Underground vehicle path planning method based on mine environment monitoring

Abstract

The invention discloses an underground vehicle path planning method based on mine environment monitoring. The method comprises the following steps: S1, acquiring a starting point position and a final point position of a target vehicle; s2, acquiring underground available roadway information, and performing path planning by combining the starting point position and the final point position of the target vehicle to generate optimal path information; s3, guiding the target vehicle to run in an underground roadway based on the optimal path information; s4, the real-time position of the target vehicle in the well is obtained, and whether the target vehicle yaws or not is judged in combination with the optimal path information; meanwhile, monitoring an underground environment, and judging whether available roadway information is updated or not; s5, re-performing path planning based on the real-time position of the target vehicle or the updated available roadway information to generate new optimal path information, and returning to the step S3; and S6, repeatedly executing the steps S3 to S5 until the target vehicle arrives at the final position. According to the invention, the accuracy and flexibility of underground vehicle path planning can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of underground vehicle management, and in particular to an underground vehicle path planning method based on mine environment monitoring. Background Art

[0002] In mining, underground vehicles play a vital role in transporting ore, materials and personnel in narrow, complex and changeable underground environments. However, due to the particularity of the underground environment, such as limited space, insufficient light, and complex geological conditions, the scheduling and path planning of underground vehicles has become an extremely challenging task.

[0003] There are many types of underground vehicles, including mining dump trucks, trams, and loaders, which are responsible for the mining and transportation of ore and the handling of underground equipment. Underground, these vehicles need to shuttle through narrow tunnels, facing rugged roads, complex geological structures, and emergencies that may occur at any time. And because of the limited space underground, vehicles often need to avoid frequently when driving, which not only reduces transportation efficiency, but also increases safety hazards. In addition, there is insufficient light underground and limited vision. Drivers need to rely on headlights and experience to judge the road conditions ahead, which undoubtedly increases the difficulty of driving and the risk of accidents. Furthermore, the geological conditions underground are complex, and there may be potential dangers such as landslides and water seepage, which places extremely high demands on the performance of the vehicle and the driver's ability to respond.

[0004] Faced with the challenges of underground vehicle operation, path planning is particularly important. Path planning refers to planning an optimal driving path for underground vehicles based on the characteristics of the underground environment and the needs of vehicle transportation. This planning process not only considers the shortest distance of the path, but also comprehensively considers multiple factors such as road conditions, emergencies, and traffic flow, aiming to maximize transportation efficiency while ensuring safety. Therefore, how to design a path planning method for underground vehicles is a technical problem that needs to be solved urgently. Summary of the invention

[0005] In view of the deficiencies of the above-mentioned prior art, the technical problem to be solved by the present invention is: how to provide an underground vehicle path planning method based on mine environment monitoring, and perform path planning based on the available tunnel information underground, so as to adapt to the complex and changeable environment underground; at the same time, detect the driving conditions of the underground vehicle and re-plan the path when the vehicle deviates, so as to flexibly respond to sudden changes in the underground environment, and ensure that the vehicle can always travel along the optimal path, thereby improving the accuracy and flexibility of underground vehicle path planning.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0007] A method for underground vehicle path planning based on mine environment monitoring, comprising:

[0008] S1: Get the starting position and end position of the target vehicle;

[0009] S2: Obtain the available tunnel information in the mine, and perform path planning based on the starting position and end position of the target vehicle to generate the optimal path information;

[0010] S3: guiding the target vehicle to travel in the tunnel underground based on the optimal path information;

[0011] S4: Obtain the real-time position of the target vehicle in the mine, and determine whether the target vehicle deviates in combination with the optimal path information; at the same time, monitor the mine environment to determine whether the available lane information is updated; when the target vehicle deviates or the available lane information is updated, execute step S5;

[0012] S5: re-planning the path based on the real-time position of the target vehicle or the updated available lane information to generate new optimal path information, and returning to step S3;

[0013] S6: Repeat steps S3 to S5 until the target vehicle reaches the end position.

[0014] Preferably, in step S2, the optimal path information includes any one or more of the least congested path, the shortest time path, the least traffic light path and the shortest distance path.

[0015] Preferably, in step S2, the least congested path is generated by the following steps:

[0016] S201: Generate a plurality of reachable paths based on the starting position and the end position of the target vehicle combined with available lane information; the reachable paths are composed of one or more lanes;

[0017] S202: Obtain vehicle information of vehicles traveling on each reachable path;

[0018] S203: Calculating a corresponding congestion coefficient based on vehicle information of vehicles traveling on each reachable path;

[0019] S204: Selecting a reachable path with the smallest congestion coefficient as the least congested path.

[0020] Preferably, in step S203, the congestion coefficient of the reachable path is calculated by the following formula:

[0021]

[0022] Where: j represents the congestion coefficient of the jth accessible path; m jrepresents the number of vehicles traveling in the same direction as the target vehicle on the jth reachable path; l j represents the distance between the target vehicle and the first vehicle traveling in the same direction on the jth accessible path; a is a constant; K i represents the real-time number of vehicles in the waiting area of ​​the i-th traffic light at the current moment; J i represents the maximum vehicle capacity of the i-th traffic light waiting area; n j Represents the number of traffic lights on the jth reachable path.

[0023] Preferably, in step S2, the shortest time path is generated by the following steps:

[0024] S211: Generate a plurality of reachable paths based on the starting position and the end position of the target vehicle combined with the available lane information; the reachable paths are composed of one or more lanes;

[0025] S212: Obtain vehicle information of vehicles traveling on each reachable path;

[0026] S213: For each reachable path, the travel time of the target vehicle is calculated by the following steps:

[0027] S2131: taking the vehicle traveling in the same direction as the target vehicle on the achievable path as a reference vehicle;

[0028] S2132: Calculate the departure position and departure time of the reference vehicle on the current achievable path according to the real-time position, terminal position and travel speed of the reference vehicle;

[0029] S2133: Calculate the arrival time of the target vehicle at the departure position of the reference vehicle according to the starting position and the driving speed of the target vehicle;

[0030] S2134: judging whether the target vehicle has followed the vehicle according to the arrival time of the target vehicle and the departure time of the reference vehicle: if following the vehicle occurs, executing step S2135; if following the vehicle does not occur, the travel time of the target vehicle on the reachable path = the length of the reachable path / the travel speed of the target vehicle;

[0031] S2135: Calculating the following starting positions of the target vehicle and the reference vehicle according to the starting position and driving speed of the target vehicle and the real-time position and driving speed of the reference vehicle;

[0032] S2136: Calculate the following vehicle start time t1 based on the distance between the starting position of the target vehicle and the following vehicle start position in combination with the driving speed of the target vehicle;

[0033] S2137: Calculate the following vehicle time t2 according to the distance between the following vehicle start position and the leaving position of the reference vehicle in combination with the driving speed of the reference vehicle;

[0034] S2138: Calculate the remaining travel time t3 based on the distance between the starting position of the following vehicle and the end position of the target vehicle and the driving speed of the target vehicle;

[0035] S2139: The travel time of the target vehicle on the reachable path = (t1+t2+t3)(1+λ); wherein λ represents the congestion coefficient of the reachable path;

[0036] S214: Selecting a reachable path with the shortest travel time for the target vehicle as the shortest time path.

[0037] Preferably, in step S2, the minimum traffic light path is generated by the following steps:

[0038] S221: Generate a plurality of reachable paths based on the starting position and the end position of the target vehicle combined with the available lane information; the reachable paths are composed of one or more lanes;

[0039] S222: Obtain the number of traffic lights on each reachable path;

[0040] S223: Select a reachable path with the least number of traffic lights as the minimum traffic light path.

[0041] Preferably, in step S2, the shortest distance path is generated by using the Dijkstra algorithm;

[0042] The processing steps of Dijkstra's algorithm are as follows:

[0043] S231: constructing a weighted undirected graph based on the connection relationship of all underground lanes and the length of each lane; the nodes in the weighted undirected graph represent lane intersections or key points, the edges represent lanes, and the weight of the edges is the length of the lanes;

[0044] S232: Create a set containing all nodes, and divide the set into an unvisited node set and a visited node set;

[0045] S233: Create a distance array and a predecessor node array for each node; the distance array is used to record the shortest distance from the starting position to the node; the predecessor node array is used to record the path information, that is, the predecessor node of each node;

[0046] S234: Select a node closest to the starting point from the unvisited node set as the current node, and move it from the unvisited set to the visited set;

[0047] S235: traverse all neighbor nodes of the current node;

[0048] S236: For each neighbor node, calculate the path length from the current node to the neighbor node; if the new path length is less than the shortest path length currently recorded by the neighbor node, update the shortest path length of the neighbor node, and update the predecessor node to the current node;

[0049] S237: Repeat steps S234 to S236 until the unvisited node set is empty;

[0050] S238: Starting from the end node, backtracking through the predecessor node array until reaching the starting position, the backtracking process will record all nodes on the path to form the shortest path from the starting position to the end position;

[0051] S239: The shortest path formed is used as the shortest distance path.

[0052] Preferably, in step S5, the real-time position of the target vehicle is used as the new starting position; based on the new starting position and the original end position of the target vehicle combined with the available lane information, the path planning is re-performed to generate new optimal path information, and then return to step S3.

[0053] Preferably, in step S5, when the driver of the target vehicle changes the destination position, the real-time position of the target vehicle is used as the new starting position, and the changed destination position is used as the new destination position; based on the new starting position and destination position of the target vehicle combined with the available lane information, the path planning is re-performed to generate new optimal path information, and then return to step S3.

[0054] Preferably, in step S5, when the available lane information is updated, the real-time position of the target vehicle is used as the new starting position, and the updated available lane information is used as the new available lane information; based on the new starting position and the original end position of the target vehicle combined with the new available lane information, the path planning is re-performed to generate new optimal path information, and then return to step S3.

[0055] Compared with the prior art, the underground vehicle path planning method based on mine environment monitoring in the present invention has the following beneficial effects:

[0056] The present invention obtains the available lane information underground and performs path planning in combination with the starting position and the end position of the target vehicle to generate the optimal path information; at the same time, the real-time position of the target vehicle is obtained in real time and it is determined whether it is yawed, the underground environment is monitored and it is determined whether the available lane information is updated. When the vehicle is yawed or the available lane information is updated, the path planning can be re-performed to continue to guide the vehicle. Firstly, the path planning based on the available lane information underground is more adaptable to the complex and changeable environment underground than the traditional static map planning, thereby improving the efficiency and accuracy of the path planning of underground vehicles. Secondly, based on the guidance of the optimal path information, the vehicle can travel according to the predetermined route, which can not only reach the end position faster and more accurately, but also avoid the risk of blind exploration or mistakenly entering dangerous areas, thereby improving the safety of the path planning of underground vehicles. Finally, by acquiring the underground position of the target vehicle in real time and comparing it with the optimal path information, it is possible to promptly detect whether the vehicle deviates from the scheduled route, and by monitoring the underground environment, it is possible to determine whether the available lane information is updated; at the same time, when the vehicle deviates or the available lane information is updated, the path planning can be re-performed based on the real-time position of the vehicle or the updated available lane information to generate new optimal path information. This dynamic adjustment capability enables the path planning method to flexibly respond to sudden changes in the underground environment (such as the driver taking the wrong road or changing the terminal location, lane closure, obstacle appearance, etc.), ensuring that the vehicle can always travel along the optimal path, thereby improving the accuracy and flexibility of underground vehicle path planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to make the purpose, technical solution and advantages of the invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings, in which:

[0058] Figure 1 This is the logical block diagram of the underground vehicle path planning method based on mine environment monitoring. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions 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 part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but only represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0060] It should be noted that similar numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. In the description of the present invention, it should be noted that the orientation or position relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside", etc. is based on the orientation or position relationship shown in the drawings, or the orientation or position relationship in which the invention product is usually placed when used, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. In addition, the terms "first", "second", "third", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance. In addition, the terms "horizontal", "vertical", etc. do not mean that the components are required to be absolutely horizontal or suspended, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted. In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0061] The following is a further detailed description through specific implementation methods:

[0062] Example:

[0063] This embodiment discloses a method for underground vehicle path planning based on mine environment monitoring.

[0064] like Figure 1 As shown, the underground vehicle path planning method based on mine environment monitoring includes:

[0065] S1: Get the starting position and end position of the target vehicle;

[0066] S2: Obtain the available tunnel information in the mine, and perform path planning based on the starting position and end position of the target vehicle to generate the optimal path information;

[0067] S3: guiding the target vehicle to travel in the tunnel underground based on the optimal path information;

[0068] S4: Obtain the real-time position of the target vehicle in the mine, and determine whether the target vehicle deviates in combination with the optimal path information; at the same time, monitor the mine environment to determine whether the available lane information is updated; when the target vehicle deviates or the available lane information is updated, execute step S5;

[0069] S5: re-planning the path based on the real-time position of the target vehicle or the updated available lane information to generate new optimal path information, and returning to step S3;

[0070] S6: Repeat steps S3 to S5 until the target vehicle reaches the end position.

[0071] The present invention obtains the available lane information underground and performs path planning in combination with the starting position and the end position of the target vehicle to generate the optimal path information; at the same time, the real-time position of the target vehicle is obtained in real time and it is determined whether it is yawed, the underground environment is monitored and it is determined whether the available lane information is updated. When the vehicle is yawed or the available lane information is updated, the path planning can be re-performed to continue to guide the vehicle. Firstly, the path planning based on the available lane information underground is more adaptable to the complex and changeable environment underground than the traditional static map planning, thereby improving the efficiency and accuracy of the path planning of underground vehicles. Secondly, based on the guidance of the optimal path information, the vehicle can travel according to the predetermined route, which can not only reach the end position faster and more accurately, but also avoid the risk of blind exploration or mistakenly entering dangerous areas, thereby improving the safety of the path planning of underground vehicles. Finally, by acquiring the underground position of the target vehicle in real time and comparing it with the optimal path information, it is possible to promptly detect whether the vehicle deviates from the scheduled route, and by monitoring the underground environment, it is possible to determine whether the available lane information is updated; at the same time, when the vehicle deviates or the available lane information is updated, the path planning can be re-performed based on the real-time position of the vehicle or the updated available lane information to generate new optimal path information. This dynamic adjustment capability enables the path planning method to flexibly respond to sudden changes in the underground environment (such as the driver taking the wrong road or changing the terminal location, lane closure, obstacle appearance, etc.), ensuring that the vehicle can always travel along the optimal path, thereby improving the accuracy and flexibility of underground vehicle path planning.

[0072] During the specific implementation process, the optimal path information includes any one or more of the least congested path, the shortest time path, the least traffic light path and the shortest distance path.

[0073] 1. Least Congested Path

[0074] Specifically, the least congested path is generated through the following steps:

[0075] S201: Generate a plurality of reachable paths based on the starting position and the end position of the target vehicle combined with available lane information; the reachable paths are composed of one or more lanes;

[0076] In this embodiment, the reachable path refers to a set of lanes that can allow the target vehicle to reach the destination position from the starting position.

[0077] S202: Obtain vehicle information of vehicles traveling on each reachable path;

[0078] S203: Calculating a corresponding congestion coefficient based on vehicle information of vehicles traveling on each reachable path;

[0079] S204: Selecting a reachable path with the smallest congestion coefficient as the least congested path.

[0080] In step S203, the congestion coefficient of the reachable path is calculated by the following formula:

[0081]

[0082] Where: j represents the congestion coefficient of the jth accessible path, where λ j is a unitless value; m j represents the number of vehicles traveling in the same direction as the target vehicle on the jth reachable path, where m j It is a value without unit. For example, if there are ten vehicles traveling in the same direction, m j =10; l j represents the distance between the target vehicle and the first vehicle traveling in the same direction on the jth accessible path, where l j It is a value without unit. For example, when the distance is 500 meters, l j =500; a is a constant used to adjust λ j , for example, it can be set to 1000; K i represents the real-time number of vehicles in the waiting area of ​​the i-th traffic light at the current moment; J i represents the maximum vehicle capacity of the i-th traffic light waiting area; n j Represents the number of traffic lights on the jth reachable path.

[0083] The present invention generates the least congested path, so that the target vehicle can avoid waiting for a long time in the lane, thereby reducing the delay caused by congestion. And reducing congestion means that the vehicle can travel more smoothly, thereby improving the overall transportation efficiency. In addition, vehicles often need to start and brake frequently in congested conditions, which increases energy consumption. Selecting the least congested path helps to reduce this unnecessary energy consumption. In addition, the calculation formula of the congestion coefficient takes into account the number of vehicles on the path, the following distance and the congestion level of the traffic lights, so that the congestion of the path can be accurately reflected.

[0084] 2. Shortest Time Path

[0085] During the specific implementation process, there are many different types of vehicles underground, and the driving speeds of various vehicles are often different. In addition, there is generally no space for overtaking in the tunnel. When the vehicle in front is driving slowly, the vehicle behind can only slow down and follow the vehicle. Therefore, when calculating the travel time on a reachable path, you cannot simply divide the distance by the time, but also need to consider the situation of following the vehicle. In addition, different paths may share the same part of the tunnel, that is, the vehicle on the current reachable path may switch to another path at some point. Therefore, when calculating the travel time on a reachable path, it is necessary to further consider the situation of vehicle switching paths.

[0086] Specifically, the shortest time path is generated through the following steps:

[0087] S211: Generate a plurality of reachable paths based on the starting position and the end position of the target vehicle combined with the available lane information; the reachable paths are composed of one or more lanes;

[0088] S212: Obtain vehicle information of vehicles traveling on each reachable path;

[0089] S213: For each reachable path, the travel time of the target vehicle is calculated by the following steps:

[0090] S2131: taking the vehicle on the achievable path that is closest to the target vehicle and traveling in the same direction as the reference vehicle;

[0091] S2132: Calculate the departure position and departure time of the reference vehicle on the current achievable path according to the real-time position, terminal position and travel speed of the reference vehicle;

[0092] In this embodiment, when the driving paths of the reference vehicle and the target vehicle only partially overlap, the reference vehicle will leave the current reachable path of the target vehicle at a certain point in time and switch to another path. The departure position at this time refers to the switching point where the reference vehicle switches from the current reachable path to another path; departure time = the distance between the real-time position of the reference vehicle and the departure position / the driving speed of the reference vehicle. If the driving paths of the reference vehicle and the target vehicle are the same, the departure position of the reference vehicle is the terminal position of the target vehicle.

[0093] S2133: Calculate the arrival time of the target vehicle at the departure position of the reference vehicle according to the starting position and the driving speed of the target vehicle;

[0094] S2134: judging whether the target vehicle has followed the vehicle according to the arrival time of the target vehicle and the departure time of the reference vehicle: if following the vehicle occurs, executing step S2135; if following the vehicle does not occur, the travel time of the target vehicle on the reachable path = the length of the reachable path / the travel speed of the target vehicle;

[0095] S2135: Calculating the following starting positions of the target vehicle and the reference vehicle according to the starting position and driving speed of the target vehicle and the real-time position and driving speed of the reference vehicle;

[0096] S2136: Calculate the following start time t1 based on the distance between the starting position of the target vehicle and the following start position combined with the target vehicle's driving speed; in this embodiment, the following start time t1 = the distance between the starting position of the target vehicle and the following start position / the target vehicle's driving speed.

[0097] S2137: Calculate the following time t2 based on the distance between the following start position and the departure position of the reference vehicle combined with the driving speed of the reference vehicle; in this embodiment, the following time t2 = the distance between the following start position and the departure position of the reference vehicle / the driving speed of the reference vehicle.

[0098] S2138: Calculate the remaining travel time t3 based on the distance between the starting position of the following vehicle and the end position of the target vehicle combined with the driving speed of the target vehicle; in this embodiment, the remaining travel time t3 = the distance between the starting position of the following vehicle and the end position of the target vehicle / the driving speed of the target vehicle.

[0099] S2139: The travel time of the target vehicle on the reachable path = (t1+t2+t3)(1+λ); wherein λ represents the congestion coefficient of the reachable path;

[0100] In this embodiment, if there are other vehicles traveling in the same direction as the target vehicle on the current reachable path after the reference vehicle leaves the current reachable path, then return to S2131 and take the vehicle traveling in the same direction that is closest to the target vehicle among the other vehicles as the reference vehicle, and continue to execute S2132 and subsequent steps, and finally add up all the times to calculate the travel time of the target vehicle on the reachable path.

[0101] S214: Selecting a reachable path with the shortest travel time for the target vehicle as the shortest time path.

[0102] The present invention generates the shortest time path so that the target vehicle can reach the end point (destination) as soon as possible, thereby ensuring the operating efficiency of the underground vehicle. At the same time, in the process of calculating the driving time of the target vehicle, the present invention fully considers the situation that other vehicles in front of the target vehicle need to follow the vehicle when the driving speed is too slow, and the situation that other vehicles in front of the target vehicle need to switch paths, so that it can better cope with the actual situation of the underground environment, and then accurately calculate the driving time of the target vehicle, and can improve the operating efficiency of the underground vehicle by selecting the shortest time path. In addition, when generating the shortest time path, the present invention combines the congestion situation (coefficient) of the path, better considers the future trend of underground traffic, foresees and copes with potential traffic congestion, thereby improving the accuracy of the shortest time path generation.

[0103] 3. The least traffic light path

[0104] Specifically, the minimum traffic light path is generated through the following steps:

[0105] S221: Generate a plurality of reachable paths based on the starting position and the end position of the target vehicle combined with the available lane information; the reachable paths are composed of one or more lanes;

[0106] S222: Obtain the number of traffic lights on each reachable path;

[0107] S223: Select a reachable path with the least number of traffic lights as the minimum traffic light path.

[0108] The present invention can reduce the waiting time of the target vehicle in the traffic light area by generating the minimum traffic light path, and reducing the waiting time means that the vehicle can pass through the key area more quickly, thereby improving the traffic efficiency of the entire underground mine. In addition, the waiting area is often a high-incidence point for accidents, and reducing the waiting time helps to reduce the accident risk of underground vehicles.

[0109] 4. Shortest Path

[0110] Specifically, the shortest distance path is generated by Dijkstra's algorithm;

[0111] The processing steps of Dijkstra's algorithm are as follows:

[0112] S231: constructing a weighted undirected graph based on the connection relationship of all underground lanes and the length of each lane; the nodes in the weighted undirected graph represent lane intersections or key points, the edges represent lanes, and the weight of the edges is the length of the lanes;

[0113] S232: Create a set containing all nodes, and divide the set into an unvisited node set (usually initialized to all nodes) and a visited node set (initialized to be empty);

[0114] S233: Create a distance array and a predecessor node array for each node; the distance array is used to record the shortest distance from the starting point to the node. Initially, the distance of the starting point node is 0, and the distances of the remaining nodes are infinite (or a sufficiently large value to indicate unreachable); the predecessor node array is used to record path information, that is, the predecessor node of each node (on the shortest path), which is used for backtracking of the final path.

[0115] S234: Select a node closest to the starting point from the unvisited node set as the current node, and move it from the unvisited set to the visited set;

[0116] S235: traverse all neighbor nodes of the current node (i.e., nodes directly connected to it);

[0117] S236: For each neighbor node, calculate the path length from the current node to the neighbor node (the distance from the current node to the starting point plus the lane length from the current node to the neighbor node); if the new path length is less than the shortest path length currently recorded for the neighbor node, update the shortest path length of the neighbor node, and update the predecessor node to the current node;

[0118] S237: Repeat steps S234 to S236 until the unvisited node set is empty (i.e., all nodes have been visited and the shortest path has been determined);

[0119] In this embodiment, the data of the prohibited point can also be set during the path planning. After the prohibited point is added through the GIS map, the branch information where the coordinates of the prohibited point are located is first identified. When the Dijkstra algorithm is calculated, the branch path where the prohibited point is located will be marked as impassable, and the shortest path calculation process of the branch will be skipped, thereby avoiding planning the path to the location of the prohibited point and realizing the prohibited point function.

[0120] S238: Starting from the end node, backtrack through the predecessor node array until reaching the starting point. The backtracking process will record all the nodes on the path to form the shortest path from the starting point to the end point. If the shortest distance to the end point node is still infinite, it means that it is unreachable from the starting point to the end point.

[0121] S239: The shortest path formed is used as the shortest distance path.

[0122] The present invention generates the shortest path through the Dijkstra algorithm, so that the mileage of the target vehicle can be reduced, which can not only save time and energy consumption, but also reduce the wear and tear of the vehicle, which helps to extend the service life of the vehicle and reduce maintenance costs. In addition, selecting the shortest path helps to allocate resources more reasonably and ensure that key tasks can be supported in a timely manner.

[0123] In the specific implementation process, the real-time position of the target vehicle is used as the new starting position; based on the new starting position and the original end position of the target vehicle combined with the available lane information, the path planning is re-performed to generate new optimal path information, and then return to step S3.

[0124] When the target vehicle enters a yaw state, the present invention re-plans the path based on the new starting position and the original end position of the target vehicle combined with the available lane information to generate new optimal path information, so that the target vehicle can flexibly respond to sudden changes in the underground environment, ensuring that the vehicle can always travel along the optimal path, thereby improving the accuracy and flexibility of underground vehicle path planning.

[0125] During the specific implementation process, when the driver of the target vehicle changes the destination position, the real-time position of the target vehicle is used as the new starting position, and the changed destination position is used as the new destination position; based on the new starting position and destination position of the target vehicle combined with the available lane information, the path planning is re-performed to generate new optimal path information, and then return to step S3.

[0126] When the driver of the target vehicle changes the destination position, the present invention re-plans the path based on the new starting position and the destination position of the target vehicle in combination with the available lane information to generate new optimal path information, so that it is possible to cope with the emergency situation where the driver changes the destination position, and ensure that the vehicle can always travel along the optimal path, thereby improving the accuracy and flexibility of underground vehicle path planning.

[0127] During the specific implementation process, when the available lane information is updated (such as: 1. Due to temporary needs, some lanes need to be cancelled so that they cannot be used. 2. Due to temporary needs, some guide points need to be changed to stop points so that they cannot be used), the real-time position of the target vehicle is used as the new starting position, and the updated available lane information is used as the new available lane information; based on the new starting position and the original end position of the target vehicle combined with the new available lane information, the path planning is re-performed to generate new optimal path information, and return to step S3.

[0128] When the available lane information is updated, the present invention re-plans the path based on the new starting position and the original end position of the target vehicle combined with the new available lane information to generate new optimal path information, so that it can cope with emergencies caused by the update of the available lane information and ensure that the vehicle can always travel along the optimal path, thereby improving the accuracy and flexibility of underground vehicle path planning.

[0129] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit the technical solution. Those skilled in the art should understand that those modifications or equivalent substitutions of the technical solution of the present invention that do not depart from the purpose and scope of the technical solution should be included in the scope of the claims of the present invention.

Claims

1. A method for underground vehicle path planning based on mine environment monitoring, characterized in that: include: S1: Get the starting position and end position of the target vehicle; S2: Obtain the available tunnel information in the mine, and perform path planning based on the starting position and end position of the target vehicle to generate the optimal path information; S3: guiding the target vehicle to travel in the tunnel underground based on the optimal path information; S4: Obtain the real-time position of the target vehicle in the mine, and determine whether the target vehicle deviates in combination with the optimal path information; at the same time, monitor the mine environment to determine whether the available lane information is updated; when the target vehicle deviates or the available lane information is updated, execute step S5; S5: re-planning the path based on the real-time position of the target vehicle or the updated available lane information to generate new optimal path information, and returning to step S3; S6: Repeat steps S3 to S5 until the target vehicle reaches the end position.

2. The underground vehicle path planning method based on mine environment monitoring according to claim 1, characterized in that: In step S2, the optimal path information includes any one or more of the least congested path, the shortest time path, the least traffic light path and the shortest distance path.

3. The underground vehicle path planning method based on mine environment monitoring according to claim 2, characterized in that: In step S2, the least congested path is generated by the following steps: S201: Generate a plurality of reachable paths based on the starting position and the end position of the target vehicle combined with available lane information; A reachable path is composed of one or more lanes; S202: Obtain vehicle information of vehicles traveling on each reachable path; S203: Calculating a corresponding congestion coefficient based on vehicle information of vehicles traveling on each reachable path; S204: Selecting a reachable path with the smallest congestion coefficient as the least congested path.

4. The underground vehicle path planning method based on mine environment monitoring according to claim 3 is characterized in that: In step S203, the congestion coefficient of the reachable path is calculated by the following formula: Where: j represents the congestion coefficient of the jth accessible path; m j represents the number of vehicles traveling in the same direction as the target vehicle on the jth reachable path; l j represents the distance between the target vehicle and the first vehicle traveling in the same direction on the jth accessible path; a is a constant; K i represents the real-time number of vehicles in the waiting area of ​​the i-th traffic light at the current moment; J i represents the maximum vehicle capacity of the i-th traffic light waiting area; n j Represents the number of traffic lights on the jth reachable path.

5. The underground vehicle path planning method based on mine environment monitoring according to claim 3, characterized in that: In step S2, the shortest time path is generated by the following steps: S211: Generate a plurality of reachable paths based on the starting position and the end position of the target vehicle combined with the available lane information; the reachable paths are composed of one or more lanes; S212: Obtain vehicle information of vehicles traveling on each reachable path; S213: For each reachable path, the travel time of the target vehicle is calculated by the following steps: S2131: taking the vehicle traveling in the same direction as the target vehicle on the achievable path as a reference vehicle; S2132: Calculate the departure position and departure time of the reference vehicle on the current achievable path according to the real-time position, terminal position and travel speed of the reference vehicle; S2133: Calculating the arrival time of the target vehicle at the departure position of the reference vehicle according to the starting position and the driving speed of the target vehicle; S2134: judging whether the target vehicle has followed the vehicle according to the arrival time of the target vehicle and the departure time of the reference vehicle: if the target vehicle has followed the vehicle, executing step S2135; If there is no following behavior, the driving time of the target vehicle on the reachable path = the length of the reachable path / the driving speed of the target vehicle; S2135: Calculating the following starting positions of the target vehicle and the reference vehicle according to the starting position and driving speed of the target vehicle and the real-time position and driving speed of the reference vehicle; S2136: Calculate the following vehicle start time t1 based on the distance between the starting position of the target vehicle and the following vehicle start position in combination with the driving speed of the target vehicle; S2137: Calculate the following vehicle time t2 according to the distance between the following vehicle start position and the leaving position of the reference vehicle in combination with the driving speed of the reference vehicle; S2138: Calculate the remaining travel time t3 based on the distance between the starting position of the following vehicle and the end position of the target vehicle and the driving speed of the target vehicle; S2139: The travel time of the target vehicle on the reachable path = (t1+t2+t3)(1+λ); wherein λ represents the congestion coefficient of the reachable path; S214: Selecting a reachable path with the shortest travel time for the target vehicle as the shortest time path.

6. The underground vehicle path planning method based on mine environment monitoring according to claim 2, characterized in that: In step S2, the minimum traffic light path is generated by the following steps: S221: Generate a plurality of reachable paths based on the starting position and the end position of the target vehicle combined with the available lane information; the reachable paths are composed of one or more lanes; S222: Obtain the number of traffic lights on each reachable path; S223: Select a reachable path with the least number of traffic lights as the minimum traffic light path.

7. The underground vehicle path planning method based on mine environment monitoring according to claim 2, characterized in that: In step S2, the shortest distance path is generated by using the Dijkstra algorithm; The processing steps of Dijkstra's algorithm are as follows: S231: constructing a weighted undirected graph based on the connection relationship of all underground lanes and the length of each lane; the nodes in the weighted undirected graph represent lane intersections or key points, the edges represent lanes, and the weight of the edges is the length of the lanes; S232: Create a set containing all nodes, and divide the set into an unvisited node set and a visited node set; S233: Create a distance array and a predecessor node array for each node; the distance array is used to record the shortest distance from the starting position to the node; the predecessor node array is used to record the path information, that is, the predecessor node of each node; S234: Select a node closest to the starting point from the unvisited node set as the current node, and move it from the unvisited set to the visited set; S235: traverse all neighbor nodes of the current node; S236: For each neighbor node, calculate the path length from the current node to the neighbor node; if the new path length is less than the shortest path length currently recorded by the neighbor node, update the shortest path length of the neighbor node, and update the predecessor node to the current node; S237: Repeat steps S234 to S236 until the unvisited node set is empty; S238: Starting from the end node, backtracking through the predecessor node array until reaching the starting position, the backtracking process will record all nodes on the path to form the shortest path from the starting position to the end position; S239: The shortest path formed is used as the shortest distance path.

8. The underground vehicle path planning method based on mine environment monitoring according to claim 1, characterized in that: In step S5, the real-time position of the target vehicle is used as the new starting position; Based on the new starting position and the original end position of the target vehicle combined with the available lane information, the path planning is re-performed to generate new optimal path information, and then the process returns to step S3.

9. The underground vehicle path planning method based on mine environment monitoring according to claim 1, characterized in that: In step S5, when the driver of the target vehicle changes the destination position, the real-time position of the target vehicle is used as the new starting position, and the changed destination position is used as the new destination position; Based on the new starting position and end position of the target vehicle combined with the available lane information, the path planning is re-performed to generate new optimal path information, and then return to step S3.

10. The underground vehicle path planning method based on mine environment monitoring according to claim 1, characterized in that: In step S5, when the available lane information is updated, the real-time position of the target vehicle is used as the new starting position, and the updated available lane information is used as the new available lane information; Based on the new starting position and the original end position of the target vehicle combined with the new available lane information, the path planning is re-performed to generate new optimal path information, and then return to step S3.

Images