Virtual connection method based on cloud-edge-end collaborative CBTC system

Abstract

The present invention provides a virtual coupling method based on a cloud-edge-end collaborative CBTC system, which relates to the field of rail transit technology. The cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle controller of each edge cloud server; the central cloud platform issues a virtual coupling instruction to each edge cloud server corresponding to the train to be coupled; each edge cloud server obtains the line data corresponding to the vehicle of each vehicle controller from the vehicle controller corresponding to the number of the train to be coupled in response to the virtual coupling instruction, including the speed information and position information corresponding to the vehicle, and determines the control strategy corresponding to the vehicle of each vehicle controller based on the line data corresponding to the vehicle of each vehicle controller; sends the control strategy corresponding to the vehicle of each vehicle controller to the corresponding vehicle controller; each vehicle controller performs virtual coupling based on the control strategy. The present invention effectively ensures driving safety.

Description

Technical Field

[0001] The present invention relates to the field of rail transit technology, and in particular to a virtual coupling method based on a cloud-edge-end collaborative CBTC system. Background Art

[0002] Virtual coupling is a train-centric control technology that connects trains through communication. They travel along the same route, at the same speed, and in the same direction, and the trains should maintain the same braking characteristics with each other, taking into account communication delays. Virtual coupling is considered to be the next generation of signal control technology that can increase rail transit volume.

[0003] In the prior art, the implementation of virtual coupling technology relies on vehicle-to-vehicle communication to obtain train operation information. When it is determined that the speed of the train ahead is less than the preset speed based on the train operation information, it is determined whether the virtual coupling condition is met based on the train operation information. The virtual coupling condition is that the overlapping operation interval between itself and the train ahead is greater than the preset length. If so, a virtual coupling is established with the train ahead and the on-board automatic protection equipment is bypassed. The train runs at the maximum speed limit of the current section until the distance between itself and the train ahead is reduced to the virtual coupling cooperative control distance so that it can be controlled by the train ahead. That is, wireless communication is used instead of mechanical coupling to enable the rear vehicle to obtain the operating status of the front vehicle, so as to achieve real-time and rapid reconnection or disassembly of trains of the same or different models during operation.

[0004] However, in the existing solution, the automatic protection system of the rear vehicle is bypassed after the virtual coupling, and the rear vehicle is completely controlled by the front vehicle. But in actual conditions, the traction and braking performance of different trains are not the same, and the rear vehicle is completely controlled by the front vehicle, which poses a safety hazard. Summary of the invention

[0005] The present invention provides a virtual coupling method based on a cloud-edge-end collaborative CBTC system, which is used to solve the defect in the prior art that the rear vehicle is completely controlled by the front vehicle, resulting in safety hazards, thereby ensuring driving safety.

[0006] In a first aspect, the present invention provides a cloud-edge-end collaborative CBTC system, the cloud-edge-end collaborative CBTC system comprising a central cloud platform, at least one edge cloud server, and a vehicle controller corresponding to each edge cloud server; wherein:

[0007] The central cloud platform is used to issue a virtual coupling instruction to each edge cloud server corresponding to the train to be coupled; the virtual coupling instruction includes the number of the train to be coupled;

[0008] Each of the edge cloud servers is used to respond to the virtual coupling instruction and obtain the route data corresponding to the vehicle of each onboard controller from the onboard controller corresponding to the number of the train to be coupled; the route data includes speed information and position information corresponding to each of the vehicles;

[0009] Based on the line data corresponding to the vehicles of each on-board controller, a control strategy corresponding to the vehicles of each on-board controller is determined; the control strategy includes movement authorization information, emergency braking speed limit and train recommended speed, and the movement authorization information is used to characterize the maximum range of safe operation of the train;

[0010] Sending the control strategy corresponding to the vehicle of each on-board controller to the corresponding on-board controller;

[0011] Each of the vehicle-mounted controllers is used to perform virtual coupling based on the corresponding control strategy.

[0012] According to a cloud-edge-end collaborative CBTC system provided by the present invention, the control strategy includes mobile authorization information, and the mobile authorization information is used to characterize the maximum range of safe operation of the train corresponding to the vehicle of each on-board controller; the speed information corresponding to each vehicle includes the speed corresponding to the preceding vehicle of each vehicle and the deceleration corresponding to the preceding vehicle of each vehicle; the position information of each vehicle includes the distance between each vehicle and the preceding vehicle of each vehicle, and the line data also includes the transmission delay;

[0013] The determining of the control strategy corresponding to the vehicle of each onboard controller based on the route data corresponding to the vehicle of each onboard controller comprises:

[0014] For any vehicle of the on-board controller, determining a speed-based tracking distance of the vehicle in the virtual coupling based on the distance between the vehicle and the vehicle ahead of the vehicle, the speed corresponding to the vehicle ahead of the vehicle, the deceleration corresponding to the vehicle ahead of the vehicle, and the transmission delay;

[0015] The speed-based tracking distance of each of the vehicles is determined as the movement authorization information corresponding to the vehicle of each of the vehicle-mounted controllers.

[0016] According to a cloud-edge-end collaborative CBTC system provided by the present invention, the speed information corresponding to each of the vehicles also includes the current speed of each of the vehicles and the acceleration of each of the vehicles, and the position information of each of the vehicles also includes the distance between each of the vehicles and the speed limit point; the control strategy also includes a target emergency braking speed limit, and the target emergency braking speed limit is used to represent the maximum speed limit for the on-board controller to control the vehicle emergency braking;

[0017] The determining of the control strategy corresponding to the vehicle of each onboard controller based on the route data corresponding to the vehicle of each onboard controller comprises:

[0018] Determine all speed limit points within the range of the train to the line terminal;

[0019] For any of the speed limit points, determining the first emergency braking speed limit corresponding to the vehicle of each of the onboard controllers at the speed limit point according to the current speed of each of the vehicles, the acceleration of each of the vehicles, and the distance between each of the vehicles and the speed limit point;

[0020] The minimum value among the first emergency braking speed limits corresponding to the vehicles of the vehicle-mounted controllers at the speed limit points is determined as the target emergency braking speed limit corresponding to the vehicles of the vehicle-mounted controllers.

[0021] According to a cloud-edge-device collaborative CBTC system provided by the present invention, the control strategy further includes a target recommended speed, and the target recommended speed is used to characterize the speed at which the on-board controller controls the vehicle to travel;

[0022] The determining of the control strategy corresponding to the vehicle of each onboard controller based on the route data corresponding to the vehicle of each onboard controller comprises:

[0023] For any speed limit point, determining a first recommended speed corresponding to the speed limit point for the vehicle of each onboard controller according to the current speed of each vehicle, the acceleration of each vehicle, and the distance between each vehicle and the speed limit point;

[0024] Compare the first recommended speed corresponding to the vehicle of each on-board controller at the speed limit point with the target emergency braking speed limit corresponding to the vehicle of each on-board controller to obtain a first comparison result, and determine the second recommended speed corresponding to the vehicle of each on-board controller at the speed limit point based on the first comparison result;

[0025] According to the preset station-to-station operation grade table, query and obtain the third recommended speed corresponding to the vehicle of each onboard controller at the speed limit point;

[0026] Compare each of the third recommended speeds with each of the second recommended speeds to obtain a second comparison result, and determine a target recommended speed corresponding to the vehicle of each of the onboard controllers at the speed limit point based on the second comparison result;

[0027] The target recommended speed corresponding to the vehicle of each on-board controller at the speed limit point is determined as the control strategy corresponding to the vehicle of each on-board controller.

[0028] According to a cloud-edge-device collaborative CBTC system provided by the present invention, each edge cloud server is further used for:

[0029] The emergency braking distance corresponding to each of the vehicles is determined based on the speed of each of the vehicles when the train braking begins, the speed of each of the vehicles when the train braking ends, the friction coefficient between the tracks, and the inclination of the road surface relative to the horizontal plane.

[0030] According to a cloud-edge-device collaborative CBTC system provided by the present invention, each edge cloud server is further used for:

[0031] According to the position information corresponding to the train set in the virtual coupling and the position information of the plurality of switches, the updated movement authorization information of the tail train in the train set in the virtual coupling is determined.

[0032] In a second aspect, the present invention further provides a virtual connection method based on a cloud-edge-end collaborative CBTC system, which is applied to an edge cloud server in the cloud-edge-end collaborative CBTC system, wherein the cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle-mounted controller corresponding to each edge cloud server; the method includes:

[0033] For any of the edge cloud servers, in response to the virtual coupling instruction, the line data corresponding to the vehicles of each on-board controller is obtained from the on-board controller corresponding to the number of the train to be coupled; the line data includes the speed information and position information corresponding to the vehicles of each on-board controller; the virtual coupling instruction is issued by the central cloud platform to each edge cloud server corresponding to the train to be coupled; the virtual coupling instruction includes the number of the train to be coupled;

[0034] Determining the control strategy corresponding to the vehicle of each onboard controller based on the route data corresponding to the vehicle of each onboard controller;

[0035] The control strategy corresponding to the vehicle of each on-board controller is sent to the corresponding on-board controller; the control strategy corresponding to the vehicle of each on-board controller is used for each on-board controller to perform virtual coupling operations based on the control strategy corresponding to the vehicle of each on-board controller.

[0036] In a third aspect, the present invention further provides a virtual coupling device based on a cloud-edge-end collaborative CBTC system, which is applied to an edge cloud server in the cloud-edge-end collaborative CBTC system, wherein the cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle-mounted controller corresponding to each edge cloud server; the device includes the following modules:

[0037] A data acquisition module is used for obtaining, for any of the edge cloud servers, line data corresponding to the vehicles of each onboard controller from the onboard controller corresponding to the number of the train to be coupled in response to the virtual coupling instruction; the line data includes speed information and position information corresponding to the vehicles of each onboard controller; the virtual coupling instruction is issued by the central cloud platform to each edge cloud server corresponding to the train to be coupled; the virtual coupling instruction includes the number of the train to be coupled;

[0038] A strategy determination module, used to determine the control strategy corresponding to the vehicle of each on-board controller based on the route data corresponding to the vehicle of each on-board controller;

[0039] A sending module is used to send the control strategy corresponding to the vehicle of each on-board controller to the corresponding on-board controller; the control strategy corresponding to the vehicle of each on-board controller is used for each on-board controller to perform virtual coupling operations based on the control strategy corresponding to the vehicle of each on-board controller.

[0040] In a fourth aspect, the present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the virtual connection method based on the cloud-edge-end collaborative CBTC system as described in any one of the above-mentioned methods is implemented.

[0041] In a fifth aspect, the present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it implements the virtual connection method based on the cloud-edge-end collaborative CBTC system as described in any of the above-mentioned methods.

[0042] In a sixth aspect, the present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements a virtual connection method based on a cloud-edge-end collaborative CBTC system as described in any one of the above-mentioned methods.

[0043] The present invention provides a virtual coupling method based on a cloud-edge-end collaborative CBTC system, wherein the cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle-mounted controller corresponding to each edge cloud server; wherein the central cloud platform is used to issue a virtual coupling instruction to each edge cloud server corresponding to a train to be coupled, the virtual coupling instruction including the number of the train to be coupled; each edge cloud server is used to respond to the virtual coupling instruction and obtain line data corresponding to the vehicle of each vehicle-mounted controller from the vehicle-mounted controller corresponding to the number of the train to be coupled; based on the line data corresponding to the vehicle of each vehicle-mounted controller, determine the control strategy corresponding to the vehicle of each vehicle-mounted controller; send the control strategy corresponding to the vehicle of each vehicle-mounted controller to the corresponding vehicle-mounted controller; each vehicle-mounted controller is used to perform virtual coupling based on the corresponding control strategy.

[0044] The cloud-edge-end collaborative CBTC system in the present invention includes a central cloud platform, at least one edge cloud server, and a vehicle controller corresponding to each edge cloud server. The central cloud platform issues a virtual coupling instruction. The edge cloud server first obtains the line data corresponding to the vehicle of each vehicle controller from the vehicle controller corresponding to the number of the train to be coupled based on the virtual coupling instruction. The edge cloud server then determines the control strategy corresponding to the vehicle of each vehicle controller based on the line data corresponding to the vehicle of each vehicle controller, and sends each control strategy to the corresponding vehicle controller. The present invention realizes virtual coupling through a cloud-edge-end collaborative CBTC system with a new architecture, and uses cloud-edge-end collaborative technology to control the tracking interval of the head and tail trains in real time, effectively ensuring driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 It is a structural diagram of the cloud-edge-end collaborative CBTC system provided by the present invention.

[0047] Figure 2 This is an architecture diagram of the vehicle-mounted software provided by the present invention.

[0048] Figure 3 An architectural diagram of the edge cloud service software provided by the present invention.

[0049] Figure 4 An architectural diagram of the central cloud monitoring software provided by the present invention.

[0050] Figure 5 It is a schematic diagram of speed-based train tracking provided by the present invention.

[0051] Figure 6 It is a force diagram of the train emergency braking provided by the present invention.

[0052] Figure 7 It is a schematic diagram of the principle of cloud-edge-end coordinated turnout control provided by the present invention.

[0053] Figure 8 It is a flow chart of the virtual connection method based on the cloud-edge-end collaborative CBTC system provided by the present invention.

[0054] Fig. 9 It is a schematic diagram of the principle of the virtual connection method based on the cloud-edge-end collaborative CBTC system provided by the present invention.

[0055] Fig.10 It is a structural schematic diagram of the virtual coupling device based on the cloud-edge-end collaborative CBTC system provided by the present invention.

[0056] Fig.11 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] Combine the following Figure 1-Figure 11 The present invention describes the virtual connection method based on the cloud-edge-end collaborative CBTC system.

[0059] Figure 1 : is a schematic diagram of the structure of the cloud-edge-end collaborative CBTC system provided by the present invention, such as Figure 1 As shown, the cloud-edge-end collaborative communication-based train automatic control system (CBTC) system includes a central cloud platform, at least one edge cloud server, and a vehicle controller corresponding to each edge cloud server; wherein,

[0060] The central cloud platform is used to issue a virtual coupling instruction to each edge cloud server corresponding to the train to be coupled; the virtual coupling instruction includes the number of the train to be coupled;

[0061] Each of the edge cloud servers is used to respond to the virtual coupling instruction and obtain the route data corresponding to the vehicle of each onboard controller from the onboard controller corresponding to the number of the train to be coupled; the route data includes speed information and position information corresponding to each of the vehicles;

[0062] Determining the control strategy corresponding to the vehicle of each onboard controller based on the route data corresponding to the vehicle of each onboard controller;

[0063] Sending the control strategy corresponding to the vehicle of each on-board controller to the corresponding on-board controller;

[0064] Each of the vehicle-mounted controllers is used to perform virtual coupling based on the corresponding control strategy.

[0065] Specifically, the overall design architecture of the CBTC system based on cloud-edge-end collaboration is a combination of front-end, edge and center cloud, that is, cloud-edge-end collaboration. The system includes a cloud-center cloud platform, an edge-edge cloud server and a terminal-vehicle controller.

[0066] The on-board controller is installed on the train to realize the information collection and control functions of the train. It mainly includes the main control module, communication module, input module, output module and power module. The main control module is the core module of the on-board controller, which has the functions of power-on self-test, periodic self-test, clock synchronization, data synchronization, etc. The communication module realizes the external transmission and reception of data and ensures data security. The input module has the function of collecting digital quantities, periodically and dynamically collecting external digital quantity inputs, and sends the collection results to the main control module. If the dynamic collection is abnormal, the channel is faulty and the fault information is reported. The output module has the function of digital quantity output, generates corresponding output according to the software instructions, and has the function of output status collection. If the output status is found to be inconsistent with the software instructions, the channel is faulty and the fault information is reported.

[0067] The edge cloud server includes a data exchange module, a data processing module, and a data analysis module. The data exchange module has the function of exchanging data with the vehicle controller and the central cloud server, and ensures data security. The data analysis module analyzes the collected vehicle controller parameters and line data. The data processing module processes and calculates the vehicle control parameters based on the data obtained by the data exchange module, the analysis results of the data analysis module, and the queried line data, and sends the control strategy to the vehicle controller.

[0068] The central cloud platform includes a data exchange module, a data storage module, a data mining module and a monitoring module. The data exchange module is responsible for exchanging data with the edge cloud server and collecting all front-end data and analysis results of the edge cloud server. The data storage module is responsible for storing the collected data, and the data mining module extracts and cleans the stored data and analyzes and processes the data. The monitoring module can display the operation and maintenance data of all vehicle-mounted and edge devices, and can issue control instructions.

[0069] For example, Figure 2 is the architecture diagram of the vehicle-mounted software provided by the present invention, such as Figure 2As shown in the figure, the interface component receives the network data sent by the edge cloud server, the behavior component forms the train control command according to the received data, the maintenance component provides operation and maintenance functions, the exception handling component ensures that the software is directed to the safety side when the application software runs abnormally, the log component provides the function of recording the application software log, and the public component provides basic public functions for other components. Different from the on-board subsystem of the traditional CBTC system, the application software of the on-board controller described in this paper only retains the related functions of self-test, data transmission and reception, and direct control of the train, including power-on self-test, emergency braking, traction, common braking, holding braking, door control, etc. The logic processing and parameter calculation are completed by the edge cloud server and the central cloud, and the results are sent to the on-board software for execution.

[0070] Figure 3 The architecture diagram of the edge cloud service software provided by the present invention is as follows: Figure 3 As shown in the figure, the data service layer is an important support for the application layer, providing basic configuration services, authorization and authentication services, log services, event services, network management services, data security services and alarm services, and realizing data collection, transmission and storage together with relational databases, real-time databases and caches. The query component in the application layer queries line data and provides data support for the calculation component and the analysis component. The calculation component calculates the train movement authorization, emergency braking speed limit and recommended speed according to the operation instructions issued by the central cloud platform, the queried line data, the trackside equipment status information, the train information uploaded by the on-board controller and the analysis results of the analysis component. The analysis component analyzes the current running status of the train according to the operation instructions issued by the central cloud platform and the train information uploaded by the on-board controller, and uses the results as the calculation basis of the calculation component. The main algorithms used include linear regression and logistic regression in regression analysis, decision tree, random forest, k nearest neighbor algorithm in classification algorithm, k mean clustering, hierarchical clustering in clustering algorithm, principal component analysis (PCA) in dimensionality reduction algorithm, ARIMA model and exponential smoothing method in time series analysis algorithm.

[0071] The edge cloud service software is deployed at the station, receiving real-time train position and speed information and trackside status information, as well as operating instructions and temporary speed limits sent by the central cloud control system. It calculates and generates train movement authorization, emergency braking speed limits and recommended speeds, and adjusts the running intervals between trains in real time, greatly improving the traffic capacity of the section. At the same time, it transfers, stores and analyzes uplink and downlink data.

[0072] Figure 4 The architecture diagram of the central cloud monitoring software provided by the present invention is as follows: Figure 4As shown in the figure, the data service layer provides data support, the application layer performs business logic processing and data analysis and calculation, and the presentation layer provides a human-computer interaction interface to display the train information, equipment information, progress information, etc. of the entire line network on the corresponding terminal, and the operator inputs the operation and maintenance related instructions through the terminal. The central cloud monitoring software receives the uplink data in real time, stores and mines the uplink data, and sends down the control information after analysis and calculation. The monitoring software has multiple monitoring pages, which display the data after collection, analysis and mining. Through each monitoring page, the management personnel can easily grasp the train information and equipment status.

[0073] An example of the process of implementing virtual connection in this embodiment is as follows:

[0074] The central cloud platform is used to issue virtual coupling instructions to each edge cloud server corresponding to the train to be coupled, and the virtual coupling instruction includes the number of the train to be coupled. Each edge cloud server is used to respond to the virtual coupling instruction and obtain the line data corresponding to the vehicle of each on-board controller from the on-board controller corresponding to the number of the train to be coupled; for example, the line data includes the speed information and position information corresponding to each of the vehicles, as well as the status information of the trackside equipment; based on the line data corresponding to the vehicle of each on-board controller, determine the control strategy corresponding to the vehicle of each on-board controller; for example, the control strategy includes movement authorization information, emergency braking speed limit and recommended train speed, and the movement authorization information is used to characterize the maximum range of safe operation of the train; send the control strategy corresponding to the vehicle of each on-board controller to the corresponding on-board controller; each on-board controller is used to perform virtual coupling based on the corresponding control strategy.

[0075] In the cloud-edge-end collaborative CBTC system, each edge cloud server collects train information, calculates the recommended train speed, and controls the train tracking interval. The central cloud platform collects data from the edge cloud servers, which are stored and displayed after analysis and processing, and human-computer interaction and instructions are issued through the control terminal.

[0076] The system provided in this embodiment, the cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle-mounted controller corresponding to each edge cloud server; wherein the central cloud platform is used to issue a virtual coupling instruction to each edge cloud server corresponding to the train to be coupled, and the virtual coupling instruction includes the number of the train to be coupled; each edge cloud server is used to respond to the virtual coupling instruction, and obtain the line data corresponding to the vehicle of each on-board controller from the on-board controller corresponding to the number of the train to be coupled; based on the line data corresponding to the vehicle of each on-board controller, determine the control strategy corresponding to the vehicle of each on-board controller; send the control strategy corresponding to the vehicle of each on-board controller to the corresponding on-board controller; each on-board controller is used to perform virtual coupling based on the corresponding control strategy.

[0077] The cloud-edge-end collaborative CBTC system in the present invention includes a central cloud platform, at least one edge cloud server, and a vehicle controller corresponding to each edge cloud server. The central cloud platform issues a virtual coupling instruction. The edge cloud server first obtains the line data corresponding to the vehicle of each vehicle controller from the vehicle controller corresponding to the number of the train to be coupled based on the virtual coupling instruction. The edge cloud server then determines the control strategy corresponding to the vehicle of each vehicle controller based on the line data corresponding to the vehicle of each vehicle controller, and sends each control strategy to the corresponding vehicle controller. The present invention realizes virtual coupling through a cloud-edge-end collaborative CBTC system with a new architecture, and uses cloud-edge-end collaborative technology to control the tracking interval of the head and tail trains in real time, effectively ensuring driving safety.

[0078] According to a cloud-edge-end collaborative CBTC system provided by the present invention, the control strategy includes mobile authorization information, which is used to characterize the maximum range of safe operation of the train corresponding to the vehicle of each on-board controller; the speed information corresponding to each vehicle includes the speed corresponding to the preceding vehicle of each vehicle and the deceleration corresponding to the preceding vehicle of each vehicle; the position information of each vehicle includes the distance between each vehicle and the preceding vehicle of each vehicle, and the line data also includes the transmission delay;

[0079] Based on the route data corresponding to the vehicles of each on-board controller, the control strategy corresponding to the vehicles of each on-board controller is determined, including:

[0080] For any vehicle with a vehicle-mounted controller, the speed-based tracking distance of the vehicle in the virtual coupling is determined based on the distance between the vehicle and the vehicle in front of the vehicle, the speed corresponding to the vehicle in front of the vehicle, the deceleration corresponding to the vehicle in front of the vehicle, and the transmission delay;

[0081] The speed-based tracking distance of each vehicle is determined as the movement authorization information corresponding to the vehicle of each on-board controller.

[0082] Specifically, in some embodiments, the control strategy includes movement authorization information, emergency braking speed limit and recommended train speed. Among them, the movement authorization information is, for example, the maximum range of safe operation of the train, and the safe interval between trains needs to be maintained based on the movement authorization information. The movement authorization information of the edge cloud computing train, for example, considers the trackside equipment status reported by the interlocking (turnout, screen door, stop button, personnel protection switch SPKS, garage door), the route status information reported by the interlocking, the temporary speed limit information issued by the central cloud, the real-time position and status information of the train, the derailed train protection area, the interval evacuation protection area and the phase separation area and other factors. The calculated movement authorization information includes the following: movement authorization direction, stop guarantee request, movement authorization start / end position, protection section validity, turnout information and status, platform door status, emergency stop button status, unmanned return button status, temporary speed limit information, emergency braking command, operation destination attribute information, signal status, personnel protection switch SPKS information, garage door information. The edge cloud matches the route (the area where the train can enter) according to the train's safe position, expected direction and trackside status information reported by the interlocking. Matching the route requires checking that the route is in an established and processed state, the axle counting section in the route is in a locked state and the locking direction is consistent with the expected direction of the train, the switch position in the route is correct and locked, and the signal at the beginning of the route is open for passage. When all the above conditions are met, the route can be matched for the train, otherwise the route will not be matched for the train.

[0083] The route data corresponding to the vehicle of each on-board controller includes the distance between the vehicle and the vehicle in front of the vehicle, the speed corresponding to the vehicle in front, the deceleration corresponding to the vehicle in front, and the transmission delay. Correspondingly, the specific implementation process of determining the control strategy corresponding to the vehicle of each on-board controller in step 102 includes the following steps:

[0084] First, for any vehicle with an onboard controller, the speed-based tracking distance of the vehicle in the virtual coupling is determined based on the distance between the vehicle and the vehicle in front, the speed of the vehicle in front, the deceleration of the vehicle in front, and the transmission delay. The CBTC system based on cloud-edge-end collaboration uses the excellent cloud computing capabilities of the edge cloud server and the unified coordination capabilities of the central cloud. Under the collaborative control of the cloud-edge-end, based on position tracking, the distance that the vehicle in front brakes forward at the current speed is calculated to achieve virtual coupling. The specific principle is as follows: Figure 5 As shown, Figure 5 It is a schematic diagram of speed-based train tracking provided by the present invention.

[0085] For example, the following formula (1) is used to calculate the speed-based tracking distance of the vehicle in the virtual coupling:

[0086] S'=S+(v-at) 2 / 2a (1)

[0087] In formula (1), S' is the speed-based tracking distance in the virtual coupling, S is the position-based tracking distance, that is, the distance between the front vehicle and the current vehicle, v is the front vehicle speed, a is the deceleration, and t is the transmission delay.

[0088] Furthermore, the speed-based tracking distance of each vehicle is determined as the mobile authorization information corresponding to the vehicle of each on-board controller, and the mobile authorization information is used to characterize the maximum range of safe operation of the train corresponding to the vehicle of each on-board controller.

[0089] In the system provided by this embodiment, the edge cloud server determines the speed-based tracking distance of the vehicles in the virtual coupling based on the distance between the vehicle and the vehicle in front of the vehicle, the speed corresponding to the vehicle in front, the deceleration corresponding to the vehicle in front, and the transmission delay; then, the speed-based tracking distance of each vehicle is determined as the mobile authorization information corresponding to the vehicle of each on-board controller, wherein the mobile authorization information is used to characterize the maximum range of safe operation of the train corresponding to the vehicle of each on-board controller. In the present invention, the edge cloud server coordinates the position and speed of all trains, collects all train information in the area, adjusts the control strategy of each train in real time, compensates for the performance differences between trains, and effectively ensures driving safety.

[0090] According to a cloud-edge-end collaborative CBTC system provided by the present invention, the speed information corresponding to each vehicle also includes the current speed and acceleration of each vehicle, and the position information of each vehicle also includes the distance between each vehicle and the speed limit point; the control strategy also includes a target emergency braking speed limit, which is used to represent the maximum speed limit of the vehicle controller to control the emergency braking of the vehicle;

[0091] Based on the route data corresponding to the vehicles of each on-board controller, the control strategy corresponding to the vehicles of each on-board controller is determined, including:

[0092] Determine all speed limit points within the range of the train to the line terminal;

[0093] For any of the speed limit points, determining the first emergency braking speed limit corresponding to the vehicle at the speed limit point of each onboard controller according to the current speed of each vehicle, the acceleration of each vehicle, and the distance between each vehicle and the speed limit point;

[0094] The minimum value among the first emergency braking speed limits corresponding to the vehicles of each on-board controller at each speed limit point is determined as the target emergency braking speed limit corresponding to the vehicles of each on-board controller.

[0095] Specifically, in some embodiments, the control strategy also includes a target emergency braking speed limit, which is used to characterize the maximum speed limit for the on-board controller to control the vehicle's emergency braking. The calculation of the emergency braking speed limit needs to consider the following information: all speed limit points from the train head to the end of the authorized movement, the train position and uncertainty, the train length, the train formation, the speed measurement error of the on-board controller, the response time of the on-board controller, the communication delay between devices, the speed limit of the train itself, the maximum acceleration of the train, the guaranteed braking rate of the train, the line slope, the line speed limit, the temporary speed limit and obstacle information (including SPKS, garage doors, switches, screen doors, platform emergency buttons, etc.). When the on-board controller detects that the real-time speed of the train is greater than or equal to the emergency braking speed limit of the edge cloud computing, it will immediately output emergency braking to ensure the safety of the train.

[0096] Correspondingly, the specific implementation process of determining the control strategy in step 102 includes the following steps:

[0097] First, determine all speed limit points within the range from the train to the line terminal. For example, query all speed limit points within the range from the train to the MA terminal (including switches, platform doors, and temporary speed limit sections).

[0098] Furthermore, a first emergency braking speed limit corresponding to each speed limit point is calculated.

[0099] Specifically, for any speed limit point, the first emergency braking speed limit corresponding to the vehicle of each onboard controller at the speed limit point is determined according to the current speed of the vehicle of each onboard controller, the acceleration of the vehicle of each onboard controller, and the distance between the vehicle of each onboard controller and the speed limit point; for example, the first emergency braking speed limit corresponding to the vehicle at the speed limit point is calculated using the following formula (2):

[0100] (2)

[0101] Among them, the emergency braking speed limit at the speed limit point is , the current speed of the train is , the acceleration / deceleration of the train is , the distance between the vehicle and the speed limit point is .

[0102] The derivation process of formula (2) is as follows:

[0103] According to the safety braking model, the emergency braking speed limit is calculated to the speed limit point. In the uniform acceleration / deceleration motion, the two basic kinematic equations are:

[0104] (3)

[0105] (4)

[0106] From formula (3), we get:

[0107] (5)

[0108] Substituting formula (5) into formula (4), we get:

[0109] (6)

[0110] After simplification, we can get formula (2):

[0111] (2)

[0112] Furthermore, the minimum value of the first emergency braking speed limits corresponding to the speed limit points of the vehicles of each vehicle controller is determined as the target emergency braking speed limit corresponding to the vehicles of each vehicle controller. For example, the minimum value of the first emergency braking speed limits of all speed limit points is taken as the target emergency braking speed limit.

[0113] In the system provided by this embodiment, the edge cloud server first determines all speed limit points within the range from the train to the line terminal; then, for any speed limit point, the first emergency braking speed limit corresponding to the vehicle of each onboard controller at the speed limit point is determined according to the current speed of the vehicle of each onboard controller, the acceleration of the vehicle of each onboard controller, and the distance between the vehicle of each onboard controller and the speed limit point; the minimum value of the first emergency braking speed limit corresponding to the vehicle of each onboard controller at each speed limit point is determined as the target emergency braking speed limit corresponding to the vehicle of each onboard controller. In the present invention, the edge cloud server coordinates the position and speed of all trains, collects all train information in the area, adjusts the control strategy of each train in real time, compensates for the performance differences between trains, and effectively ensures driving safety.

[0114] According to a cloud-edge-device collaborative CBTC system provided by the present invention, the control strategy also includes a target recommended speed, which is used to characterize the speed at which the on-board controller controls the vehicle to travel;

[0115] Based on the route data corresponding to the vehicles of each on-board controller, the control strategy corresponding to the vehicles of each on-board controller is determined, including:

[0116] For any of the speed limit points, determining a first recommended speed corresponding to the vehicle at the speed limit point of each vehicle controller according to the current speed of each vehicle, the acceleration of each vehicle, and the distance between each vehicle and the speed limit point;

[0117] Compare the first recommended speed corresponding to the vehicle of each on-board controller at the speed limit point with the target emergency braking speed limit corresponding to the vehicle of each on-board controller to obtain a first comparison result, and determine the second recommended speed corresponding to the vehicle of each on-board controller at the speed limit point based on the first comparison result;

[0118] According to the preset station-to-station operation level table, query and obtain the third recommended speed corresponding to the vehicle at the speed limit point of each on-board controller;

[0119] Compare each third recommended speed with each second recommended speed to obtain a second comparison result, and determine a target recommended speed corresponding to the vehicle at the speed limit point of each onboard controller based on the second comparison result;

[0120] The target recommended speed corresponding to the vehicle of each on-board controller at the speed limit point is determined as the control strategy corresponding to the vehicle of each on-board controller.

[0121] Specifically, in some embodiments, the control strategy also includes a target recommended speed, which is used to characterize the speed at which the on-board controller controls the vehicle. Factors that need to be considered when the edge cloud server calculates the recommended speed include: emergency braking speed limit, inter-station running time, vehicle detent jump stop command, line slope, curvature, vehicle acceleration / deceleration performance, comfort, vehicle load, and energy saving. The edge cloud receives the interval operation level issued by the central cloud, and uses the speed corresponding to the interval operation level as the maximum recommended speed. After receiving the recommended speed from the edge cloud computing, the on-board controller drives the train at the recommended speed and completes the reasonable control of the train speed by outputting traction and braking commands to the vehicle.

[0122] Correspondingly, the specific implementation process of determining the control strategy corresponding to the vehicle of each onboard controller in step 102 includes the following steps:

[0123] First, for any speed limit point, the first recommended speed corresponding to the vehicle of each vehicle controller at the speed limit point is determined based on the current speed of the vehicle of each vehicle controller, the acceleration of the vehicle of each vehicle controller, and the distance between the vehicle of each vehicle controller and the speed limit point. Similar to the emergency braking speed limit, the specific process of the recommended speed calculation is as follows:

[0124] (7)

[0125] The recommended speed of the train is , the current speed of the train is , the acceleration / deceleration of the train is (If it is deceleration, it is a negative value), the distance from the speed limit point is .

[0126] Furthermore, the first recommended speed corresponding to the vehicle of each on-board controller at the speed limit point is compared with the target emergency braking speed limit corresponding to the vehicle of each on-board controller to obtain a first comparison result, and the second recommended speed corresponding to the vehicle of each on-board controller at the speed limit point is determined based on the first comparison result; the third recommended speed corresponding to the vehicle of each on-board controller at the speed limit point can also be obtained by querying according to the preset station-to-station operation level table.

[0127] Further, each third recommended speed is compared with each second recommended speed to obtain a second comparison result, and the target recommended speed corresponding to the vehicle at the speed limit point of each onboard controller is determined based on the second comparison result. Finally, the minimum value of all recommended speeds is taken as the final target recommended speed of the train.

[0128] Furthermore, the target recommended speed corresponding to the vehicle of each on-board controller at the speed limit point is determined as the control strategy corresponding to the vehicle of each on-board controller.

[0129] In the system provided by this embodiment, the edge cloud server calculates the target recommended speed of the train based on the line data. After the on-board controller receives the target recommended speed calculated by the edge cloud server, it drives the train at the recommended speed and outputs traction and braking commands to the vehicle to complete the reasonable control of the train speed, thereby effectively ensuring driving safety.

[0130] According to a cloud-edge-device collaborative CBTC system provided by the present invention, each edge cloud server is further used for:

[0131] The emergency braking distance corresponding to each vehicle is determined based on the speed of each vehicle when the train brakes, the speed of each vehicle when the train brakes, the friction coefficient between the tracks, and the inclination of the road surface relative to the horizontal plane.

[0132] Specifically, in some embodiments, the method further includes calculating the emergency braking distance of the vehicle at different speeds and slopes. An example of the calculation process is as follows:

[0133] The emergency braking distance corresponding to each vehicle is determined based on the speed of each vehicle when the train brakes, the speed of each vehicle when the train brakes, the friction coefficient between the tracks, and the inclination of the road surface relative to the horizontal plane.

[0134] For example, Figure 6 It is the force diagram of the train emergency braking provided by the present invention, such as Figure 6 As shown, C is the center of mass of the train, G is gravity, and the following is established: Figure 6 In the coordinate system shown in , the x-axis and y-axis are along the inclination direction of the road surface and perpendicular to the road surface respectively. Projecting each force along the two coordinate axes, we can get:

[0135] (8)

[0136] (9)

[0137] in, represents all the forces on the x-axis, represents all forces on the y-axis, to are the track support forces on the n wheels of the train, to are the track friction forces on the n wheels when the train brakes, and their magnitudes are to The coefficient of friction between the wheel and the track The product of It is the imaginary inertia force during braking, acting on the center of mass of the train and pointing in the forward direction. is the inclination of the road surface relative to the horizontal plane.

[0138] Numerically, the imaginary inertial force is:

[0139] (10)

[0140] In the formula, is the train mass, is the absolute value of acceleration during braking, and its sign has been considered here. It is assumed that the train moves at a constant deceleration during braking. Therefore, equation (8) becomes:

[0141] (11)

[0142] Note the relationship in formula (9):

[0143] (12)

[0144] After sorting:

[0145] (13)

[0146] The braking distance in the x direction is set to , and the speed of the train at the beginning and end of braking are and , from kinematics we know:

[0147] (14)

[0148] If the negative acceleration is taken into account and only its absolute value is used for calculation, the above formula can be rewritten as:

[0149] (15)

[0150] Substituting formula (13) into the equation, we get the expression of emergency braking distance:

[0151] (16)

[0152] is the emergency braking distance; the speed of the train at the beginning of braking is The speed of the train at the end of braking is , is the friction coefficient between the rails; is the inclination of the road surface relative to the horizontal plane; is the acceleration due to gravity.

[0153] In the system provided in this embodiment, the edge cloud server determines the emergency braking distance corresponding to each vehicle based on the speed of each vehicle at the beginning of train braking, the speed of each vehicle at the end of train braking, the friction coefficient between the tracks, and the inclination of the road surface relative to the horizontal plane, thereby effectively ensuring driving safety.

[0154] According to a cloud-edge-device collaborative CBTC system provided by the present invention, each edge cloud server is further used for:

[0155] According to the position information corresponding to the marshaling vehicles in the virtual coupling and the position information of the plurality of switches, the updated movement authorization information of the tail vehicle in the marshaling vehicles in the virtual coupling is determined.

[0156] Specifically, in some embodiments, the method also includes coordinating switch control through an edge cloud server to achieve independent control of the switch, and the state of the current switch will not be affected by whether other switches in the route are occupied.

[0157] According to the position information corresponding to the marshaling vehicles in the virtual coupling and the position information of the plurality of switches, the updated movement authorization information of the tail vehicle in the marshaling vehicles in the virtual coupling is determined.

[0158] Figure 7 Schematic diagram of the principle of cloud-edge-end coordinated turnout control provided by the present invention, such as Figure 7 As shown in the figure, the leading car in the virtual coupling is in a straight line, occupying the second turnout that the trailing car is going to pass. The trailing car applies for a lateral shortcut on the side of the turnout. The edge cloud server can open a lateral shortcut for the trailing car based on the position information of the leading and trailing cars, and calculate the movement authorization of the trailing car before the second turnout, so that the trailing car can pass through the first turnout. When the leading car leaves the second turnout, the edge cloud server extends the movement authorization of the trailing car through the second turnout, so that the trailing car can pass through the current turnout earlier when the approach to the turnout is not fully unlocked, thereby improving operation efficiency.

[0159] The system provided in this embodiment coordinates the switch control through the edge cloud server to achieve independent control of the switch, and the status of the current switch will not be affected by whether other switches in the route are occupied, thereby improving the operation efficiency.

[0160] During operation, when a single train formation cannot meet the transportation volume requirements, virtual coupling can be enabled to increase the transportation volume. The operator only needs to issue a virtual coupling instruction through the monitoring terminal of the central cloud platform. After receiving the instruction, the edge cloud server first finds the head and tail cars in the formation, and then automatically implements virtual coupling according to the position and speed of the head and tail trains in the current formation (this article only describes the virtual coupling of two trains).

[0161] 1) Station coupling. When the leading train is about to enter the platform or has not yet started during platform operations, the edge cloud server controls the leading train to wait at the platform by extending the stop time or sending a temporary stop command. The edge cloud server controls the tail train to stop at a certain distance from the tail of the leading train through train movement authorization. After the tail train stops steadily, the two trains start in a virtual coupling state.

[0162] 2) Section coupling. When the leading car is running in the section, the edge cloud server controls the leading car to run at a low and uniform speed by recommending a speed, and controls the tail car to run at a speed higher than the leading car, so that the interval between the two cars is gradually reduced, and the speed of the tail car gradually approaches the speed of the leading car when it approaches the leading car. The edge cloud server ensures through calculation that the two cars reach a virtual coupling state before the leading car enters the station parking process.

[0163] When the transport demand drops to a certain level, the operator sends an instruction to cancel the virtual coupling through the monitoring center of the central cloud platform. After receiving the instruction, the edge cloud server finds the head and tail cars in the formation, and then automatically de-marshals the train according to the current position of the train.

[0164] 1) Disassembly at the station. After the virtual coupled train stops at the station, the edge cloud server receives the command from the central cloud platform to disassemble the large train into a small train. The edge cloud server controls the rear train to continue to stop at the platform and not depart by timing the stop or sending a temporary stop command, and controls the front train to start. After the front train has started for a period of time, the rear train is controlled to start, ensuring that the front and rear trains maintain a sufficient distance to continue running.

[0165] 2) Section disassembly. When the virtually coupled trains are running in the section, the edge cloud server receives the command from the central cloud platform and disassembles the large train into a small train. First, the large train is controlled to reduce the running speed by reducing the recommended speed, and then the train is disassembled. After disassembly, the front train is controlled to increase the speed. After a period of time, the rear train is controlled to continue to run forward according to the operation plan to ensure that the front and rear trains maintain a sufficient distance.

[0166] The technical solution of the present invention has the following advantages:

[0167] 1) The on-board equipment is the most complex, the largest in number, and the most scattered among all the signal equipment on the entire line. This method can greatly reduce the complexity of the on-board equipment, thereby greatly reducing the manpower and material costs of construction and maintenance, as well as the probability of failure, making the entire signal system more stable and reliable;

[0168] 2) The limited space in the vehicle leads to a bottleneck in the performance of the on-board equipment, and thus there are great limitations on the communication between vehicles and the realization of the linkage function. However, this method uses cloud-edge-end collaboration, and a large amount of computing and collaborative work are completed in the edge cloud and the central cloud. The performance limitations of the edge cloud and the central cloud are very small, which can realize the linkage function of more vehicles and improve the performance of the entire system.

[0169] 3) Through the collaboration of cloud, edge and terminal, the present invention can achieve efficient co-movement of coupled vehicles in the switch area.

[0170] 4) The present invention uses cloud-edge-end collaborative control to virtually couple multiple trains without actual physical connection, thereby realizing the operation of large-scale trains, greatly improving the collaborative control capabilities between subsystems, making operations more flexible, and greatly shortening the operating intervals of trains.

[0171] Figure 8 : is a flow chart of a virtual connection method based on a cloud-edge-end collaborative CBTC system provided by the present invention, the method is applied to an edge cloud server in a cloud-edge-end collaborative CBTC system, the cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle controller corresponding to each edge cloud server; Figure 8 As shown, the method includes the following:

[0172] Step 801: For any edge cloud server, in response to a virtual coupling instruction, obtain the line data corresponding to the vehicles of each on-board controller from the on-board controller corresponding to the number of the train to be coupled; the line data includes the speed information and position information corresponding to the vehicles of each on-board controller; the virtual coupling instruction is issued by the central cloud platform to each edge cloud server corresponding to the train to be coupled; the virtual coupling instruction includes the number of the train to be coupled;

[0173] Specifically, it should be noted that the executor of this embodiment is the edge cloud server in the cloud-edge-end collaborative CBTC system, which is used to effectively ensure the driving safety in the virtual coupling.

[0174] like Figure 1As shown in the figure, the cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle controller corresponding to each edge cloud server. Specifically, the overall design architecture of the CBTC system based on cloud-edge-end collaboration is a combination of the front end, edge and central cloud, that is, cloud-edge-end collaboration. The system includes a cloud-central cloud platform, an edge-edge cloud server and a device-vehicle controller.

[0175] Fig. 9 Schematic diagram of the principle of the virtual connection method based on the cloud-edge-end collaborative CBTC system provided by the present invention, such as Fig. 9 As shown in the figure, the onboard controller periodically obtains the real-time speed, position and other information of the train, and uploads the information to the edge cloud server through the communication module. The edge cloud server collects the real-time information of all trains in the jurisdiction, calculates the recommended speed of each train and sends it to the train. The edge cloud server can make real-time adjustments based on the operation strategy issued by the central cloud platform and the feedback of the current running status of the train. The two adjacent edge cloud servers synchronize data in real time, and physically establish a takeover area. When the train runs into the takeover area, the two adjacent edge cloud servers communicate with the train at the same time to complete the takeover of the train and realize seamless switching between adjacent edge cloud servers that control the train.

[0176] The virtual connection method provided in this embodiment includes the following steps:

[0177] First, for any edge cloud server, in response to a virtual coupling instruction, the line data corresponding to the vehicles of each onboard controller is obtained from the onboard controller corresponding to the number of the train to be coupled.

[0178] The virtual coupling instruction is issued by the central cloud platform to each edge cloud server corresponding to the train to be coupled, and the virtual coupling instruction includes the number of the train to be coupled. For example, the monitoring module of the central cloud platform can display the operation and maintenance data of all on-board controllers and edge cloud service devices, and can issue control instructions, for example, issuing virtual coupling instructions to edge cloud servers through the monitoring module of the central cloud platform.

[0179] The edge cloud server responds to the virtual coupling instruction and obtains the line data corresponding to the vehicles of each on-board controller from the on-board controller corresponding to the number of the train to be coupled. The edge cloud server includes a data exchange module, a data processing module and a data analysis module. The data exchange module has the function of exchanging data with the on-board controller and the central cloud server, and ensures data security. The data analysis module analyzes the collected on-board controller parameters and line data. The data processing module processes and calculates the vehicle control parameters based on the data obtained by the data exchange module, the analysis results of the data analysis module, and the queried line data, and sends the control strategy to the on-board controller. The line data includes the speed information, position information and trackside equipment status information corresponding to the vehicles of each on-board controller.

[0180] Step 802: Determine the control strategy corresponding to the vehicle of each onboard controller based on the route data corresponding to the vehicle of each onboard controller;

[0181] Specifically, after collecting the line data corresponding to the vehicles of each on-board controller (including the speed information, position information and trackside equipment status information corresponding to the vehicles of each on-board controller), the control strategy of each vehicle in the train set is determined based on the line data.

[0182] For example, the control strategy is to calculate the train movement authorization, emergency braking speed limit and recommended speed. The movement authorization is the maximum range of safe operation of the train, so as to maintain a safe interval between trains. The emergency braking speed limit is the maximum speed limit for emergency braking of the vehicle controlled by the on-board controller. The recommended speed is the speed at which the on-board controller controls the train to travel.

[0183] Different from the on-board subsystem of the traditional CBTC system, the application software of the on-board controller in the present invention only retains the functions of self-test, data transmission and reception, and direct control of the train, including power-on self-test, emergency braking, traction, normal braking, holding braking, door control, etc. The logic processing and parameter calculation are completed by the edge cloud server and the central cloud platform, and the results are sent to the on-board software of the on-board controller for execution.

[0184] Step 803: Send the control strategy corresponding to the vehicle of each on-board controller to the corresponding on-board controller; the control strategy corresponding to the vehicle of each on-board controller is used for each on-board controller to perform virtual coupling operation based on the control strategy corresponding to the vehicle of each on-board controller.

[0185] Specifically, after calculating the control strategy of the train formation, the edge cloud server sends the control strategy corresponding to the vehicle of each on-board controller to the corresponding on-board controller, for example, sends the control strategy of the train formation to the corresponding on-board controller via a wireless network.

[0186] Furthermore, after each on-board controller receives the control strategy, the control strategy corresponding to the vehicle of each on-board controller is used for each on-board controller to perform a virtual coupling operation based on the control strategy corresponding to the vehicle of each on-board controller.

[0187] For example, a virtual coupling operation is when the on-board controller detects that the real-time speed of the train is greater than or equal to the emergency braking speed limit of the edge cloud computing, it immediately outputs emergency braking to ensure the safety of the train; after the on-board controller receives the recommended speed of the edge cloud computing, it drives the train at the recommended speed and outputs traction and braking commands to the vehicle to complete the reasonable control of the train speed, and so on.

[0188] In the traditional CBTC system, the braking performance of different trains is not the same. As long as the braking performance of the front train is better than that of the rear train, the two trains may collide during braking even if the speed of the rear train is lower than that of the front train. This situation is well solved in the CBTC system based on cloud-edge-end collaboration. The edge cloud server coordinates the position and speed of all trains, collects information about all trains in the area, and adjusts the control strategy of each train in real time to make up for the performance differences between trains. The maximum braking force of the virtual coupled train is the maximum braking force of all trains in the formation. The edge cloud server calculates the emergency braking distance of the front train at different speeds and slopes according to the maximum braking force and the most unfavorable situation, and uses this distance as the safety protection distance of the rear train. This ensures that even if the front train brakes urgently, the parking position of the rear train is greater than the previous estimate, effectively ensuring driving safety during the virtual coupling process.

[0189] The method provided in this embodiment is applied to an edge cloud server in a cloud-edge-end collaborative CBTC system, wherein the cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle-mounted controller corresponding to each edge cloud server; the method includes: first, for any edge cloud server, in response to a virtual coupling instruction, obtaining line data corresponding to the vehicle of each vehicle-mounted controller from the vehicle-mounted controller corresponding to the number of the train to be coupled, wherein the virtual coupling instruction is issued by the central cloud platform to each edge cloud server corresponding to the train to be coupled, and the virtual coupling instruction includes the number of the train to be coupled; then, based on the line data corresponding to the vehicle of each vehicle-mounted controller, determining the control strategy corresponding to the vehicle of each vehicle-mounted controller; and then, sending the control strategy corresponding to the vehicle of each vehicle-mounted controller to the corresponding vehicle-mounted controller, wherein the control strategy corresponding to the vehicle of each vehicle-mounted controller is used for each vehicle-mounted controller to perform a virtual coupling operation based on the control strategy corresponding to the vehicle of each vehicle-mounted controller.

[0190] The cloud-edge-end collaborative CBTC system in the present invention includes a central cloud platform, at least one edge cloud server, and a vehicle controller corresponding to each edge cloud server. The central cloud platform issues a virtual coupling instruction. The edge cloud server first obtains the line data corresponding to the vehicle of each vehicle controller from the vehicle controller corresponding to the number of the train to be coupled based on the virtual coupling instruction. The edge cloud server then determines the control strategy corresponding to the vehicle of each vehicle controller based on the line data corresponding to the vehicle of each vehicle controller, and sends each control strategy to the corresponding vehicle controller. The present invention realizes virtual coupling through a cloud-edge-end collaborative CBTC system with a new architecture, and uses cloud-edge-end collaborative technology to control the tracking interval of the head and tail trains in real time, effectively ensuring driving safety.

[0191] The virtual connection device based on the cloud-edge-end collaborative CBTC system provided by the present invention is described below. The virtual connection device based on the cloud-edge-end collaborative CBTC system described below and the virtual connection method based on the cloud-edge-end collaborative CBTC system described above can be referenced to each other.

[0192] Fig.10 1 is a structural schematic diagram of a virtual coupling device based on a cloud-edge-end collaborative CBTC system provided by the present invention. The virtual coupling device 1000 based on a cloud-edge-end collaborative CBTC system is applied to an edge cloud server in the cloud-edge-end collaborative CBTC system. The cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle controller corresponding to each edge cloud server; the virtual coupling device 1000 based on a cloud-edge-end collaborative CBTC system includes the following modules:

[0193] The data acquisition module 1010 is used for obtaining, for any of the edge cloud servers, line data corresponding to the vehicles of each on-board controller from the on-board controller corresponding to the number of the train to be coupled in response to the virtual coupling instruction; the line data includes speed information and position information corresponding to the vehicles of each on-board controller; the virtual coupling instruction is issued by the central cloud platform to each edge cloud server corresponding to the train to be coupled; the virtual coupling instruction includes the number of the train to be coupled;

[0194] A strategy determination module 1020, for determining a control strategy corresponding to the vehicle of each onboard controller based on the route data corresponding to the vehicle of each onboard controller;

[0195] The sending module 1030 is used to send the control strategy corresponding to the vehicle of each on-board controller to the corresponding on-board controller; the control strategy corresponding to the vehicle of each on-board controller is used for each on-board controller to perform virtual coupling operations based on the control strategy corresponding to the vehicle of each on-board controller.

[0196] The device provided in this embodiment is applied to the edge cloud server in the cloud-edge-end collaborative CBTC system, and the cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle controller corresponding to each edge cloud server; the device includes a data acquisition module 1010, a strategy determination module 1020 and a sending module 1030, wherein the data acquisition module 1010, for any edge cloud server, responds to a virtual coupling instruction, and obtains the line data corresponding to the vehicle of each vehicle controller from the vehicle controller corresponding to the number of the train to be coupled; wherein the line data includes the speed corresponding to the vehicle of each vehicle controller Information and location information, the virtual coupling instruction is issued by the central cloud platform to each edge cloud server corresponding to the train to be coupled, and the virtual coupling instruction includes the number of the train to be coupled; then, the strategy determination module 1020 is used to determine the control strategy corresponding to the vehicle of each on-board controller based on the line data corresponding to the vehicle of each on-board controller; further, the sending module 1030 is used to send the control strategy corresponding to the vehicle of each on-board controller to the corresponding on-board controller, wherein the control strategy corresponding to the vehicle of each on-board controller is used for each on-board controller to perform virtual coupling operations based on the control strategy corresponding to the vehicle of each on-board controller.

[0197] The cloud-edge-end collaborative CBTC system in the present invention includes a central cloud platform, at least one edge cloud server, and a vehicle controller corresponding to each edge cloud server. The central cloud platform issues a virtual coupling instruction. The edge cloud server first obtains the line data corresponding to the vehicle of each vehicle controller from the vehicle controller corresponding to the number of the train to be coupled based on the virtual coupling instruction. The edge cloud server then determines the control strategy corresponding to the vehicle of each vehicle controller based on the line data corresponding to the vehicle of each vehicle controller, and sends each control strategy to the corresponding vehicle controller. The present invention realizes virtual coupling through a cloud-edge-end collaborative CBTC system with a new architecture, and uses cloud-edge-end collaborative technology to control the tracking interval of the head and tail trains in real time, effectively ensuring driving safety.

[0198] According to a virtual coupling device 1000 based on a cloud-edge-end collaborative CBTC system provided by the present invention, the control strategy includes movement authorization information, and the movement authorization information is used to characterize the maximum range of safe operation of the train corresponding to the vehicle of each on-board controller; the speed information corresponding to each vehicle includes the speed corresponding to the preceding vehicle of each vehicle and the deceleration corresponding to the preceding vehicle of each vehicle; the position information of each vehicle includes the distance between each vehicle and the preceding vehicle of each vehicle, and the line data also includes the transmission delay;

[0199] The strategy determination module 1020 is specifically used to:

[0200] For any vehicle of the on-board controller, determining a speed-based tracking distance of the vehicle in the virtual coupling based on the distance between the vehicle and the vehicle ahead of the vehicle, the speed corresponding to the vehicle ahead of the vehicle, the deceleration corresponding to the vehicle ahead of the vehicle, and the transmission delay;

[0201] The speed-based tracking distance of each vehicle is determined as the mobile authorization information corresponding to the vehicle of each on-board controller; the mobile authorization information is used to characterize the maximum range of safe operation of the train corresponding to the vehicle of each on-board controller.

[0202] According to a virtual coupling device 1000 based on a cloud-edge-end collaborative CBTC system provided by the present invention, the speed information corresponding to each of the vehicles also includes the current speed of each of the vehicles and the acceleration of each of the vehicles, and the position information of each of the vehicles also includes the distance between each of the vehicles and the speed limit point; the control strategy also includes a target emergency braking speed limit, and the target emergency braking speed limit is used to represent the maximum speed limit of the vehicle emergency braking controlled by the on-board controller;

[0203] The strategy determination module 1020 is further configured to:

[0204] Determine all speed limit points within the range of the train to the line terminal;

[0205] For any of the speed limit points, determining the first emergency braking speed limit corresponding to the vehicle of each of the onboard controllers at the speed limit point according to the current speed of each of the vehicles, the acceleration of each of the vehicles, and the distance between each of the vehicles and the speed limit point;

[0206] The minimum value among the first emergency braking speed limits corresponding to the vehicles of the vehicle-mounted controllers at the speed limit points is determined as the target emergency braking speed limit corresponding to the vehicles of the vehicle-mounted controllers.

[0207] According to a virtual coupling device 1000 based on a cloud-edge-end collaborative CBTC system provided by the present invention, the control strategy also includes a target recommended speed, and the target recommended speed is used to characterize the speed at which the on-board controller controls the vehicle to travel;

[0208] The strategy determination module 1020 is further configured to:

[0209] For any speed limit point, determining a first recommended speed corresponding to the speed limit point for the vehicle of each onboard controller according to the current speed of each vehicle, the acceleration of each vehicle, and the distance between each vehicle and the speed limit point;

[0210] Compare the first recommended speed corresponding to the vehicle of each on-board controller at the speed limit point with the target emergency braking speed limit corresponding to the vehicle of each on-board controller to obtain a first comparison result, and determine the second recommended speed corresponding to the vehicle of each on-board controller at the speed limit point based on the first comparison result;

[0211] According to the preset station-to-station operation grade table, query and obtain the third recommended speed corresponding to the vehicle of each onboard controller at the speed limit point;

[0212] Compare each of the third recommended speeds with each of the second recommended speeds to obtain a second comparison result, and determine a target recommended speed corresponding to the vehicle of each of the onboard controllers at the speed limit point based on the second comparison result;

[0213] The target recommended speed corresponding to the vehicle of each on-board controller at the speed limit point is determined as the control strategy corresponding to the vehicle of each on-board controller.

[0214] According to a virtual connection device 1000 based on a cloud-edge-device collaborative CBTC system provided by the present invention, the strategy determination module 1020 is further used to:

[0215] The emergency braking distance corresponding to each of the vehicles is determined based on the speed of each of the vehicles when the train braking begins, the speed of each of the vehicles when the train braking ends, the friction coefficient between the tracks, and the inclination of the road surface relative to the horizontal plane.

[0216] According to a virtual connection device 1000 based on a cloud-edge-device collaborative CBTC system provided by the present invention, the strategy determination module 1020 is further used to:

[0217] According to the position information corresponding to the train set in the virtual coupling and the position information of the plurality of switches, the updated movement authorization information of the tail train in the train set in the virtual coupling is determined.

[0218] Fig.11 An example of a physical structure diagram of an electronic device is shown in FIG. Fig.11As shown, the electronic device may include: a processor 1110, a communication interface 1120, a memory 1130 and a communication bus 1140, wherein the processor 1110, the communication interface 1120 and the memory 1130 communicate with each other through the communication bus 1140. The processor 1110 may call the logic instructions in the memory 1130 to execute a virtual connection method based on a cloud-edge-end collaborative CBTC system, the method being applied to an edge cloud server in a cloud-edge-end collaborative CBTC system, the cloud-edge-end collaborative CBTC system including a central cloud platform, at least one edge cloud server, and a vehicle-mounted controller corresponding to each edge cloud server; the method includes:

[0219] For any of the edge cloud servers, in response to the virtual coupling instruction, the line data corresponding to the vehicles of each on-board controller is obtained from the on-board controller corresponding to the number of the train to be coupled; the line data includes the speed information and position information corresponding to the vehicles of each on-board controller; the virtual coupling instruction is issued by the central cloud platform to each edge cloud server corresponding to the train to be coupled; the virtual coupling instruction includes the number of the train to be coupled;

[0220] Determining the control strategy corresponding to the vehicle of each onboard controller based on the route data corresponding to the vehicle of each onboard controller;

[0221] The control strategy corresponding to the vehicle of each on-board controller is sent to the corresponding on-board controller; the control strategy corresponding to the vehicle of each on-board controller is used for each on-board controller to perform virtual coupling operations based on the control strategy corresponding to the vehicle of each on-board controller.

[0222] In addition, the logic instructions in the above-mentioned memory 1130 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0223] On the other hand, the present invention further provides a computer program product, the computer program product includes a computer program, the computer program can be stored on a non-transitory computer-readable storage medium, when the computer program is executed by a processor, the computer can execute the virtual connection method based on the cloud-edge-end collaborative CBTC system provided by the above methods, the method is applied to an edge cloud server in the cloud-edge-end collaborative CBTC system, the cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle controller corresponding to each of the edge cloud servers; the method includes:

[0224] For any of the edge cloud servers, in response to the virtual coupling instruction, the line data corresponding to the vehicles of each on-board controller is obtained from the on-board controller corresponding to the number of the train to be coupled; the line data includes the speed information and position information corresponding to the vehicles of each on-board controller; the virtual coupling instruction is issued by the central cloud platform to each edge cloud server corresponding to the train to be coupled; the virtual coupling instruction includes the number of the train to be coupled;

[0225] Determining the control strategy corresponding to the vehicle of each onboard controller based on the route data corresponding to the vehicle of each onboard controller;

[0226] The control strategy corresponding to the vehicle of each on-board controller is sent to the corresponding on-board controller; the control strategy corresponding to the vehicle of each on-board controller is used for each on-board controller to perform virtual coupling operations based on the control strategy corresponding to the vehicle of each on-board controller.

[0227] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to execute the virtual connection method based on the cloud-edge-end collaborative CBTC system provided by the above methods, and the method is applied to an edge cloud server in the cloud-edge-end collaborative CBTC system, wherein the cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle-mounted controller corresponding to each of the edge cloud servers; the method includes:

[0228] For any of the edge cloud servers, in response to the virtual coupling instruction, the line data corresponding to the vehicles of each on-board controller is obtained from the on-board controller corresponding to the number of the train to be coupled; the line data includes the speed information and position information corresponding to the vehicles of each on-board controller; the virtual coupling instruction is issued by the central cloud platform to each edge cloud server corresponding to the train to be coupled; the virtual coupling instruction includes the number of the train to be coupled;

[0229] Determining the control strategy corresponding to the vehicle of each onboard controller based on the route data corresponding to the vehicle of each onboard controller;

[0230] The control strategy corresponding to the vehicle of each on-board controller is sent to the corresponding on-board controller; the control strategy corresponding to the vehicle of each on-board controller is used for each on-board controller to perform virtual coupling operations based on the control strategy corresponding to the vehicle of each on-board controller.

[0231] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0232] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0233] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A cloud-edge-device collaborative CBTC system, characterized in that: The cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle controller corresponding to each edge cloud server; wherein, The central cloud platform is used to issue a virtual coupling instruction to each edge cloud server corresponding to the train to be coupled; the virtual coupling instruction includes the number of the train to be coupled; Each of the edge cloud servers is used to respond to the virtual coupling instruction and obtain the route data corresponding to the vehicle of each onboard controller from the onboard controller corresponding to the number of the train to be coupled; the route data includes speed information and position information corresponding to each of the vehicles; Based on the route data corresponding to the vehicles of each on-board controller, the control strategy corresponding to the vehicles of each on-board controller is determined; the control strategy includes movement authorization information, target emergency braking speed limit and target recommended speed; the movement authorization information is used to characterize the maximum range of safe operation of the train corresponding to the vehicles of each on-board controller; the target emergency braking speed limit is used to characterize the maximum speed limit for emergency braking of the vehicle controlled by each on-board controller; the target recommended speed is used to characterize the speed at which the vehicle is controlled by each on-board controller; Sending the control strategy corresponding to the vehicle of each on-board controller to the corresponding on-board controller; Each of the on-board controllers is used to perform virtual coupling based on the corresponding control strategy; the virtual coupling is used to represent connecting the trains to be coupled by means of communication.

2. The cloud-edge-end collaborative CBTC system according to claim 1 is characterized in that: The speed information corresponding to each of the vehicles includes the speed corresponding to the vehicle preceding each of the vehicles and the deceleration corresponding to the vehicle preceding each of the vehicles; the position information of each of the vehicles includes the distance between each of the vehicles and the vehicle preceding each of the vehicles, and the line data also includes the transmission delay; The determining of the control strategy corresponding to the vehicle of each onboard controller based on the route data corresponding to the vehicle of each onboard controller comprises: For any vehicle of the on-board controller, determining a speed-based tracking distance of the vehicle in the virtual coupling based on the distance between the vehicle and the vehicle ahead of the vehicle, the speed corresponding to the vehicle ahead of the vehicle, the deceleration corresponding to the vehicle ahead of the vehicle, and the transmission delay; The speed-based tracking distance of each of the vehicles is determined as the movement authorization information corresponding to the vehicle of each of the vehicle-mounted controllers.

3. The cloud-edge-end collaborative CBTC system according to claim 1 is characterized in that: The speed information corresponding to each of the vehicles also includes the current speed of each of the vehicles and the acceleration of each of the vehicles, and the position information of each of the vehicles also includes the distance between each of the vehicles and the speed limit point; the control strategy corresponding to the vehicle of each of the vehicle controllers is determined based on the route data corresponding to the vehicle of each of the vehicle controllers, including: Determine all speed limit points within the range of the train to the line terminal; For any of the speed limit points, determining the first emergency braking speed limit corresponding to the vehicle of each of the onboard controllers at the speed limit point according to the current speed of each of the vehicles, the acceleration of each of the vehicles, and the distance between each of the vehicles and the speed limit point; The minimum value among the first emergency braking speed limits corresponding to the vehicles of the vehicle-mounted controllers at the speed limit points is determined as the target emergency braking speed limit corresponding to the vehicles of the vehicle-mounted controllers.

4. The cloud-edge-end collaborative CBTC system according to claim 3 is characterized in that: The determining of the control strategy corresponding to the vehicle of each onboard controller based on the route data corresponding to the vehicle of each onboard controller comprises: For any speed limit point, determining a first recommended speed corresponding to the speed limit point for the vehicle of each onboard controller according to the current speed of each vehicle, the acceleration of each vehicle, and the distance between each vehicle and the speed limit point; Compare the first recommended speed corresponding to the vehicle of each on-board controller at the speed limit point with the target emergency braking speed limit corresponding to the vehicle of each on-board controller to obtain a first comparison result, and determine the second recommended speed corresponding to the vehicle of each on-board controller at the speed limit point based on the first comparison result; According to the preset station-to-station operation grade table, query and obtain the third recommended speed corresponding to the vehicle of each onboard controller at the speed limit point; Compare each of the third recommended speeds with each of the second recommended speeds to obtain a second comparison result, and determine a target recommended speed corresponding to the vehicle of each of the onboard controllers at the speed limit point based on the second comparison result; The target recommended speed corresponding to the vehicle of each on-board controller at the speed limit point is determined as the control strategy corresponding to the vehicle of each on-board controller.

5. The cloud-edge-end collaborative CBTC system according to any one of claims 1 to 4, characterized in that: Each of the edge cloud servers is further used for: The emergency braking distance corresponding to each of the vehicles is determined based on the speed of each of the vehicles when the train braking begins, the speed of each of the vehicles when the train braking ends, the friction coefficient between the tracks, and the inclination of the road surface relative to the horizontal plane.

6. The cloud-edge-end collaborative CBTC system according to any one of claims 1 to 4, characterized in that: Each of the edge cloud servers is further used for: According to the position information corresponding to the train set in the virtual coupling and the position information of the plurality of switches, the updated movement authorization information of the tail train in the train set in the virtual coupling is determined.

7. A virtual connection method based on a cloud-edge-end collaborative CBTC system, characterized in that: An edge cloud server applied to a cloud-edge-end collaborative CBTC system, wherein the cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle controller corresponding to each edge cloud server; the method includes: For any of the edge cloud servers, in response to the virtual coupling instruction, the line data corresponding to the vehicles of each on-board controller is obtained from the on-board controller corresponding to the number of the train to be coupled; the line data includes the speed information and position information corresponding to the vehicles of each on-board controller; the virtual coupling instruction is issued by the central cloud platform to each edge cloud server corresponding to the train to be coupled; the virtual coupling instruction includes the number of the train to be coupled; Based on the route data corresponding to the vehicles of each on-board controller, the control strategy corresponding to the vehicles of each on-board controller is determined; the control strategy includes movement authorization information, target emergency braking speed limit and target recommended speed; the movement authorization information is used to characterize the maximum range of safe operation of the train corresponding to the vehicles of each on-board controller; the target emergency braking speed limit is used to characterize the maximum speed limit for emergency braking of the vehicle controlled by each on-board controller; the target recommended speed is used to characterize the speed at which the vehicle is controlled by each on-board controller; The control strategy corresponding to the vehicle of each on-board controller is sent to the corresponding on-board controller; the control strategy corresponding to the vehicle of each on-board controller is used for each on-board controller to perform virtual coupling operations based on the control strategy corresponding to the vehicle of each on-board controller; the virtual coupling is used to represent that the trains to be coupled are connected through communication.

8. A virtual connection device based on a cloud-edge-end collaborative CBTC system, characterized in that: An edge cloud server applied to a cloud-edge-end collaborative CBTC system, wherein the cloud-edge-end collaborative CBTC system includes a central cloud platform, at least one edge cloud server, and a vehicle controller corresponding to each edge cloud server; the device includes: A data acquisition module is used for obtaining, for any of the edge cloud servers, line data corresponding to the vehicles of each on-board controller from the on-board controller corresponding to the number of the train to be coupled in response to the virtual coupling instruction; the line data includes speed information and position information corresponding to the vehicles of each on-board controller; the virtual coupling instruction is issued by the central cloud platform to each edge cloud server corresponding to the train to be coupled; the virtual coupling instruction includes the number of the train to be coupled; A strategy determination module is used to determine the control strategy corresponding to the vehicle of each on-board controller based on the route data corresponding to the vehicle of each on-board controller; the control strategy includes movement authorization information, target emergency braking speed limit and target recommended speed; the movement authorization information is used to characterize the maximum range of safe operation of the train corresponding to the vehicle of each on-board controller; the target emergency braking speed limit is used to characterize the maximum speed limit for emergency braking of the vehicle controlled by each on-board controller; the target recommended speed is used to characterize the speed at which the vehicle is controlled by each on-board controller; A sending module is used to send the control strategy corresponding to the vehicle of each on-board controller to the corresponding on-board controller; the control strategy corresponding to the vehicle of each on-board controller is used for each on-board controller to perform virtual coupling operation based on the control strategy corresponding to the vehicle of each on-board controller; the virtual coupling is used to represent that the trains to be coupled are connected by communication.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, it implements the virtual connection method based on the cloud-edge-end collaborative CBTC system as described in claim 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the virtual connection method based on the cloud-edge-end collaborative CBTC system as described in claim 7.

Images