Cooperative control method and system for coal mine unmanned transport vehicle

Abstract

The invention provides a coal mine unmanned transport vehicle cooperative control method and system. The method comprises the following steps: determining an advancing collision cluster of a target transport vehicle at each driving switching point through a preset advancing route of each conflicting transport vehicle; the advancing deviation degree of the target transport vehicle is determined through historical transport data, deviation prediction is carried out on each driving switching point in the planned advancing route according to the advancing deviation degree, and a deviation reachable domain of each driving switching point after position deviation is obtained; determining a plurality of emergency collision avoidance areas through each advancing collision cluster and the corresponding deviation reachable area, and performing space-time cooperative coupling on the advancing route of the target transport vehicle through each emergency collision avoidance area to obtain all collision risk values; and performing collision avoidance on each driving switching point according to all collision risk values and each deviation reachable domain. Based on the scheme, the space-time cooperative collision avoidance of the coal mine unmanned transport vehicle in a dynamic uncertain scene can be realized, so that the real-time efficiency of the advancing route of the coal mine unmanned transport vehicle is improved.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle collision avoidance control, and more specifically, to a method and system for collaborative control of unmanned coal mine transport vehicles. Background Art

[0002] Vehicle collision avoidance control of unmanned coal mine transport vehicles is an important technology to ensure that unmanned coal mine transport vehicles avoid collisions with obstacles during transportation. The core goal of vehicle collision avoidance control is to ensure the safety and smoothness of vehicle driving through the comprehensive use of sensor data, path planning algorithms and real-time control strategies. Vehicle collision avoidance control is a core component of unmanned autonomous driving technology. Through advanced sensors, algorithms and control strategies, the system can perceive the environment, predict paths and make collision avoidance decisions in real time, ensuring the safe driving of unmanned coal mine transport vehicles in complex traffic environments. With the continuous advancement of technology, collision avoidance control of unmanned coal mine transport vehicles will become more intelligent and reliable, promoting the popularization and application of autonomous driving technology.

[0003] The vehicle collision avoidance control in the prior art mainly monitors the operating status of each unmanned coal transport vehicle in real time, thereby ensuring that multiple unmanned coal transport vehicles in intersecting routes can also ensure that there will be no collision between unmanned coal transport vehicles. The setting of the initial route of the unmanned coal transport vehicle in the above method greatly affects the number of collision avoidance adjustments of the unmanned coal transport vehicle. If the number of collision avoidance adjustments is too large, the transportation efficiency of the unmanned coal transport vehicle will be reduced. The routes of each unmanned coal transport vehicle in a coal mine are coordinated and compared with those of other unmanned coal transport vehicles in time and space to avoid collisions for each unmanned coal transport vehicle, which can reduce the number of collision adjustments between unmanned coal transport vehicles in a coal mine. Therefore, how to achieve spatiotemporal coordinated collision avoidance of unmanned coal transport vehicles in the dynamic and uncertain scenario of coal mines, thereby improving the real-time and high efficiency of the routes of unmanned coal transport vehicles in coal mines, is a difficult problem faced by the industry. Summary of the invention

[0004] The present application provides a method and system for collaborative control of unmanned coal mine transport vehicles, which can realize spatiotemporal collaborative collision avoidance of unmanned coal mine transport vehicles in dynamic uncertain scenarios, thereby improving the real-time and high efficiency of the travel routes of unmanned coal mine transport vehicles.

[0005] In a first aspect, the present application provides a method for collaboratively controlling an unmanned transport vehicle in a coal mine, comprising: A plug-in hybrid-driven coal mine unmanned transport vehicle is selected as the target transport vehicle, and then the initial travel state and planned travel route of the target transport vehicle are determined; According to the initial traveling state, all conflicting transport vehicles are selected from all coal mine unmanned transport vehicles, and then the cooperative driving relationship between the conflicting transport vehicles is determined; Determine all driving switching points in the planned route, and determine the travel collision cluster of the target transport vehicle at each driving switching point in the planned route through the preset travel routes of each conflicting transport vehicle and the cooperative driving relationship; Acquire historical transportation data of the target transport vehicle, determine the travel deviation of the target transport vehicle through the historical transportation data, perform position deviation prediction for each drive switching point in the planned travel route according to the travel deviation and the collaborative driving relationship, and obtain a deviation reachable domain of each drive switching point after the position deviation; Determine the emergency collision avoidance zone of each driving switching point in the planned route when the target transport vehicle deviates from its position through each travel collision cluster and the corresponding deviation reachable domain, and perform spatiotemporal collaborative coupling on the collision of the route when the target transport vehicle deviates from its position through each emergency collision avoidance zone to obtain a collision risk value between the target transport vehicle and each conflicting transport vehicle; When the target transport vehicle is transporting along the planned route, collision avoidance is performed on each driving switching point in the planned route according to all collision risk values ​​and each deviation reachable domain.

[0006] In some embodiments, selecting all conflicting transport vehicles from all coal mine unmanned transport vehicles according to the initial traveling state specifically includes: Determining the travel acceleration and travel angular velocity of the target transport vehicle through the initial travel state; Determining a travel conflict range of the target transport vehicle according to the travel acceleration and the travel angular velocity; Get the current travel status of each coal mine unmanned transport vehicle; All coal mine unmanned transport vehicles are subjected to conflict screening according to each current travel state and the travel conflict range, so as to obtain all conflicting transport vehicles.

[0007] In some embodiments, determining the travel collision cluster of the target transport vehicle at each drive switching point in the planned travel route through the preset travel routes of each conflicting transport vehicle and the cooperative driving relationship specifically includes: For each driving switching point in the planned travel route, determining a risk time period for the target transport vehicle to reach the driving switching point through the planned travel route; Determine the risky travel route of the corresponding conflicting transport vehicle within the risky time period through each preset travel route; Determine the travel collision value between the corresponding conflicting transport vehicle and the target transport vehicle at the drive switching point according to each risk travel route and the cooperative driving relationship; The traveling collision cluster of the driving switching point is determined based on all the traveling collision values, and then the traveling collision cluster of each driving switching point in the planned traveling route is obtained.

[0008] In some embodiments, determining the travel deviation of the target transport vehicle through the historical transport data specifically includes: For each historical transportation process of the target transport vehicle, obtaining the actual travel route and the planned route of the historical transportation process from the historical transportation data; Compare the deviation of each driving switching point of the planned route with the corresponding actual driving switching point in the actual travel route to obtain the deviation value of each driving switching point; Determine the route deviation value of the target transport vehicle in the historical transportation process through all the deviation values, and then obtain the route deviation value of the target transport vehicle in each historical transportation process; The travel deviation degree of the target transport vehicle is determined based on all route deviation values.

[0009] In some embodiments, performing position deviation prediction for each driving switching point in the planned traveling route according to the traveling deviation degree and the coordinated driving relationship to obtain the deviation reachable domain of each driving switching point after the position deviation specifically includes: For each driving switching point in the planned traveling route, obtaining the traveling state before the driving switching point in the planned traveling route as a preceding traveling state quantity; The position before the driving switching point is predicted by the preceding traveling state quantity, the coordinated driving relationship and the traveling deviation degree to obtain a preceding deviation area; Acquiring a travel state after a driving switching point in the planned travel route as a post-travel state quantity; The position after the driving switching point is predicted by the post-travel state quantity, the coordinated driving relationship and the travel deviation degree to obtain a post-travel deviation area; The deviation reachable domain of the driving switching point after the position deviation is determined according to the leading deviation zone and the trailing deviation zone, and then the deviation reachable domain of each driving switching point after the position deviation is obtained.

[0010] In some embodiments, determining the emergency collision avoidance zone of each driving switching point in the planned traveling route when the target transport vehicle deviates from its position through each traveling collision cluster and the corresponding deviation reachable domain specifically includes: For each driving switching point in the planned travel route, obtaining a deviation reachable domain of the driving switching point after the position deviation; Determine a collision-avoiding cooperation zone between the target transport vehicle and each conflicting transport vehicle at a driving switching point by using the deviation reachable domain and each travel collision value in the travel collision cluster; The emergency collision avoidance zone of the driving switching point after the position deviation is determined through all the cooperative zones, and then the emergency collision avoidance zone of each driving switching point in the planned route when the target transport vehicle has a position deviation is obtained.

[0011] In some embodiments, the conflict transport vehicle is a plug-in hybrid driven unmanned coal mine transport vehicle.

[0012] In a second aspect, the present application provides a coal mine unmanned transport vehicle collaborative control system, including a collaborative control unit, the collaborative control unit comprising: An acquisition module is used to select a plug-in hybrid-driven coal mine unmanned transport vehicle as a target transport vehicle, and then determine the initial travel state of the target transport vehicle and plan the travel route; A processing module, used for screening out all conflicting transport vehicles from all coal mine unmanned transport vehicles according to the initial traveling state, and then determining the cooperative driving relationship between the conflicting transport vehicles; The processing module is also used to determine all driving switching points in the planned travel route, and determine the travel collision cluster of the target transport vehicle at each driving switching point in the planned travel route through the preset travel routes of each conflicting transport vehicle and the cooperative driving relationship; The processing module is also used to obtain historical transportation data of the target transport vehicle, determine the travel deviation of the target transport vehicle through the historical transportation data, and predict the position deviation of each drive switching point in the planned travel route according to the travel deviation and the cooperative driving relationship to obtain the deviation reachable domain of each drive switching point after the position deviation; The processing module is also used to determine the emergency collision avoidance zone of each driving switching point in the planned route when the target transport vehicle deviates from its position through each travel collision cluster and the corresponding deviation reachable domain, and to perform spatiotemporal collaborative coupling on the collision of the route when the target transport vehicle deviates from its position through each emergency collision avoidance zone, so as to obtain the collision risk value between the target transport vehicle and each conflicting transport vehicle; The execution module is used to perform collision avoidance for each driving switching point in the planned route according to all collision risk values ​​and each deviation reachable domain when the target transport vehicle is transporting along the planned route.

[0013] In a third aspect, the present application provides a computer device, comprising a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned method for collaborative control of unmanned coal mine transport vehicles.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, in which instructions or codes are stored. When the instructions or codes are run on a computer, the computer implements the above-mentioned method for collaborative control of unmanned coal mine transport vehicles when executed.

[0015] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects: The present application provides a method and system for cooperative control of unmanned coal mine transport vehicles, wherein a plug-in hybrid-driven unmanned coal mine transport vehicle is selected as a target transport vehicle, and then the initial travel state and planned travel route of the target transport vehicle are determined; all conflicting transport vehicles are screened out from all unmanned coal mine transport vehicles according to the initial travel state, and then the cooperative driving relationship between the conflicting transport vehicles is determined; all driving switching points in the planned travel route are determined, and the travel collision cluster of each driving switching point of the target transport vehicle in the planned travel route is determined through the preset travel routes of each conflicting transport vehicle and the cooperative driving relationship; the historical transportation data of the target transport vehicle is obtained, and the travel deviation of the target transport vehicle is determined through the historical transportation data. The position deviation of each driving switching point in the planned route is predicted according to the travel deviation degree and the collaborative driving relationship, and the deviation reachable domain of each driving switching point after the position deviation is obtained; the emergency collision avoidance zone of each driving switching point in the planned route when the target transport vehicle has a position deviation is determined through each travel collision cluster and the corresponding deviation reachable domain, and the collision property of the route when the target transport vehicle has a position deviation is coupled in time and space through each emergency collision avoidance zone to obtain the collision risk value between the target transport vehicle and each conflicting transport vehicle; when the target transport vehicle is transported along the planned route, collision avoidance is performed on each driving switching point in the planned route according to all collision risk values ​​and each deviation reachable domain.

[0016] It can be seen that in the present application, when the target transport vehicle is transporting along the planned route, collision avoidance is performed on each drive switching point in the planned route according to all collision risk values ​​and each deviation reachable domain; wherein, by determining the deviation reachable domain of each drive switching point in the planned route after the position deviation, the regional range of each drive switching point of the target transport vehicle after the position deviation can be obtained. The above process determines the travel collision cluster of the target transport vehicle at each drive switching point based on the preset travel route of the conflicting vehicle, and can analyze the potential risk of each drive switching point in more detail, thereby improving the accuracy of risk assessment, and further improving the effectiveness of route adjustment of the target transport vehicle. The use of historical data for deviation prediction can comprehensively consider the travel deviation of unmanned coal mine transport vehicles under dynamic uncertain scenarios, thereby effectively reducing unforeseen deviations, improving the accuracy of prediction, and further improving the real-time efficiency of the travel route of unmanned coal mine transport vehicles; then, confirm By determining the collision risk value between the target transport vehicle and each conflicting transport vehicle, the possibility of collision between the target transport vehicle and each conflicting transport vehicle can be obtained. The above process determines the emergency collision avoidance zone of each drive switching point after the position deviation through the traveling collision cluster and the deviation reachable domain, and clarifies the collision avoidance area, which is convenient for the subsequent targeted collision avoidance operation of the coal mine unmanned transport vehicle. The delineation of the collaborative collision avoidance area makes the collision avoidance strategy more targeted, thereby improving the effectiveness of collision avoidance measures in dynamic uncertain scenarios. By calculating the collision risk value through spatiotemporal collaborative coupling, the risk can be more comprehensively evaluated to ensure the comprehensiveness and effectiveness of the collision avoidance strategy in dynamic uncertain scenarios. Finally, by dynamically adjusting the route, the collision risk can be minimized and the driving safety of the transport vehicle can be improved. In summary, based on the above scheme, the spatiotemporal collaborative collision avoidance of coal mine unmanned transport vehicles in dynamic uncertain scenarios can be realized, thereby improving the real-time and high efficiency of the coal mine unmanned transport vehicle's route. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0018] Figure 1 is an exemplary flow chart of a method for cooperatively controlling an unmanned transport vehicle in a coal mine according to some embodiments of the present application; Figure 2 is a schematic diagram of a process for determining a travel deviation degree according to some embodiments of the present application; Figure 3 is a schematic diagram of a process for determining an emergency collision avoidance zone according to some embodiments of the present application; Figure 4 is a schematic diagram of exemplary hardware and / or software of a collaborative control unit according to some embodiments of the present application; Figure 5 It is a structural schematic diagram of a computer device for implementing a method for collaborative control of unmanned coal mine transport vehicles according to some embodiments of the present application. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0020] The embodiment of the present application provides a method and system for collaborative control of unmanned transport vehicles in coal mines, the core of which is to determine the travel collision cluster of each drive switching point of the target transport vehicle in the planned travel route through the preset travel routes of each conflicting transport vehicle; determine the travel deviation of the target transport vehicle through historical transportation data, and predict the position deviation of each drive switching point in the planned travel route according to the travel deviation, and obtain the deviation reachable domain of each drive switching point after the position deviation; determine multiple emergency collision avoidance zones through each travel collision cluster and the corresponding deviation reachable domain, and perform spatiotemporal collaborative coupling on the travel route of the target transport vehicle through each emergency collision avoidance zone to obtain all collision risk values; perform collision avoidance on each drive switching point in the planned travel route according to all collision risk values ​​and each deviation reachable domain. Based on the above scheme, spatiotemporal collaborative collision avoidance of unmanned transport vehicles in coal mines in dynamic uncertain scenarios can be realized, thereby improving the real-time and high efficiency of the travel route of unmanned transport vehicles in coal mines.

[0021] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 , which is an exemplary flow chart of a method for cooperatively controlling an unmanned coal mine transport vehicle according to some embodiments of the present application, and the method for cooperatively controlling an unmanned coal mine transport vehicle mainly includes the following steps: In step 101, a plug-in hybrid driven coal mine unmanned transport vehicle is selected as a target transport vehicle, and then the initial travel state and planned travel route of the target transport vehicle are determined.

[0022] It should be noted that, in the present application, the target transport vehicle is a plug-in hybrid driven coal mine unmanned transport vehicle. In the present application, one coal mine unmanned transport vehicle is mainly used as the target transport vehicle for collision avoidance control. Other coal mine unmanned transport vehicles also use the same method for collision avoidance control, which will not be repeated in the present application; the initial travel state refers to the operating parameter information of the target transport vehicle at the beginning of the operation stage, and the initial travel state mainly includes the travel position, travel speed and travel angle of the target transport vehicle within the preset time period at the beginning of the travel; the planned travel route represents the default transport route of the target transport vehicle, and the planned travel route The travel route is usually generated by the central control system of the target transport vehicle at the beginning of transportation; in specific implementation, a plug-in hybrid-driven coal mine unmanned transport vehicle is randomly selected as the target transport vehicle. When the target transport vehicle starts running, the travel position, travel speed and travel angle of the target transport vehicle within a preset time period (the default is 5 minutes) are detected once per second. The set of all travel positions, travel speeds and travel angles can be used as the initial travel state of the target transport vehicle; the default transportation route of the target transport vehicle can be obtained in the central control system of the target transport vehicle as the planned travel route of the target transport vehicle.

[0023] In step 102, all conflicting transport vehicles are screened out from all coal mine unmanned transport vehicles according to the initial traveling state, and then the cooperative driving relationship between the conflicting transport vehicles is determined.

[0024] In some embodiments, selecting all conflicting transport vehicles from all coal mine unmanned transport vehicles according to the initial traveling state can be achieved by using the following steps: Determining the travel acceleration and travel angular velocity of the target transport vehicle through the initial travel state; Determining a travel conflict range of the target transport vehicle according to the travel acceleration and the travel angular velocity; Get the current travel status of each coal mine unmanned transport vehicle; All coal mine unmanned transport vehicles are subjected to conflict screening according to each current travel state and the travel conflict range, so as to obtain all conflicting transport vehicles.

[0025] It should be noted that, in the present application, the conflicting transport vehicle refers to an unmanned coal mine transport vehicle that may have a path conflict with the target transport vehicle during its movement, and the conflicting transport vehicle is a plug-in hybrid driven unmanned coal mine transport vehicle; the travel conflict range indicates the area where the target transport vehicle and other unmanned coal mine transport vehicles may have a path conflict and cause a collision; the current travel state includes a preset travel route, travel position, travel speed and travel angle, among which the preset travel route is generated by the central control system of the conflicting transport vehicle when the transportation starts.

[0026] In the specific implementation, first, the difference value of adjacent travel speeds in the initial travel state is obtained. Since the collection interval of adjacent travel speeds is once per second, the average of the difference values ​​of all adjacent travel speeds can be used as the travel acceleration, and the difference value of adjacent travel angular velocities in the initial travel state is obtained. Since the collection interval of adjacent travel angular velocities is once per second, the difference value of all adjacent travel angular velocities can be used as the value range of the travel angular velocity; secondly, the transportation time of this transportation can be obtained in the central control system of the target transport vehicle, and the travel angular velocity and travel acceleration can be used as the value range of the target transport vehicle this time. The travel parameters during transportation are used, and the existing trajectory prediction algorithm (for example: CTRA algorithm) is used to generate the operation trajectory of the target transport vehicle within the transportation duration. The middle area between the operation trajectory and the planned travel route can be used as the travel conflict range; then, the current travel status of each coal mine unmanned transport vehicle can be obtained from the sensor of the target transport vehicle. It should be noted that the current travel status does not include the travel status of the target transport vehicle; finally, all coal mine unmanned transport vehicles whose preset travel routes in the current travel status will pass through the travel conflict range can be used as conflicting transport vehicles, and all conflicting transport vehicles can be obtained.

[0027] It should be noted that in the present application, in order to improve the accuracy of defining conflicting transport vehicles, in its embodiments, the travel speed and travel angle in the current travel state can also be kept unchanged, so that the operation trajectory of each coal mine unmanned transport vehicle can be obtained, and the coal mine unmanned transport vehicles whose operation trajectories may pass through the travel conflict range are regarded as all conflicting transport vehicles, and no limitation is made here.

[0028] In some embodiments, the cooperative driving relationship between each conflicting transport vehicle is determined; in specific implementation, all cooperative information between the preset travel routes of each conflicting transport vehicle can be obtained, and all cooperative information within the travel conflict range can be screened as the cooperative driving relationship between each conflicting transport vehicle. It should be noted that each conflicting transport vehicle corresponds to a piece of cooperative information, and the cooperative information includes all conflict points of the preset travel route. The conflict point refers to the point where the conflicting transport vehicle may collide with other conflicting transport vehicles after deviating from the travel. The point whose distance between the preset travel routes is less than the preset conflict threshold can be used as the conflict point. The conflict threshold can be preset through historical experience.

[0029] In step 103, all driving switching points in the planned route are determined, and the travel collision cluster of the target transport vehicle at each driving switching point in the planned route is determined through the preset travel routes of each conflicting transport vehicle and the cooperative driving relationship.

[0030] In some embodiments, all drive switching points in the planned route are determined. It should be noted that in the present application, the drive switching points refer to the key nodes that the central control system in the coal mine unmanned transport vehicle needs to consider for collision avoidance and common use when performing path planning. The drive switching points can be manually marked in the central control system of the coal mine unmanned transport vehicle through historical experience.

[0031] It should be noted that the preset route of the conflicting transport vehicle refers to the default route of the conflicting transport vehicle, which is usually generated by the central control system of the conflicting transport vehicle at the beginning of transportation; in specific implementation, the communicator in the central control system of the target transport vehicle can be used to communicate with each conflicting transport vehicle to obtain the preset route of each conflicting transport vehicle.

[0032] In some embodiments, determining the travel collision cluster of the target transport vehicle at each drive switching point in the planned travel route through the preset travel routes of each conflicting transport vehicle and the cooperative driving relationship can be achieved by the following steps: For each driving switching point in the planned travel route, determining a risk time period for the target transport vehicle to reach the driving switching point through the planned travel route; Determine the risky travel route of the corresponding conflicting transport vehicle within the risky time period through each preset travel route; Determine the travel collision value between the corresponding conflicting transport vehicle and the target transport vehicle at the drive switching point according to each risk travel route and the cooperative driving relationship; The traveling collision cluster of the driving switching point is determined based on all the traveling collision values, and then the traveling collision cluster of each driving switching point in the planned traveling route is obtained.

[0033] It should be noted that, in the present application, a traveling collision cluster is a data set consisting of a plurality of traveling collision values, and a traveling collision value is a quantitative value representing the possibility of a collision between the target transport vehicle and the conflicting transport vehicle at each driving switching point.

[0034] In specific implementation, first, for each driving switching point in the planned route, the maximum value (i.e., maximum driving speed) and the minimum value (i.e., minimum driving speed) of all driving speeds (only values ​​greater than 0) of the target transport vehicle in the initial driving state are obtained, the distance from the starting point to the driving switching point in the planned route is obtained as the travel trajectory length, a time period is initialized, the sum of the ratio of the travel trajectory length to the maximum driving speed and the start time of this transportation is taken as the lower bound of the time period, and the sum of the ratio of the travel trajectory length to the minimum driving speed and the start time of this transportation is taken as the upper bound of the time period, and the time period can be taken as the risk time period for the target transport vehicle to reach the driving switching point; secondly, a conflicting transport vehicle is selected, and the maximum value (conflicting maximum speed) and the minimum value (conflicting minimum speed) of all driving speeds (only values ​​greater than 0) of the conflicting transport vehicle in the preset time period (the default is 3 days) can be obtained, and the product of the conflicting minimum speed and the lower bound of the risk time period is taken as the lower bound of the travel distance, and the conflicting transport vehicle can be transported from the initial point of transportation in the preset route for a fixed distance (i.e. The position after the conflicting transport vehicle reaches the lower limit of the travel distance (i.e., the lower limit of the travel distance), and the product of the maximum conflict speed and the upper limit of the risk time period as the upper limit of the travel distance. The position after the conflicting transport vehicle transports a fixed distance (i.e., the upper limit of the travel distance) from the initial point of transportation in the preset travel route can be used as the upper limit of the travel position. The set of all positions between the lower limit of the travel position and the upper limit of the travel position in the preset travel route of the conflicting transport vehicle can be used as the risky travel route of the conflicting transport vehicle in the risky time period. By repeating the above steps, the risky travel route of each conflicting transport vehicle in the risky time period can be obtained. Then, a conflicting transport vehicle is selected to obtain the cooperative information of the conflicting transport vehicle in the cooperative driving relationship. The shortest distance from the driving switching point to all the conflicting points in the cooperative information can be used as the travel collision value of the conflicting transport vehicle at the driving switching point with the target transport vehicle. By repeating the above steps, the travel collision value of each conflicting transport vehicle at the driving switching point with the target transport vehicle can be obtained. Finally, the set of all travel collision values ​​can be used as a travel collision cluster. The travel collision cluster of each drive switching point in the planned travel route can be obtained in the above manner.

[0035] In step 104, historical transportation data of the target transport vehicle is obtained, and the travel deviation of the target transport vehicle is determined through the historical transportation data. The position deviation of each drive switching point in the planned travel route is predicted according to the travel deviation and the collaborative driving relationship, and the deviation reachable domain of each drive switching point after the position deviation is obtained.

[0036] In specific implementation, the transportation record of each historical transportation process of the target transport vehicle within a preset time period (the default is 1 week) is obtained, and the collection of all transportation records can be used as the historical transportation data of the target transport vehicle, where the transportation record contains the actual route and the planned route.

[0037] In some embodiments, the travel deviation of the target transport vehicle is determined by using the historical transport data, referring to Figure 2 As described above, the figure is a schematic diagram of a process for determining a travel deviation in some embodiments of the present application. In this embodiment, determining the travel deviation can be achieved by using the following steps: In step 1041, for each historical transportation process of the target transport vehicle, an actual travel route and a planned route of the historical transportation process are obtained from the historical transportation data; In step 1042, a deviation comparison is performed between each driving switching point of the planned route and a corresponding actual driving switching point in the actual travel route to obtain a deviation value of each driving switching point; In step 1043, the route deviation value of the target transport vehicle in the historical transport process is determined by all the deviation values, and then the route deviation value of the target transport vehicle in each historical transport process is obtained; In step 1044, the travel deviation degree of the target transport vehicle is determined according to all the route deviation values.

[0038] It should be noted that, in the present application, the travel deviation degree indicates the degree of deviation of the travel route of the target transport vehicle; in specific implementation, first, for each historical transportation process of the target transport vehicle, the actual travel route and the planned route of the historical transportation process are obtained in the historical transportation data; secondly, a drive switching point is selected in the actual travel route, and the straight-line distance from the drive switching point to the nearest drive switching point in the planned route can be used as the deviation value of the drive switching point, and the above steps are repeated to obtain the deviation value of each drive switching point, and the deviation value is a quantitative value indicating the degree of deviation of the actual drive switching point in the actual travel route relative to the corresponding drive switching point in the planned route; then, the sum of all deviation values ​​can be used as the route deviation value of the target transport vehicle in the historical transportation process, and the route deviation value of the target transport vehicle in each historical transportation process can be obtained in the above manner, and the route deviation value is a quantitative value indicating the degree of deviation of the actual travel route of the target transport vehicle in each historical transportation process relative to the planned route; finally, the average of all route deviation values ​​can be used as the travel deviation degree of the target transport vehicle.

[0039] In some embodiments, the position deviation of each driving switching point in the planned traveling route is predicted according to the traveling deviation degree and the cooperative driving relationship, and the deviation reachable domain of each driving switching point after the position deviation is obtained can be implemented by the following steps: For each driving switching point in the planned traveling route, obtaining the traveling state before the driving switching point in the planned traveling route as a preceding traveling state quantity; The position before the driving switching point is predicted by the preceding traveling state quantity, the coordinated driving relationship and the traveling deviation degree to obtain a preceding deviation area; Acquiring a travel state after a driving switching point in the planned travel route as a post-travel state quantity; The position after the driving switching point is predicted by the post-travel state quantity, the coordinated driving relationship and the travel deviation degree to obtain a post-travel deviation area; The deviation reachable domain of the driving switching point after the position deviation is determined according to the leading deviation zone and the trailing deviation zone, and then the deviation reachable domain of each driving switching point after the position deviation is obtained.

[0040] It should be noted that the deviation reachable domain represents the possible area range of each driving switching point after the position deviation; the travel state includes the travel position, travel speed and travel angle; in specific implementation, firstly, for each driving switching point in the planned travel route, the travel state before the driving switching point (the default is 1 minute before reaching the driving switching point) in the planned travel route can be obtained once per second, and the set of all travel states can be used as the preceding travel state quantity; secondly, a high-order Markov model is initialized, and each travel state in the preceding travel state quantity is used as the state quantity of the high-order Markov model, all conflict points in the collaborative driving relationship are used as the prediction parameters of the high-order Markov model, and the travel deviation degree is used as the maximum deviation degree of the next predicted state of each travel state. All prediction results of the high-order Markov model (that is, multiple position points) can be used as the preceding deviation parameters. departure zone; then, the travel state after the drive switching point (the default is 1 minute after reaching the drive switching point) in the planned travel route can be obtained every second, and the set of all travel states can be used as the post-travel state quantity; then, a high-order Markov model is initialized, each travel state in the post-travel state quantity is used as the state quantity of the high-order Markov model, all conflict points in the collaborative driving relationship are used as prediction parameters of the high-order Markov model, and the travel deviation degree is used as the maximum deviation degree of the next predicted state of each travel state. All prediction results of the high-order Markov model (i.e., multiple position points) can be used as the post-deviation zone; finally, the front deviation zone and the rear deviation zone can be combined as the deviation reachable domain of the drive switching point after the position deviation. The deviation reachable domain of each drive switching point in the planned travel route after the position deviation can be obtained in the above manner.

[0041] In addition, it should be noted that the high-order Markov model is an extended Markov model. The high-order Markov model takes into account the impact of multiple past states of the system on the current state, rather than just the impact of the previous state on the current state. The high-order Markov model has significant advantages in processing time series and sequence data with complex dependencies. In this application, the high-order Markov model is used to predict the leading deviation zone and the trailing deviation zone, which can capture the dependency between each traveling state in the leading traveling state quantity (or the trailing traveling state quantity) and the traveling deviation degree, rather than just considering the previous state, thereby improving the prediction accuracy.

[0042] In step 105, the emergency collision avoidance zone of each driving switching point in the planned route when the target transport vehicle deviates from its position is determined through each travel collision cluster and the corresponding deviation reachable domain. The collision property of the route when the target transport vehicle deviates from its position is coupled in time and space through each emergency collision avoidance zone to obtain the collision risk value between the target transport vehicle and each conflicting transport vehicle.

[0043] In some embodiments, the emergency collision avoidance zone of each driving switching point in the planned travel route when the target transport vehicle deviates from the position is determined by each travel collision cluster and the corresponding deviation reachable domain, referring to Figure 3 As described above, the figure is a schematic diagram of a process for determining an emergency collision avoidance zone in some embodiments of the present application. In this embodiment, determining the emergency collision avoidance zone can be implemented by the following steps: In step 1051, for each driving switching point in the planned route, a deviation reachable domain of the driving switching point after position deviation is obtained; In step 1052, a cooperative zone for avoiding collision between the target transport vehicle at the driving switching point and each conflicting transport vehicle is determined by using the deviation reachable domain and each travel collision value in the travel collision cluster; In step 1053, the emergency collision avoidance zone of the driving switching point after the position deviation is determined through all the cooperative areas, and then the emergency collision avoidance zone of each driving switching point in the planned route when the target transport vehicle deviates from the position is obtained.

[0044] It should be noted that, in the present application, the emergency collision avoidance zone represents the traversable area used by the target transport vehicle to avoid collision at each drive switching point; in specific implementation, first, for each drive switching point in the planned route, the deviation reachable domain of the drive switching point after the position deviation is obtained; then, a conflicting transport vehicle is selected, and the travel collision value of the conflicting transport vehicle at the drive switching point with the target transport vehicle is obtained. If the travel collision value is less than the preset risk threshold, the deviation reachable domain is used as the cooperative zone for the target transport vehicle to avoid collision between the drive switching point and the conflicting transport vehicle. If the travel collision value is greater than or equal to the preset risk threshold value, then the difference between the traveling collision value and the risk threshold and the difference between the risk threshold are used as the adjustment coefficient, and the deviation from the reachable domain is increased by the adjustment coefficient. The increased deviation from the reachable domain can be used as the cooperative area for the target transport vehicle to avoid collision between the driving switching point and the conflicting transport vehicle. The above steps are repeated to obtain the cooperative area for the target transport vehicle to avoid collision between the driving switching point and each conflicting transport vehicle; finally, all the cooperative areas can be merged as the emergency collision avoidance area after the driving switching point deviates from the position. The emergency collision avoidance area of ​​each driving switching point in the planned route after the position deviation can be obtained in the above manner.

[0045] In some embodiments, the collision risk value between the target transport vehicle and each conflicting transport vehicle is obtained by performing spatiotemporal synergistic coupling of the collision risk of the target transport vehicle when the target transport vehicle deviates from the position through each emergency collision avoidance zone, and the following steps can be used to achieve the result: For each conflicting transport vehicle, the conflicting spatial domain of the conflicting transport vehicle arriving at each emergency collision avoidance zone is obtained, and then the conflicting time window of the conflicting transport vehicle arriving at each emergency collision avoidance zone is determined; Determine the conflicting road sections of the target transport vehicle within each conflict time window; Determine the conflict time period of the target transport vehicle when it reaches each conflict space domain; Each conflicting spatial domain is coupled and compared with the corresponding conflicting road section to obtain the spatial coupling degree of each emergency collision avoidance zone; Each conflict time window is coupled and compared with the corresponding conflict time period to obtain the time coupling degree of each emergency collision avoidance zone; The collision risk value between the target transport vehicle and the conflicting transport vehicle is determined according to the spatial coupling degree and the temporal coupling degree, and then the collision risk value between the target transport vehicle and each conflicting transport vehicle is obtained.

[0046] It should be noted that the collision risk value is used to characterize the possibility of a collision between the target transport vehicle and the conflicting transport vehicle. The larger the collision risk value, the lower the possibility of a collision between the target transport vehicle and the conflicting transport vehicle. The temporal coupling degree is a quantitative value of the temporal repetition degree of the route of the target transport vehicle after the position deviation. The spatial coupling degree is a quantitative value of the spatial repetition degree of the route of the target transport vehicle after the position deviation. The conflict time period refers to the range of time required for the target transport vehicle to reach the conflicting spatial domain. The conflicting road section refers to the section that the target transport vehicle can reach after traveling within the conflicting time window. The conflicting time window refers to the conflicting time range between the conflicting transport vehicle and the target transport vehicle. The conflicting spatial domain refers to the conflicting spatial range between the conflicting transport vehicle and the target transport vehicle.

[0047] In the specific implementation, first, for each conflicting transport vehicle, obtain the preset route of the conflicting transport vehicle, select an emergency avoidance zone, and determine whether there is an interaction between the emergency avoidance zone and the preset route. If there is no interaction, the conflict time window and conflict space domain of the conflicting transport vehicle to the emergency avoidance zone are both empty. If there is an interaction, the interactive part of the emergency avoidance zone and the preset route can be used as the conflict space domain of the conflicting transport vehicle to the emergency avoidance zone. At this time, the average of all travel speeds of the conflicting transport vehicle in the preset time period (the default is 3 days) can be used as the conflict travel speed, initialize a time window, and take the ratio of the total distance of the preset route entering the conflict space domain to the conflict travel speed as the lower bound of the time window, and take the ratio of the total distance of the preset route leaving the conflict space domain to the conflict travel speed as the upper bound of the time window. The time window can be used as the conflict time window for the conflicting transport vehicle to arrive at the emergency avoidance zone. Repeat the above steps to obtain the conflict time window of the conflicting transport vehicle to each emergency avoidance zone; then, select a conflict time window, and the target transport vehicle can be The average of all the travel speeds of the transport vehicle within a preset time period (the default is 3 days) is used as the target travel speed, a trajectory interval is initialized, the product of the target travel speed and the lower bound of the conflict time window is used as the entrance running distance of the trajectory interval in the planned travel route of the target transport vehicle, and the product of the target travel speed and the upper bound of the conflict time window is used as the exit running distance of the trajectory interval in the planned travel route of the target transport vehicle. The route within the trajectory interval can be used as the conflict section within the conflict time window. Repeat the above steps to obtain the conflict section of the target transport vehicle in each conflict time window; finally, select a conflict space domain, the average of all the travel speeds of the target transport vehicle within a preset time period (the default is 3 days) can be used as the target travel speed, initialize a time window, the ratio of the total distance of the preset travel route entering the conflict space domain and the target travel speed can be used as the lower bound of the time window, the ratio of the total distance of the preset travel route leaving the conflict space domain and the target travel speed can be used as the upper bound of the time window, and the above steps are repeated to obtain the conflict time period of the target transport vehicle when reaching each conflict space domain.

[0048] In addition, in the specific implementation, first, select an emergency collision avoidance zone, obtain the conflict space domain and the corresponding conflict road section of the emergency collision avoidance zone, calculate the overlapping area of ​​the conflict space domain and the conflict road section, and the ratio of the overlapping area to the area of ​​the conflict space domain can be used as the spatial coupling degree of the emergency collision avoidance zone. Repeat the above steps to obtain the temporal coupling degree of each emergency collision avoidance zone; then, select an emergency collision avoidance zone, obtain the conflict time window and the corresponding conflict time period of the emergency collision avoidance zone, and the ratio of the overlapping window length to the conflict time window length can be used as the temporal coupling degree of the emergency collision avoidance zone. Repeat the above steps to obtain The time coupling degree of each emergency collision avoidance zone; finally, the product of the spatial coupling degree and the temporal coupling degree can be used as the collision risk value between the target transport vehicle and the conflicting transport vehicle. In other embodiments, other methods can also be used to determine the collision risk value between the target transport vehicle and the conflicting transport vehicle by using the spatial coupling degree and the temporal coupling degree. It is only necessary to ensure that the greater the spatial coupling degree, the greater the collision risk value and the greater the temporal coupling degree, the greater the collision risk value. Different calculation methods of the collision risk value also determine the setting method of the subsequent collision threshold, which is not limited here. The collision risk value between the target transport vehicle and each conflicting transport vehicle can be obtained by the above method.

[0049] In step 106, when the target transport vehicle is transporting along the planned route, collision avoidance is performed for each driving switching point in the planned route according to all collision risk values ​​and each deviation reachable domain.

[0050] In some embodiments, collision avoidance for each driving switching point in the planned route according to all collision risk values ​​and each deviation from the reachable domain may be implemented by the following steps: For each driving switching point in the planned travel route, obtaining a deviation reachable domain of the driving switching point after the position deviation; All collision risk vehicles at the driving switching point are screened out from all conflicting vehicles through all collision risk values ​​and deviation from the reachable domain; Collision avoidance is performed on each transport vehicle with a collision risk, collision avoidance of the driving switching point is completed, and collision avoidance of each driving switching point in the planned route is further completed.

[0051] In the specific implementation, first, for each driving switching point in the planned route, the deviation reachable domain of the driving switching point after the position deviation is obtained; then, all the conflicting transport vehicles that satisfy both the preset route deviation from the reachable domain and the collision risk value higher than the collision threshold can be used as all the collision risk transport vehicles of the driving switching point; finally, the existing collision avoidance algorithm can be used, and the planned route of the target transport vehicle is used as the position to be avoided in the collision avoidance algorithm, and collision avoidance is performed on each collision risk transport vehicle to complete the collision avoidance of the driving switching point. The collision avoidance of each driving switching point in the planned route can be completed in the above manner, wherein collision avoidance can be performed in a variety of ways, such as: emergency braking, avoidance path and speed adjustment, emergency braking refers to the target transport vehicle immediately taking emergency braking measures; avoidance path refers to planning a new avoidance path to enable the target transport vehicle to bypass obstacles; speed adjustment refers to changing the relative position of the target transport vehicle and the conflicting transport vehicle by acceleration or deceleration.

[0052] In the present application, when the target transport vehicle is transporting along the planned route, collision avoidance is performed on each drive switching point in the planned route according to all collision risk values ​​and each deviation reachable domain; wherein, by determining the deviation reachable domain of each drive switching point in the planned route after the position deviation, the regional range of each drive switching point of the target transport vehicle after the position deviation can be obtained. The above process determines the travel collision cluster of the target transport vehicle at each drive switching point based on the preset route of the conflicting vehicle, and can analyze the potential risk of each drive switching point in more detail, thereby improving the accuracy of risk assessment, and further improving the effectiveness of route adjustment of the target transport vehicle. The use of historical data for deviation prediction can comprehensively consider the travel deviation of unmanned coal mine transport vehicles under dynamic uncertain scenarios, thereby effectively reducing unforeseen deviations, improving the accuracy of prediction, and further improving the real-time efficiency of the route of unmanned coal mine transport vehicles; then, determine the target The collision risk value between the transport vehicle and each conflicting transport vehicle can be used to obtain the probability of collision between the target transport vehicle and each conflicting transport vehicle. The above process determines the emergency collision avoidance zone of each drive switching point after position deviation through the traveling collision cluster and the deviation reachable domain, and clarifies the collision avoidance area, which is convenient for subsequent targeted collision avoidance operations on the coal mine unmanned transport vehicle. The delineation of the collaborative collision avoidance area makes the collision avoidance strategy more targeted, thereby improving the effectiveness of collision avoidance measures in dynamic uncertain scenarios. The collision risk value is calculated through spatiotemporal collaborative coupling, which can more comprehensively evaluate the risk and ensure the comprehensiveness and effectiveness of the collision avoidance strategy in dynamic uncertain scenarios. Finally, by dynamically adjusting the route, the collision risk can be minimized and the driving safety of the transport vehicle can be improved. In summary, based on the above scheme, spatiotemporal collaborative collision avoidance of coal mine unmanned transport vehicles in dynamic uncertain scenarios can be realized, thereby improving the real-time and high efficiency of the coal mine unmanned transport vehicle's route.

[0053] In addition, in another aspect of the present application, in some embodiments, the present application provides a coal mine unmanned transport vehicle collaborative control system, the coal mine unmanned transport vehicle collaborative control system also includes a collaborative control unit, reference Figure 4 , which is a schematic diagram of exemplary hardware and / or software of a collaborative control unit according to some embodiments of the present application, the collaborative control unit includes: an acquisition module 201, a processing module 202 and an execution module 203, which are described as follows: Acquisition module 201, in this application, acquisition module 201 is mainly used to select a plug-in hybrid driven coal mine unmanned transport vehicle as a target transport vehicle, and then determine the initial travel state and planned travel route of the target transport vehicle; Processing module 202, in the present application, the processing module 202 is used to screen out all conflicting transport vehicles from all coal mine unmanned transport vehicles according to the initial traveling state, and then determine the cooperative driving relationship between the conflicting transport vehicles; It should be noted that the processing module 202 is also used to determine all driving switching points in the planned travel route, and determine the travel collision cluster of each driving switching point of the target transport vehicle in the planned travel route through the preset travel routes of each conflicting transport vehicle and the cooperative driving relationship; In addition, the processing module 202 is also used to obtain historical transportation data of the target transport vehicle, determine the travel deviation of the target transport vehicle through the historical transportation data, and predict the position deviation of each driving switching point in the planned travel route according to the travel deviation and the collaborative driving relationship to obtain the deviation reachable domain of each driving switching point after the position deviation; In addition, the processing module 202 is further used to determine the emergency collision avoidance zone of each driving switching point in the planned route when the target transport vehicle deviates from its position through each travel collision cluster and the corresponding deviation reachable domain, and to perform spatiotemporal collaborative coupling on the collision of the route when the target transport vehicle deviates from its position through each emergency collision avoidance zone, so as to obtain the collision risk value between the target transport vehicle and each conflicting transport vehicle; The execution module 203 in the present application is mainly used to perform collision avoidance for each driving switching point in the planned route according to all collision risk values ​​and each deviation from the reachable domain when the target transport vehicle is transporting along the planned route.

[0054] The above describes in detail the examples of the method and system for collaborative control of unmanned coal mine transport vehicles provided in the embodiments of the present application. It can be understood that in order to realize the above functions, the corresponding device includes hardware structures and / or software modules corresponding to the execution of each function. It should be easily appreciated by those skilled in the art that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0055] In some embodiments, the present application also provides a computer device, which includes a memory and a processor, the memory is used to store computer programs, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned coal mine unmanned transport vehicle collaborative control method.

[0056] In some embodiments, reference Figure 5 , the dotted line in the figure indicates that the unit or module is optional, and the figure is a structural schematic diagram of a computer device for implementing a method for collaboratively controlling coal mine unmanned transport vehicles according to an embodiment of the present application. The method for collaboratively controlling coal mine unmanned transport vehicles described in the above embodiment can be Figure 5 The computer device shown in the figure is implemented, and the computer device includes at least one processor 301, a memory 302 and at least one communication unit 305. The computer device can be a terminal device, a server or a chip.

[0057] The processor 301 may be a general-purpose processor or a special-purpose processor. For example, the processor 301 may be a central processing unit (CPU), which may be used to control the computer device, execute software programs, and process data of the software programs. The computer device may also include a communication unit 305 to implement signal input (reception) and output (transmission).

[0058] For example, the computer device may be a chip, the communication unit 305 may be an input and / or output circuit of the chip, or the communication unit 305 may be a communication interface of the chip, and the chip may be a component of a terminal device, a network device, or other devices.

[0059] For another example, the computer device may be a terminal device or a server, and the communication unit 305 may be a transceiver of the terminal device or the server, or the communication unit 305 may be a transceiver circuit of the terminal device or the server.

[0060] The computer device may include one or more memories 302, on which a program 304 is stored. The program 304 can be executed by the processor 301 to generate instructions 303, so that the processor 301 performs the method described in the above method embodiment according to the instructions 303. Optionally, data (such as a target audit model) can also be stored in the memory 302. Optionally, the processor 301 can also read the data stored in the memory 302, and the data can be stored at the same storage address as the program 304, or the data can be stored at a different storage address from the program 304.

[0061] The processor 301 and the memory 302 may be provided separately or integrated together, for example, integrated on a system on chip (SOC) of the terminal device.

[0062] It should be understood that each step of the above method embodiment can be completed by a hardware-based logic circuit or software-based instructions in the processor 301. The processor 301 can be a CPU, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, such as discrete gates, transistor logic devices, or discrete hardware components.

[0063] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0064] For example, in some embodiments, the present application also provides a computer-readable storage medium, in which instructions or codes are stored. When the instructions or codes are run on a computer, the computer implements the above-mentioned coal mine unmanned transport vehicle collaborative control method when executed.

[0065] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0066] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for cooperative control of unmanned transport vehicles in coal mines, characterized in that: The steps include: A plug-in hybrid-driven coal mine unmanned transport vehicle is selected as the target transport vehicle, and then the initial travel state and planned travel route of the target transport vehicle are determined; According to the initial traveling state, all conflicting transport vehicles are selected from all coal mine unmanned transport vehicles, and then the cooperative driving relationship between the conflicting transport vehicles is determined; Determine all driving switching points in the planned route, and determine the travel collision cluster of the target transport vehicle at each driving switching point in the planned route through the preset travel routes of each conflicting transport vehicle and the cooperative driving relationship; Acquire historical transportation data of the target transport vehicle, determine the travel deviation of the target transport vehicle through the historical transportation data, perform position deviation prediction for each drive switching point in the planned travel route according to the travel deviation and the collaborative driving relationship, and obtain a deviation reachable domain of each drive switching point after the position deviation; Determine the emergency collision avoidance zone of each driving switching point in the planned route when the target transport vehicle deviates from its position through each travel collision cluster and the corresponding deviation reachable domain, and perform spatiotemporal collaborative coupling on the collision of the route when the target transport vehicle deviates from its position through each emergency collision avoidance zone to obtain a collision risk value between the target transport vehicle and each conflicting transport vehicle; When the target transport vehicle is transporting along the planned route, collision avoidance is performed on each driving switching point in the planned route according to all collision risk values ​​and each deviation reachable domain.

2. The method according to claim 1, characterized in that Screening out all conflicting transport vehicles from all coal mine unmanned transport vehicles according to the initial traveling state specifically includes: Determining the travel acceleration and travel angular velocity of the target transport vehicle through the initial travel state; Determining a travel conflict range of the target transport vehicle according to the travel acceleration and the travel angular velocity; Get the current travel status of each coal mine unmanned transport vehicle; All coal mine unmanned transport vehicles are subjected to conflict screening according to each current travel state and the travel conflict range, so as to obtain all conflicting transport vehicles.

3. The method according to claim 1, characterized in that Determining the travel collision cluster of each drive switching point of the target transport vehicle in the planned travel route through the preset travel routes of each conflicting transport vehicle and the cooperative driving relationship specifically includes: For each driving switching point in the planned travel route, determining a risk time period for the target transport vehicle to reach the driving switching point through the planned travel route; Determine the risky travel route of the corresponding conflicting transport vehicle within the risky time period through each preset travel route; Determine the travel collision value between the corresponding conflicting transport vehicle and the target transport vehicle at the drive switching point according to each risk travel route and the cooperative driving relationship; The traveling collision cluster of the driving switching point is determined based on all the traveling collision values, and then the traveling collision cluster of each driving switching point in the planned traveling route is obtained.

4. The method according to claim 1, characterized in that Determining the travel deviation of the target transport vehicle through the historical transport data specifically includes: For each historical transportation process of the target transport vehicle, obtaining the actual travel route and the planned route of the historical transportation process from the historical transportation data; Compare the deviation of each driving switching point of the planned route with the corresponding actual driving switching point in the actual travel route to obtain the deviation value of each driving switching point; Determine the route deviation value of the target transport vehicle in the historical transportation process through all the deviation values, and then obtain the route deviation value of the target transport vehicle in each historical transportation process; The travel deviation degree of the target transport vehicle is determined based on all route deviation values.

5. The method according to claim 1, characterized in that Predicting the position deviation of each driving switching point in the planned traveling route according to the traveling deviation degree and the cooperative driving relationship to obtain the deviation reachable domain of each driving switching point after the position deviation specifically includes: For each driving switching point in the planned traveling route, obtaining the traveling state before the driving switching point in the planned traveling route as a preceding traveling state quantity; The position before the driving switching point is predicted by the preceding traveling state quantity, the coordinated driving relationship and the traveling deviation degree to obtain a preceding deviation area; Acquiring a travel state after a driving switching point in the planned travel route as a post-travel state quantity; The position after the driving switching point is predicted by the post-travel state quantity, the coordinated driving relationship and the travel deviation degree to obtain a post-travel deviation area; The deviation reachable domain of the driving switching point after the position deviation is determined according to the leading deviation zone and the trailing deviation zone, and then the deviation reachable domain of each driving switching point after the position deviation is obtained.

6. The method according to claim 1, characterized in that Determining the emergency collision avoidance zone of each driving switching point in the planned traveling route when the target transport vehicle deviates from its position through each traveling collision cluster and the corresponding deviation reachable domain specifically includes: For each driving switching point in the planned travel route, obtaining a deviation reachable domain of the driving switching point after the position deviation; Determine a collision-avoiding cooperation zone between the target transport vehicle and each conflicting transport vehicle at a driving switching point by using the deviation reachable domain and each travel collision value in the travel collision cluster; The emergency collision avoidance zone after the position deviation of the driving switching point is determined through all the cooperative zones, and then the emergency collision avoidance zone of each driving switching point in the planned route when the target transport vehicle has a position deviation is obtained.

7. The method according to claim 1, characterized in that The conflict transport vehicle is a plug-in hybrid driven unmanned coal mine transport vehicle.

8. A coal mine unmanned transport vehicle collaborative control system, the coal mine unmanned transport vehicle collaborative control system includes a collaborative control unit, characterized in that: The collaborative control unit comprises: An acquisition module is used to select a plug-in hybrid-driven coal mine unmanned transport vehicle as a target transport vehicle, and then determine the initial travel state of the target transport vehicle and plan the travel route; A processing module, used for screening out all conflicting transport vehicles from all coal mine unmanned transport vehicles according to the initial traveling state, and then determining the cooperative driving relationship between the conflicting transport vehicles; The processing module is also used to determine all driving switching points in the planned travel route, and determine the travel collision cluster of the target transport vehicle at each driving switching point in the planned travel route through the preset travel routes of each conflicting transport vehicle and the cooperative driving relationship; The processing module is also used to obtain historical transportation data of the target transport vehicle, determine the travel deviation of the target transport vehicle through the historical transportation data, and predict the position deviation of each drive switching point in the planned travel route according to the travel deviation and the cooperative driving relationship to obtain the deviation reachable domain of each drive switching point after the position deviation; The processing module is also used to determine the emergency collision avoidance zone of each driving switching point in the planned route when the target transport vehicle deviates from its position through each travel collision cluster and the corresponding deviation reachable domain, and to perform spatiotemporal collaborative coupling on the collision of the route when the target transport vehicle deviates from its position through each emergency collision avoidance zone, so as to obtain the collision risk value between the target transport vehicle and each conflicting transport vehicle; The execution module is used to perform collision avoidance for each driving switching point in the planned route according to all collision risk values ​​and each deviation reachable domain when the target transport vehicle is transporting along the planned route.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the coal mine unmanned transport vehicle collaborative control method described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions or codes, and when the instructions or codes are executed on a computer, the computer implements the method for collaborative control of unmanned mine transport vehicles as described in any one of claims 1 to 7.

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