and path conflicts, and ensure the smooth progress of the simulation process. After the simulation is over, analyze the data recorded during the collaborative reverse process, verify the logical rationality of path allocation and speed synchronization, and check whether the trains run according to the predetermined path, whether the speed reaches the synchronization requirements, and whether the key indicators of safety distance are met. If there are logical irrationalities, such as the risk of path conflicts and low operation efficiency caused by speed asynchronization, record the scenarios, times, and relevant train information where the problems occur, make adjustments and optimizations, and perform simulation verification again until the logic of path allocation and speed synchronization is completely reasonable, ensuring that potential problems are discovered and solved in advance in a virtual environment, and improving the safety and efficiency of multi-train collaborative reverse; The speed synchronization control module specifically includes: Continuously monitor the operating status of each train to obtain the speed and acceleration data of the train in real time. At the same time, through the communication interface between the train and the system, collect the local information of the train, and obtain the simulation data from the digital twin simulation module, including the key parameters such as the speed and safety distance of the train under the ideal operating state. Integrate the monitored real-time operating data of the train with the simulation results provided by the simulation unit to construct a comprehensive train operating status information database. Based on the integrated train operating status information, compare the actual speed of each train with the ideal speed in the simulation results, calculate the difference between each train and the ideal speed, and combine the dynamic characteristics of the train to formulate a targeted speed adjustment plan. For trains with a speed lower than the ideal value, consider appropriate acceleration, and for trains with a speed higher than the ideal value, arrange deceleration. When formulating the plan, comprehensively consider the smoothness of train operation and the safety distance factor to ensure that the adjustment plan can achieve speed synchronization and minimize energy consumption to the greatest extent, ensuring the efficiency and economy of train operation. According to the formulated speed adjustment plan, send speed adjustment instructions to the relevant trains through the communication system. During the execution of the instructions, continuously monitor the response of the train to the adjustment instructions, and collect the feedback data of the train speed and acceleration in real time. Compare and analyze the feedback data with the expected adjustment effect. If it is found that the train does not adjust its speed as expected, or there is still a speed difference after adjustment, correct the speed adjustment instructions, and optimize the speed adjustment strategy according to the feedback information. Through cyclic adjustment and optimization, ensure that all trains finally achieve speed synchronization, improve the operating performance and safety of the entire train system, and ensure the efficient and stable operation of the train during the return process.

[0023] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should be covered by the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claimed rights.

Claims

1. A reverse control system based on the formation of a virtual coupled train, including a reverse control center, characterized in that: The reverse control center is communicatively connected to the following modules, where: The local information perception module is used to obtain the environmental perception information around the train through on-vehicle multi-source sensors and vehicle-to-vehicle communication technology; The distributed path planning module is used to calculate the optimal path according to the environmental perception information of each train and coordinate the path planning of each train; The digital twin simulation module is used to construct a virtual train model and an operation scenario library, simulate the multi-vehicle collaborative reverse process, and verify the rationality of the path allocation and speed synchronization logic; The speed synchronization control module is used to autonomously adjust the speed of the train according to the local information of the train and the simulation results, and monitor the speed and acceleration data of each train to keep it coordinated with other trains.

2. The reverse control system based on the formation of a virtual coupled train according to claim 1, characterized in that: The local information perception module specifically includes: Deploy on-vehicle multi-source sensors on the train. Each on-vehicle multi-source sensor collects the environmental information around the train in real time according to the preset sampling frequency. At the same time, through vehicle-to-vehicle communication technology, it receives the operation status information sent by adjacent trains; Preprocess the sensor data collected by the on-vehicle multi-source sensors and the vehicle-to-vehicle communication data, including data cleaning, noise filtering, and format unification, and use a multi-source information fusion algorithm to fuse the preprocessed sensor data and vehicle-to-vehicle communication data to form complete environmental perception information. Furthermore, integrate the fused data into a unified data packet and transmit the data packet to the database of the reverse control center through the train communication network for storage.

3. The reverse control system based on the formation of a virtual coupled train set according to claim 1, wherein: The distributed path planning module includes a local path planning unit and a path coordination unit; Among them, the local path planning unit is used to autonomously calculate the optimal reverse path according to the environmental perception information of each train; The path coordination unit is used to coordinate the path planning of each train when multiple trains collaborate in reverse.

4. A reverse control system based on a virtual coupled train formation according to claim 3, characterized in that: The local path planning unit specifically includes: Obtain the environmental perception information around the train from the local information perception module, including the environmental information around the train and the operation status information sent by adjacent trains, and according to the current position, target position of the train and the requirements of the reverse task, set the goal of path planning as the shortest driving time, determine the constraints of path planning, and then construct a dynamic model of the train's surrounding environment according to the environmental perception information around the train, including the track topology structure, obstacle positions, signal light states, and the positions and movement trends of adjacent trains; Select the Dijkstra algorithm as the path planning algorithm, model the track network as a graph structure, where nodes represent key positions, edges represent track segments, and the weight is the time for the train to pass through this section of the track, and set the algorithm parameters according to the dynamic characteristics and environmental constraints of the train. Among them, the dynamic characteristics of the train are the maximum acceleration, maximum deceleration, and turning radius limit, and the environmental constraints are signal light limit and obstacle avoidance; Input the dynamic model of the train's surrounding environment, the current position of the train, and the position of the target reverse point into the Dijkstra algorithm, and calculate multiple feasible reverse paths according to the track topology structure and environmental constraints; Calculate the total driving time of each reverse path, and then calculate the comprehensive score of the reverse path according to the driving time and safety, and select the path with the highest comprehensive score of the reverse path as the optimal reverse path.

5. The reversing control system based on the formation of a virtual coupled train according to claim 4, characterized in that: The calculation process of the comprehensive score of the return path is as follows: For each candidate path, according to the track section length and train speed limit, calculate the total running time of the train passing through this path, find the minimum running time and average running time among all paths, calculate the average speed of the train on this path, and at the same time obtain the maximum allowable speed of the train on this path; Calculate the ratio of the minimum running time to the total running time to obtain the minimum running time ratio function, calculate the ratio of the average running time to the total running time, add 1 and take the logarithmic function to obtain the average running time ratio function, then calculate the ratio of the average speed to the maximum allowable speed, multiply by the speed utilization adjustment coefficient to obtain the speed ratio function, and then multiply the minimum running time ratio function by the average running time ratio function, add the speed ratio function to obtain the running time score; For each candidate path, analyze its relative position and distance change with respect to obstacles, determine the minimum safety distance and average safety distance from obstacles, and according to the signal light position and status, evaluate whether the train meets the signal light requirements on this candidate path, calculate the degree of meeting the signal light requirements, determine the maximum satisfaction of the signal light requirements, and then combine the operation status information of adjacent trains to calculate the minimum safety distance and average safety distance from adjacent trains; Calculate the ratio of the minimum safety distance to the average safety distance to obtain the minimum safety distance ratio function, calculate the ratio of the average safety distance to the minimum safety distance, add 1 and take the logarithmic function to obtain the average safety distance ratio function, then calculate the ratio of the degree of meeting the signal light requirements to the maximum satisfaction of the signal light requirements, multiply by the satisfaction adjustment coefficient to obtain the satisfaction ratio function, and at the same time calculate the ratio of the minimum safety distance to the average safety distance, multiply by the distance adjustment coefficient to obtain the distance ratio function, and then multiply the minimum safety distance ratio function by the average safety distance ratio function, add the satisfaction ratio function and the distance ratio function to obtain the safety score; According to the local path planning requirements, determine the running time score and safety score respectively, and calculate the weighted sum of the running time score and safety score to obtain the comprehensive score of the return path.

6. A reverse control system based on a virtual coupled train formation according to claim 4, characterized in that: The path coordination unit specifically includes: Collect the return path planning information of each train, including the current position, target position, current speed, planned path and estimated running time of each train, and through vehicle-to-vehicle communication technology, obtain the return path planning information of adjacent trains in real time. Based on the collected information, analyze the return paths of all trains, detect whether there are return path conflicts, and then record the detected conflict information; Assign priorities to each train according to factors such as the urgency and task priority of the train, formulate conflict resolution strategies, and select corresponding coordination schemes according to the priorities and conflict types; According to the coordination plan, the reverse paths of each train are adjusted, the reverse path planning information is updated, and then the adjusted reverse path information is fed back to the local path planning unit of each train. Through vehicle-to-vehicle communication technology, the adjusted path information is synchronized to adjacent trains. After the reverse path is adjusted, the running status of the trains is continuously monitored, and the reverse path is further dynamically adjusted according to the real-time information.

7. A reverse control system based on a virtual coupled train formation according to claim 1, characterized in that: The digital twin simulation module includes a virtual train modeling unit and a collaborative reverse simulation unit; Among them, the virtual train modeling unit is used to construct a virtual coupled train model including tracks, signal systems, trains, and control centers, and map the running status of physical trains in real time; The collaborative reverse simulation unit is used to combine the preset operation scenario library and the virtual train model to simulate the multi-train collaborative reverse scenario and verify the logical rationality of path allocation and speed synchronization.

8. A reverse control system based on a virtual coupled train formation according to claim 7, characterized in that: The virtual train modeling unit specifically includes: Collect the actual geometric data of the tracks, including physical parameters such as geometric shape, length, gradient, and curve radius, obtain the topological structure of the tracks, including turnouts, intersections, and station locations, and collect information on the position, type, and display status of signal lights, obtain the control logic and operation rules of the signal system, and then collect the physical parameters of the trains, obtain the dynamic characteristics of the trains, synchronously collect the dispatching plans, operation diagrams, and emergency handling plan information of the reverse control center, and perform digital conversion on the collected various types of information to form a standardized data format; According to the collected track information, construct a virtual track model, according to the signal system information, construct a virtual signal system model, according to the train information, construct a virtual train model, and according to the information of the reverse control center, construct a virtual control center model, and then integrate the virtual models of the tracks, signal systems, trains, and reverse control centers to form a complete virtual coupled train model; Through sensors and communication technology, obtain the running status information of physical trains in real time, map the real-time obtained physical train status information to the virtual coupled train model, update the running status of the virtual coupled train model, and dynamically update the running status of the virtual coupled train model according to the real-time running status information. When an abnormal situation in the system is detected, update the virtual coupled train model and trigger the corresponding warning mechanism.

9. The reversing control system based on the formation of a virtual coupled train according to claim 8, wherein: The collaborative reverse simulation unit specifically includes: Pre-collect the multi-train collaborative reverse requirements under different operation conditions, including peak hours, off-peak hours, and special weather operation conditions, and accordingly preset an operation scenario library. According to the actual requirements, select the operation scenario that meets the current simulation requirements from the preset operation scenario library. At the same time, load the constructed virtual coupled train model and perform initialization settings on the loaded operation scenario and virtual coupled train model, including setting the start time of the simulation, the initial positions and states of each train; After completing the loading preparation of the operation scenario and the virtual coupled train model, start the collaborative reverse simulation. According to the preset path allocation and speed synchronization logic, simulate the collaborative reverse process of multiple trains in the virtual environment. During the simulation process, record the key data of the running trajectories, speed changes, and position information of each train in real time; After the simulation is completed, analyze the data recorded during the collaborative reverse journey, verify the logical rationality of path allocation and speed synchronization, check whether the trains are running along the predetermined paths, whether their speeds meet the synchronization requirements, and whether they meet the key indicators of safety distances. If there are any illogical issues, record the scenarios, times, and relevant train information where the problems occur, make adjustments and optimizations, and conduct the simulation verification again until the logic of path allocation and speed synchronization is completely reasonable, ensuring that potential problems are discovered and solved in advance in the virtual environment and improving the safety and efficiency of multi-train collaborative reverse journeys.

10. A reverse control system based on a virtual coupled train formation according to claim 1, characterized in that: The speed synchronization control module specifically includes: Continuously monitor the operating status of each train, obtain the speed and acceleration data of the train in real time. At the same time, collect the local information of the train through the communication interface between the train and the system, and obtain the simulation data from the digital twin simulation module. Integrate the monitored real-time operating data of the train with the simulation results provided by the simulation unit to construct a comprehensive train operating status information database; Based on the integrated train operating status information, compare the actual speed of each train with the ideal speed in the simulation results, calculate the difference between each train and the ideal speed, and formulate targeted speed adjustment plans in combination with the dynamic characteristics of the train; According to the formulated speed adjustment plan, send speed adjustment instructions to the relevant trains through the communication system. During the execution of the instructions, continuously monitor the response of the trains to the adjustment instructions, collect the feedback data of the train speed and acceleration in real time, and compare and analyze the feedback data with the expected adjustment effects. If it is found that the trains do not adjust their speeds as expected, or there are still speed differences after adjustment, correct the speed adjustment instructions and optimize the speed adjustment strategy according to the feedback information.

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