Train-oriented virtual marshalling operation control system and method

Abstract

The invention discloses a train-oriented virtual marshalling operation control system and a train-oriented virtual marshalling operation control method. The system comprises a data acquisition module, a train autonomous decision module and a central operation control module, wherein the data acquisition module is used for acquiring running condition data and line condition data corresponding to a train; the train autonomous decision-making module is used for analyzing the running state of the train based on the received running state data and the line state data, determining an abnormal type corresponding to the abnormal state when the running state is the abnormal state, and determining an abnormal state of the train based on the abnormal type; at least one virtual marshalling including the virtual marshalling corresponding to the train is adjusted; and the central operation control module is used for performing operation control on the virtual marshalling based on the received operation condition data corresponding to the adjusted virtual marshalling. According to the technical scheme, flexible virtual marshalling of the trains can be achieved, the labor cost is reduced, and the train dispatching efficiency and the track resource utilization rate are improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a train-based virtual marshaling operation control system and method. Background Art

[0002] With the continuous growth of network scale and passenger flow, the temporal and spatial imbalance of urban rail transit passenger travel distribution has gradually become apparent, and the existing train operation organization method is difficult to match the dynamic changes of capacity and passenger flow.

[0003] At present, the traditional train virtual marshaling operation control system, the virtual marshaling and dispatching of trains are restricted by the block division of the track and the fixed signal system. Trains need to be dispatched according to fixed routes and timetables. When encountering emergencies, they rely on manual adjustments by dispatchers, which are difficult to adjust. In addition, the traditional train operation marshaling mode is relatively simple and cannot quickly meet the changing transportation needs and special operation needs, and track resources cannot be optimally utilized. Summary of the invention

[0004] The present invention provides a train-based virtual marshaling operation control system and method to achieve flexible virtual marshaling of trains, reduce labor costs, and improve train dispatching efficiency and track resource utilization.

[0005] In a first aspect, an embodiment of the present invention provides a train-based virtual marshaling operation control system, wherein the train-based virtual marshaling operation control system includes: a data acquisition module, a train autonomous decision-making module and a central operation control module; wherein:

[0006] The data acquisition module is used to collect the running status data and line status data corresponding to the train, and send the running status data and the line status data to the train autonomous decision-making module;

[0007] The train autonomous decision module is used to analyze the running state of the train based on the received running state data and the line state data, and when the running state is an abnormal state, determine the abnormal type corresponding to the abnormal state;

[0008] The train autonomous decision module is used to adjust at least one of the virtual marshalings including the virtual marshaling corresponding to the train based on the abnormal type, and send the operation status data of the adjusted virtual marshaling to the central operation control module, wherein each virtual marshaling includes at least one train;

[0009] The central operation control module is used to control the operation of the virtual formation based on the received operation status data corresponding to the virtual formation.

[0010] In a second aspect, an embodiment of the present invention further provides a train-based virtual marshaling operation control method, the method comprising:

[0011] The data collection module collects the running status data and the line status data corresponding to the train, and sends the running status data and the line status data to the train autonomous decision-making module;

[0012] By means of the train autonomous decision-making module, the running state of the train is analyzed based on the received running state data and the line state data, and when the running state is an abnormal state, the abnormal type corresponding to the abnormal state is determined;

[0013] By means of the train autonomous decision-making module, based on the abnormal type, at least one of the virtual marshalings including the virtual marshaling corresponding to the train is adjusted, and the operation status data of the adjusted virtual marshaling is sent to the central operation control module, wherein each virtual marshaling includes at least one train;

[0014] The central operation control module controls the operation of the virtual formation based on the received operation status data corresponding to the virtual formation.

[0015] The train-based virtual marshaling operation control system of the embodiment of the present invention includes: a data acquisition module, a train autonomous decision module and a central operation control module; wherein the data acquisition module is used to collect the operation status data and line status data corresponding to the train, and send the operation status data and the line status data to the train autonomous decision module, which can ensure the accuracy and comprehensiveness of the data. The train autonomous decision module is used to analyze the operation status of the train based on the received operation status data and the line status data, and when the operation status is an abnormal state, determine the abnormal type corresponding to the abnormal state; the train autonomous decision module is used to adjust at least one virtual marshaling including the virtual marshaling corresponding to the train based on the abnormal type, and send the adjusted operation status data of the virtual marshaling to the central operation control module, so as to reduce the labor cost of time delay caused by human decision-making and improve the operation efficiency, wherein each virtual marshaling includes at least one train. The central operation control module is used to control the operation of the virtual marshaling based on the received operation status data corresponding to the virtual marshaling, which helps to optimize the overall transportation efficiency and safety. By integrating data acquisition modules, train autonomous decision-making and central operation control modules, flexible virtual marshaling of trains can be achieved, which can adapt to the virtual marshaling operation needs of different scales and complexities, reduce labor costs, and improve train scheduling efficiency and track resource utilization.

[0016] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 It is a structural schematic diagram of a train-based virtual marshaling operation control system provided by Embodiment 1 of the present invention;

[0019] Figure 2 It is a structural schematic diagram of another train-based virtual marshaling operation control system involved in Embodiment 1 of the present invention;

[0020] Figure 3 It is a flow chart of a train-based virtual marshaling operation control method provided in Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only 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 should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] Embodiment 1

[0024] Figure 1 The structure block diagram of a train-based virtual marshaling operation control system provided by an embodiment of the present invention. Figure 1 As shown, the train-based virtual marshaling operation control system includes: a data acquisition module 101, a train autonomous decision-making module 102 and a central operation control module 103; wherein,

[0025] The data acquisition module 101 is used to collect the running status data and the line status data corresponding to the train, and send the running status data and the line status data to the train autonomous decision module 102;

[0026] The train autonomous decision module 102 is used to analyze the running state of the train based on the received running state data and the line state data, and when the running state is an abnormal state, determine the abnormal type corresponding to the abnormal state;

[0027] The train autonomous decision module 102 is used to adjust at least one of the virtual marshalings including the virtual marshaling corresponding to the train based on the abnormal type, and send the operation status data of the adjusted virtual marshaling to the central operation control module 103, wherein each virtual marshaling includes at least one train;

[0028] The central operation control module 103 is used to control the operation of the virtual formation based on the received operation status data corresponding to the virtual formation.

[0029] In an embodiment of the present invention, the data acquisition module is used to collect the operating status data and line status data corresponding to the train, and send the operating status data and the line status data to the train autonomous decision-making module, which can ensure the accuracy and comprehensiveness of the data. Among them, the operating status data can refer to various data generated by the train during operation, including but not limited to the train's running speed, acceleration, location information (such as the current line and mileage), the number and distribution of passengers in the car, etc. The line status data can refer to various data related to the train operation line, including the physical state of the line (such as track wear, turnout status, signal equipment status, etc.), weather conditions (such as rain and snow, wind speed, visibility, etc.) and obstacles or abnormal conditions around the line (such as foreign objects on the track, construction conditions, etc.).

[0030] The train autonomous decision module is used to analyze the running state of the train based on the received running state data and the line state data, and when the running state is an abnormal state, determine the abnormal type corresponding to the abnormal state; the train autonomous decision module is used to adjust at least one of the virtual marshalings including the virtual marshaling corresponding to the train based on the abnormal type, and send the adjusted running state data of the virtual marshaling to the central operation control module, so as to reduce the labor cost of time delay caused by human decision-making and improve the operation efficiency, wherein each virtual marshaling includes at least one train. Among them, the running state may refer to the running state and performance of the train during operation. The abnormal state may refer to the situation or problem that is inconsistent with the normal state during operation. The abnormal type may refer to the result of classifying and identifying the abnormal state. For example, the abnormal type may include abnormal passenger flow (the passenger capacity in the carriage is higher than the preset threshold), line fault (such as track damage, signal fault, etc.) and train fault. Virtual marshaling may refer to a virtual train marshaling unit formed by grouping trains according to certain rules and conditions.

[0031] The central operation control module is used to control the operation of the virtual marshaling based on the received operation status data corresponding to the virtual marshaling, which helps to optimize the overall transportation efficiency and safety. By integrating the data acquisition module, train autonomous decision-making and central operation control module, flexible virtual marshaling of trains can be achieved, which can adapt to the operation requirements of virtual marshaling of different scales and complexities, reduce labor costs, and improve train scheduling efficiency and track resource utilization.

[0032] Optionally, the data acquisition module includes: a train data acquisition unit and a train-to-ground communication unit, wherein the train data acquisition unit is used to collect corresponding operating status data based on sensors inside the train; the train-to-ground communication unit is used to obtain status information of the train line and stations along the line.

[0033] Specifically, a variety of sensors can be installed on the train, such as positioning sensors (Global Positioning System, GPS), speed sensors, acceleration sensors, passenger capacity sensors, etc., and signal acquisition equipment and road condition monitoring sensors and other equipment are set on the line. The train data acquisition unit collects the corresponding train-related operating status data based on the sensors inside the train; the train-to-ground communication unit obtains the status information of the line where the train is located and the stations along the line based on the signal acquisition equipment and road condition monitoring sensors and other equipment set on the line, where the status information of the station may include but is not limited to passenger flow information. Furthermore, the collected operating status data and line status data can also be pre-processed to remove noise and outliers to ensure the accuracy and reliability of the data.

[0034] It should be noted that the data acquisition module monitors the train's running position, speed, acceleration, equipment operating status (such as traction system, braking system, communication system, etc.) and environmental parameters in the carriage (temperature, humidity, lighting, etc.). Once a train failure or other abnormal conditions (such as equipment overheating, communication interruption, passenger emergency, etc.) are found, the adjustment mechanism can be started immediately. In the event of a train failure, the impact of the failure on the operation of the virtual marshaling is quickly assessed, and corresponding adjustment measures are taken, such as safely removing the faulty train from the virtual marshaling, and reallocating the tasks of other trains to ensure that the overall operation of the virtual marshaling is not seriously affected; or according to the fault situation, the operation mode of the virtual marshaling is adjusted, such as reducing the operating speed, changing the operating route, etc., to ensure the safety of the train operation. And upload this information to the central operation control module.

[0035] Optionally, the train autonomous decision-making module comprises: a data processing unit, a vehicle-to-vehicle communication unit and an autonomous decision-making unit, wherein the data processing unit is used to determine the operating status corresponding to the train based on the received operating status data and the line status data, and determine the abnormality type corresponding to the abnormal status when the operating status is an abnormal state; the vehicle-to-vehicle communication unit is used to obtain the operating status data and line status data corresponding to other trains in the virtual formation corresponding to the train; the autonomous decision-making unit is used to adjust at least one virtual formation including the virtual formation based on the abnormality type and the operating status data and line status data corresponding to the trains in the virtual formation.

[0036] Specifically, Figure 2As shown, the data processing unit receives the running status data and line status data from the data acquisition module. Based on the received data, the data processing unit analyzes the running status of the train to determine whether the train is in a normal state or an abnormal state. If the train is in an abnormal state, the data processing unit will further analyze the data corresponding to the abnormal state and determine the specific abnormal type corresponding to the abnormal state, such as overload, signal failure, foreign matter on the track, etc., so as to provide timely information for subsequent decision-making and control. The vehicle-to-vehicle communication unit follows a specific communication protocol to ensure that data can be correctly transmitted between trains, communicate with other trains in the virtual formation, and exchange their respective running status data and line status data. Through vehicle-to-vehicle communication, the train can understand the running status and line status of other trains in the virtual formation in real time and realize information sharing. The autonomous decision-making unit analyzes the abnormal type, the running status data of the trains in the virtual formation, and the line status data. According to the analysis results, an adjustment strategy is formulated, such as adjusting the speed of the train, changing the running path, reconfiguring the virtual formation, etc. Through the autonomous decision-making unit, data can be analyzed and decisions can be made quickly, reducing the time delay of human decision-making and improving the response speed of the system.

[0037] It should be noted that trains exchange information in real time through vehicle-to-vehicle communication units. They share key information such as position, speed, acceleration, and operating intentions so that each train can understand the dynamics of other trains in real time and coordinate their operations. For example, when a train needs to slow down or stop, it can notify the rear train in advance through vehicle-to-vehicle communication. After receiving the information, the rear train automatically adjusts its own running speed according to the distance and speed relationship between itself and the front train, maintains a safe interval, and avoids rear-end collisions. At the same time, trains can also collaborate in operations such as entering, exiting, and overtaking to improve the operating efficiency of the entire virtual formation.

[0038] Optionally, the autonomous decision-making unit includes: a structure adjustment subunit, a spacing adjustment subunit and a speed control subunit, wherein the structure adjustment subunit is used to adjust the train composition of at least one virtual formation including the virtual formation based on the abnormality type; the spacing adjustment subunit is used to adjust the interval distance between each train in the virtual formation based on the operating status data and line status data corresponding to the trains in the adjusted virtual formation; the speed control subunit is used to adjust the speed of the trains in the virtual formation based on the operating status data and line status data corresponding to the trains in the adjusted virtual formation.

[0039] Specifically, the structure adjustment subunit receives the abnormal type information from the data processing unit, analyzes the abnormal type, and evaluates the train composition of the current virtual marshaling according to the abnormal type, and determines whether the structure of the virtual marshaling needs to be adjusted to cope with the abnormal state. The spacing adjustment subunit receives the running status data and line status data of the adjusted trains in the virtual marshaling from the data processing unit, and calculates the interval distance between each train in the adjusted virtual marshaling according to the received data, and adjusts the interval distance between each train to ensure the safety of train travel. The speed control subunit receives the running status data and line status data of the adjusted trains in the virtual marshaling from the data processing unit, and analyzes the speed of the trains in the adjusted virtual marshaling according to the received data, and adjusts the running speed of the train to ensure the safety of train travel.

[0040] It should be noted that the train autonomous decision-making module implements the dynamic adjustment of virtual marshaling supported by train-based distributed control technology. Trains can flexibly and autonomously join or leave virtual marshaling during operation according to actual operational needs (such as changes in passenger flow, line failures, equipment maintenance, etc.). When a new train unit needs to join the virtual marshaling, it negotiates the location and timing of joining and synchronizes its own operating parameters to achieve a smooth marshaling process. Similarly, when a train needs to be disassembled from a virtual marshaling, it can also safely detach from the marshaling and continue to operate independently or perform other tasks.

[0041] Exemplarily, the abnormality type may be abnormal passenger flow, line failure, and train failure.

[0042] When the passenger flow is abnormal, that is, when the passenger flow of a certain section of the line increases, the train in this area can detect the change in the passenger capacity in the carriage through the on-board sensor. The train transmits this information to other trains in the virtual marshaling through train-to-train communication, and jointly formulates and implements the adjustment operation strategy. And upload this information to the central operation control module. For example, appropriately reduce the interval distance between virtual marshaling trains (within a safe range), increase the possibility of the number of trains passing through the area per unit time, to meet the needs of passenger flow changes; or adjust the stop time of the train to improve the transportation capacity of the line.

[0043] In case of line fault, that is, if the train detects a fault in the line ahead (such as track damage, signal failure, etc.), it immediately sends the fault information to other trains in the virtual formation and starts the local emergency handling procedure. The train negotiates with other trains to adjust the running route or speed according to the severity and location of the fault. For example, some trains may need to slow down or stop and wait, while other trains can choose to detour or adjust the running interval according to the actual situation to ensure the safe operation of the entire virtual formation. And upload this information to the central operation control module.

[0044] When a train fails, that is, when a train fails, its onboard control system automatically sends fault alarm information to other trains, including the fault type, location and severity. After receiving the information, other trains in the virtual formation make adjustments according to the preset fault handling strategy. For example, trains near the faulty train will automatically increase the distance between them and the faulty train to prevent collision accidents; at the same time, according to the overall operation situation, other trains may adjust their speed, running routes or reallocate transportation tasks to minimize the impact of the fault on the entire virtual formation operation. And upload this information to the central operation control module.

[0045] Optionally, the spacing adjustment subunit is specifically used to: determine the spacing distance between multiple trains in the virtual formation based on the operating status data corresponding to the adjusted trains in the virtual formation, and adjust the spacing distance between each train in the virtual formation based on a preset safety distance corresponding to the line status data.

[0046] Among them, the preset safety distance may refer to a pre-set vehicle distance range for ensuring the safety of train travel.

[0047] Specifically, the spacing adjustment subunit analyzes the running status data corresponding to the adjusted trains in the virtual marshaling, determines the spacing distances between the multiple trains in the virtual marshaling, and compares the spacing distances between the trains in the virtual marshaling with the preset safety distance. If the spacing distances between the trains in the marshaling exceed the range corresponding to the preset safety distance, the spacing distances between the trains in the virtual marshaling are adjusted according to the preset safety distance corresponding to the line status data, thereby improving the utilization rate of track resources while ensuring the safety of train travel.

[0048] Optionally, the spacing adjustment subunit is further specifically used to determine a preset safety distance between each train in the virtual formation based on the operating mode corresponding to the adjusted virtual formation.

[0049] Specifically, the spacing adjustment subunit can dynamically adjust the preset spacing distance between trains according to the operation mode of the virtual marshaling (such as dense operation mode or loose operation mode). Furthermore, it can also combine the actual situation of the line and, under the premise of ensuring safety, try to shorten the spacing distance between trains to improve the line's throughput capacity. Furthermore, using advanced sensor technology and control algorithms, the actual spacing distance between trains can be monitored in real time, and compared with the preset safety distance, so as to adjust the spacing in time.

[0050] Exemplarily, the interval adjustment subunit pre-sets the safe interval distance range (preset safe distance) between trains according to line conditions (such as curves, ramps, etc.), train performance and the operation mode of virtual marshaling. The actual interval distance between trains is monitored in real time using ranging sensors, and when the distance exceeds the safe range, it is adjusted by controlling the speed of the train. For example, on straight sections with good road conditions and similar train performance, a smaller safe interval distance is used to increase the train density; on curves, ramps or sections with large differences in train performance, the safe interval distance is appropriately increased to ensure safe operation. The safe interval distance can be adaptively adjusted according to the real-time operation situation. For example, in the event of an emergency (such as an obstacle ahead, a train failure, etc.), the interval distance can be quickly increased to ensure that the train has sufficient safe braking distance; during peak passenger flow periods, the interval distance can be flexibly adjusted according to transportation demand and train operation status to optimize the line transportation capacity.

[0051] Optionally, the speed control subunit is specifically used to: determine the speed curve corresponding to the train in the virtual formation based on the operating status data and line status data corresponding to the train in the adjusted virtual formation, and adjust the speed of the train in the virtual formation based on the speed curve so that the interval between the trains in the virtual formation reaches a preset safety distance.

[0052] Specifically, the speed control subunit receives the running status data and line status data of the adjusted virtual train in the data processing unit, and analyzes these data to determine the running status and line conditions of the train. These data may include the current speed, position, acceleration, line slope, curve radius, signal status, etc. of the train. Based on the collected data, the speed control subunit calculates the ideal speed curve of the train, which can ensure that the train can meet the requirements of safety interval while maintaining efficient operation. According to the deviation between the ideal speed curve and the actual operating speed, the speed control subunit formulates a speed adjustment strategy. If the actual speed is higher than the ideal speed, the subunit will formulate a deceleration strategy; if the actual speed is lower than the ideal speed, an acceleration strategy will be formulated. The speed control subunit performs corresponding speed adjustment operations on the train according to the speed adjustment strategy. Through precise speed control and adjustment, the speed control subunit can ensure that the interval between trains reaches a preset safety distance, thereby avoiding the occurrence of safety accidents such as rear-end collisions.

[0053] For example, the speed control subunit can calculate the optimal speed curve for each train based on the line speed limit, the state of the signal ahead, the relative position and speed of the trains in the virtual formation, and the passenger flow demand. Through the traction and braking systems of the train, the acceleration, deceleration and cruising of the train are controlled according to the optimal speed curve, and the speed coordination between trains is achieved by using the train-to-train communication to avoid the risk of collision between trains, while improving the operation efficiency and reducing energy consumption.

[0054] Optionally, the structure adjustment subunit is specifically used to: in response to the abnormality type being passenger flow abnormality and the train and the preceding car being the same virtual marshaling, adjust the virtual marshaling corresponding to the train; and in response to the abnormality type being passenger flow abnormality and the train and the preceding car being different virtual marshalings, update the virtual marshaling corresponding to the train to the virtual marshaling corresponding to the preceding car.

[0055] Among them, abnormal passenger flow may refer to that the passenger density or passenger capacity in the train is higher than the preset density or preset passenger capacity.

[0056] Specifically, if the abnormality type is abnormal passenger flow (train overload), it is determined whether the train and the preceding car are in the same virtual marshaling. If the train and the preceding car are in the same virtual marshaling, the virtual marshaling corresponding to the train is adjusted, and the train is kicked out of the virtual marshaling (i.e., the train and the corresponding virtual marshaling are disassembled); if the train and the preceding car are in different virtual marshalings, the train is kicked out of the virtual marshaling and added to the virtual marshaling corresponding to the preceding car. By adjusting or updating the virtual marshaling, it is possible to more effectively cope with abnormal passenger flow, reduce waiting time and running intervals between trains, and thus improve overall operating efficiency.

[0057] For example, the calculation is based on the capacity of 310 people per section of the A-type car, and the calculation is based on the maximum passenger capacity of 50% overload. The virtual marshaling adopts a small marshaling, calculated according to two cars, with a full load of 620 people and a maximum overload of 930 people. The relationship between the passenger boarding speed and the full load rate, as well as the relationship between the passenger arrival and the waiting time, and the relationship between the number of waiting trips. The virtual marshaling scheme can be determined based on the comprehensive evaluation of the train / platform crowding level and the passenger waiting time. The data processing unit corresponding to the train receives the passenger space occupancy rate transmitted by the data acquisition module, and judges the crowding level and boarding rate in the car. If it is judged that the crowding level in the car is high and the boarding rate is slow, it is determined that the state of the train is abnormal, and the abnormal type is abnormal passenger flow, which is sent to the autonomous decision-making unit. When the autonomous decision-making unit determines that it is a different virtual marshaling from the preceding car, it immediately starts the virtual marshaling with the preceding car, calculates the mobile authorization of the virtual marshaling, starts the vehicle control strategy of the catching-up state, and performs the interval spacing adjustment and running speed control through the spacing adjustment subunit and the speed control subunit. And this dynamic marshaling state is sent to the central operation control module. It should be noted that the calculation and division methods of the carriage congestion state are as follows:

[0058]

[0059] Among them, θ is the passenger space occupancy rate, S is the compartment area, and P is the number of passengers.

[0060]

[0061] Among them, β 上 is the passenger boarding rate, F 上 is the number of people getting on the bus when it stops, T 停 The train stop time.

[0062] If the calculated space occupancy rate of the vehicle is less than 0.4 persons / m 2 When the boarding rate is less than 20 people / min, it is determined that the train has abnormal passenger flow and needs to actively adjust the virtual formation of the train or the preceding train. The relationship between passenger space occupancy and carriage status can be shown in Table 1 below:

[0063] Table 1: Correlation table between space occupancy and compartment status

[0064]

[0065] For example, assuming that this train has 6 carriages (A, B, C, D, E, F), the status is: carriage A-comfortable, B-crowded, C-extremely crowded, D-crowded, E-comfortable, F-spacious, and the train broadcast can also be triggered: "Dear passengers, the middle carriage is crowded, please evacuate to the front or rear of the train, thank you for your cooperation!"

[0066] It should be noted that the train autonomous decision-making module can also report the degree of congestion in the carriage (passenger space occupancy rate) and boarding rate to the central operation control module. The central operation control module also receives the passenger entry rate. When the passenger entry speed is much faster than the boarding speed, it can comprehensively judge the platform congestion period, adjust the subsequent train virtual marshaling train plan, and increase transportation capacity. Specifically,

[0067]

[0068] Among them, β 进 is the passenger entry rate, F 进 is the number of people entering the station within time T.

[0069] when When the entry speed exceeds the boarding speed, people will gather on the platform. 2 When the train space occupancy rate is greater than or equal to 1 person / m, the central operation control module starts the virtual marshaling plan. 2 until.

[0070] Optionally, the central operation control module is specifically used to adjust the operating speed corresponding to the virtual grouping and the interval between the virtual groupings based on the received operating status data and expected passenger flow corresponding to the multiple virtual groupings.

[0071] Specifically, the central operation control module receives the operation status data from each virtual marshaling, including the real-time speed, position, acceleration, passenger capacity, etc. of the train. According to the operation status data and the expected passenger flow, the operation status and passenger flow demand of each virtual marshaling are analyzed. If it is found that the operating speed of a virtual marshaling is lower or higher than expected, the module will adjust the operating speed of the marshaling to optimize the operation efficiency and passenger comfort. The central operation control module can also adjust the interval between virtual marshalings according to the expected passenger flow and the operation status of each virtual marshaling. In the case of large passenger flow, the module may shorten the interval between virtual marshalings to increase train capacity and reduce passenger waiting time. In the case of small passenger flow, the module may increase the interval between virtual marshalings to improve operation efficiency and reduce energy consumption. By adjusting the operating speed and interval of virtual marshaling, the central operation control module can optimize the operation efficiency of the train, reduce waiting time and operation interval.

[0072] The train-based virtual marshaling operation control system provided in an embodiment of the present invention includes: a data acquisition module, a train autonomous decision module and a central operation control module; wherein the data acquisition module is used to collect the operation status data and line status data corresponding to the train, and send the operation status data and the line status data to the train autonomous decision module, which can ensure the accuracy and comprehensiveness of the data. The train autonomous decision module is used to analyze the operation status of the train based on the received operation status data and the line status data, and when the operation status is an abnormal state, determine the abnormal type corresponding to the abnormal state; the train autonomous decision module is used to adjust at least one virtual marshaling including the virtual marshaling corresponding to the train based on the abnormal type, and send the adjusted operation status data of the virtual marshaling to the central operation control module, so as to reduce the labor cost of time delay caused by human decision-making and improve the operation efficiency, wherein each virtual marshaling includes at least one train. The central operation control module is used to control the operation of the virtual marshaling based on the received operation status data corresponding to the virtual marshaling, which helps to optimize the overall transportation efficiency and safety. By integrating data acquisition modules, train autonomous decision-making and central operation control modules, flexible virtual marshaling of trains can be achieved, which can adapt to the virtual marshaling operation needs of different scales and complexities, reduce labor costs, and improve train scheduling efficiency and track resource utilization.

[0073] It should be noted that before the virtual marshaling is in operation, the central operation control module will dynamically adjust the composition of the virtual marshaling according to the conditions. Dynamically build the virtual marshaling according to passenger flow demand, train performance and line conditions. Determine the number, type (such as ordinary trains, virtual marshaling trains with different numbers of marshaling) and running order of the trains in the marshaling. Monitor the running status of the trains in the virtual marshaling in real time. When a train fails or other abnormal conditions occur, adjust the composition of the virtual marshaling in time, such as removing the faulty train from the marshaling, or reallocating other trains to join the marshaling.

[0074] Embodiment 2

[0075] This embodiment provides a train-based virtual marshaling operation control method based on the train-based virtual marshaling operation control system provided in the above embodiment. Figure 3 A flow chart of a train-based virtual marshaling operation control method provided by an embodiment of the present invention is shown as follows: Figure 3 As shown, the method comprises the following steps:

[0076] S210. Collect the running status data and line status data corresponding to the train through the data collection module, and send the running status data and the line status data to the train autonomous decision-making module.

[0077] Specifically, the data acquisition module collects the train's operating status data (such as speed, position, acceleration, etc.) and line status data (such as track status, signal status, weather conditions, etc.) in real time through various sensors installed on the train and the line (such as speed sensors, position sensors, track status monitors, etc.). After preprocessing, the collected data is transmitted to the train's autonomous decision-making module in real time through a wireless network or wired connection, thereby ensuring the real-time nature of the data, helping to quickly respond to any potential problems, and improving the accuracy and comprehensiveness of data collection, reducing manual monitoring costs, and improving the automation level of the system.

[0078] S220. Analyze the running status of the train based on the received running status data and the line status data through the train autonomous decision-making module, and when the running status is an abnormal state, determine the abnormal type corresponding to the abnormal state.

[0079] Specifically, after receiving the operating status data and the line status data from the data acquisition module, the train autonomous decision module analyzes the operating status of the train based on these data to determine whether there is an abnormal state (such as overload, signal failure, foreign objects on the track, etc.). If an abnormal state is detected, the type of abnormality is further identified. Through the train autonomous decision module, the time delay of human decision-making can be reduced, and the ability and efficiency of responding to emergencies can be improved.

[0080] S230. Through the train autonomous decision-making module, based on the abnormality type, at least one of the virtual marshalings including the virtual marshaling corresponding to the train is adjusted, and the operating status data of the adjusted virtual marshaling is sent to the central operation control module, wherein each virtual marshaling includes at least one train.

[0081] Specifically, if an abnormal state is detected, the train autonomous decision module will further identify the type of abnormality and formulate countermeasures based on the abnormality type, which may involve adjusting the speed of the train, changing the running path, or reconfiguring the virtual marshaling. Virtual marshaling adjustments may include reallocating trains to different marshalings, adjusting the spacing or speed of trains within the marshaling to optimize overall efficiency or safety. The adjusted virtual marshaling operating status data is updated and sent to the central operation control module. The dynamic adjustment of virtual marshaling can adapt to the changing operating environment and optimize operating efficiency.

[0082] S240. Performing operation control on the virtual formation based on the received operation status data corresponding to the virtual formation through the central operation control module.

[0083] Specifically, the central operation control module receives the operating status data corresponding to the virtual marshaling from the train autonomous decision-making module, and based on this data, monitors the overall operating status of each virtual marshaling to ensure that all trains are running on the predetermined safe and efficient track. The central operation control module can issue instructions to further adjust the configuration of the virtual marshaling or take other operation control measures, such as suspending service, initiating emergency braking, etc., and ensure the synchronization and coordination of information between each virtual marshaling. Through the central operation control module, the train operation can be managed as a whole, which helps to optimize the overall transportation efficiency and safety.

[0084] In the train-based virtual marshaling operation control method provided in the embodiment of the present invention, the data acquisition module is used to collect the running status data and line status data corresponding to the train, and the running status data and the line status data are sent to the train autonomous decision module, which can ensure the accuracy and comprehensiveness of the data. Through the train autonomous decision module, based on the received running status data and the line status data, the running status of the train is analyzed, and when the running status is an abnormal state, the abnormal type corresponding to the abnormal state is determined; through the train autonomous decision module, based on the abnormal type, at least one virtual marshaling including the virtual marshaling corresponding to the train is adjusted, and the running status data of the adjusted virtual marshaling is sent to the central operation control module, so as to reduce the labor cost of time delay caused by human decision-making and improve the operation efficiency, wherein each virtual marshaling contains at least one train. Through the central operation control module, based on the received running status data corresponding to the virtual marshaling, the virtual marshaling is operated and controlled, which helps to optimize the overall transportation efficiency and safety. By integrating data acquisition modules, train autonomous decision-making and central operation control modules, flexible virtual marshaling of trains can be achieved, which can adapt to the virtual marshaling operation needs of different scales and complexities, reduce labor costs, and improve train scheduling efficiency and track resource utilization.

[0085] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A train-based virtual marshaling operation control system, characterized in that: include: Data acquisition module, train autonomous decision-making module and central operation control module; among them, The data acquisition module is used to collect the running status data and line status data corresponding to the train, and send the running status data and the line status data to the train autonomous decision-making module; The train autonomous decision module is used to analyze the running state of the train based on the received running state data and the line state data, and when the running state is an abnormal state, determine the abnormal type corresponding to the abnormal state; The train autonomous decision module is used to adjust at least one of the virtual marshalings including the virtual marshaling corresponding to the train based on the abnormal type, and send the operation status data of the adjusted virtual marshaling to the central operation control module, wherein each virtual marshaling includes at least one train; The central operation control module is used to control the operation of the virtual formation based on the received operation status data corresponding to the virtual formation.

2. The system according to claim 1, characterized in that The data acquisition module includes: a train data acquisition unit and a train-to-ground communication unit, wherein: The train data collection unit is used to collect corresponding running status data based on sensors inside the train; The train-to-ground communication unit is used to obtain status information of the line where the train is located and the stations along the line.

3. The system according to claim 1, characterized in that The train autonomous decision-making module includes: a data processing unit, a vehicle-to-vehicle communication unit and an autonomous decision-making unit, wherein: The data processing unit is used to determine the running state corresponding to the train based on the received running state data and the line state data, and determine the abnormality type corresponding to the abnormal state when the running state is an abnormal state; The vehicle-to-vehicle communication unit is used to obtain the running status data and line status data corresponding to other trains in the virtual formation corresponding to the train; The autonomous decision-making unit is used to adjust at least one virtual formation including the virtual formation based on the abnormal type and the running status data and line status data corresponding to the train in the virtual formation.

4. The system according to claim 3, characterized in that The autonomous decision-making unit includes: a structure adjustment subunit, a spacing adjustment subunit and a speed control subunit, wherein: The structure adjustment subunit is used to adjust the train configuration of at least one virtual marshaling including the virtual marshaling based on the abnormality type; The spacing adjustment subunit is used to adjust the spacing distance between each train in the virtual formation based on the running status data and line status data corresponding to the trains in the adjusted virtual formation; The speed control subunit is used to adjust the speed of the train in the virtual formation based on the running status data and line status data corresponding to the train in the adjusted virtual formation.

5. The system according to claim 4, characterized in that The spacing adjustment subunit is specifically used to: determine the spacing distance between multiple trains in the virtual formation based on the operating status data corresponding to the adjusted trains in the virtual formation, and adjust the spacing distance between each train in the virtual formation based on the preset safety distance corresponding to the line status data.

6. The system according to claim 4, characterized in that The spacing adjustment subunit is further specifically used to determine a preset safety distance between each train in the virtual formation based on the operation mode corresponding to the adjusted virtual formation.

7. The system according to claim 4, characterized in that The speed control subunit is specifically used to: determine the speed curve corresponding to the train in the virtual formation based on the adjusted operating status data and line status data corresponding to the train in the virtual formation, and adjust the speed of the train in the virtual formation based on the speed curve so that the interval between the trains in the virtual formation reaches a preset safety distance.

8. The system according to claim 4, characterized in that The structure adjustment subunit is specifically used to: in response to the abnormality type being passenger flow abnormality and the train and the preceding car being the same virtual marshaling, adjust the virtual marshaling corresponding to the train; and in response to the abnormality type being passenger flow abnormality and the train and the preceding car being different virtual marshalings, update the virtual marshaling corresponding to the train to the virtual marshaling corresponding to the preceding car.

9. The system according to claim 1, characterized in that The central operation control module is specifically used to adjust the operating speed corresponding to the virtual marshaling and the interval between the virtual marshalings based on the received operating status data and expected passenger flow corresponding to the multiple virtual marshalings.

10. A train-based virtual marshaling operation control method, characterized in that: include: The data collection module collects the running status data and the line status data corresponding to the train, and sends the running status data and the line status data to the train autonomous decision-making module; By means of the train autonomous decision-making module, the running state of the train is analyzed based on the received running state data and the line state data, and when the running state is an abnormal state, the abnormal type corresponding to the abnormal state is determined; By means of the train autonomous decision-making module, based on the abnormal type, at least one of the virtual marshalings including the virtual marshaling corresponding to the train is adjusted, and the operation status data of the adjusted virtual marshaling is sent to the central operation control module, wherein each virtual marshaling includes at least one train; The central operation control module controls the operation of the virtual formation based on the received operation status data corresponding to the virtual formation.

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