Fault response and dynamic path planning method of mine cloud control scheduling system

Abstract

This invention discloses a fault response and dynamic path planning method for a mine cloud-based control and scheduling system. The method includes classifying fault information; calculating and allocating initial optimal travel paths for vehicles requesting passage based on a preset road network topology in the transportation area using a graph search algorithm; real-time monitoring of vehicle status; when a vehicle fault is detected, executing corresponding operations based on the takeover attribute corresponding to the fault, and updating the passability status of the affected road segments in the global road network model accordingly; responding to the road network status update, triggering secondary path planning for associated vehicles blocked by the faulty road segment, calculating feasible travel paths; and issuing the paths to the corresponding affected vehicles and controlling them to travel along the new paths. This invention achieves real-time dynamic adjustment of unmanned transport vehicle scheduling paths by establishing a closed-loop process of decision-making, initial path planning, fault response and road network update, dynamic secondary planning, and new path issuance.

Description

Technical Field

[0001] This invention relates to the field of path planning technology for mine cloud control and scheduling, and particularly to a fault response and dynamic path planning method for a mine cloud control and scheduling system. Background Technology

[0002] Unmanned transportation systems have become a key technology for improving operational efficiency and ensuring operational safety in closed or semi-closed environments such as mines, ports, and logistics parks. These systems typically rely on a central dispatching platform (cloud control system) to uniformly plan and coordinate the routes of the fleet. Most existing dispatching strategies are based on static or semi-static shortest path algorithms (such as Dijkstra's algorithm and A algorithm) to generate the optimal driving route from the origin to the destination for each vehicle.

[0003] However, in actual operation, especially in complex environments such as mines with limited road resources, existing technologies have revealed significant shortcomings. When transport vehicles (such as mining trucks) experience breakdowns during transit (e.g., mechanical failure, power loss, sensor malfunction), the disabled vehicles become stranded and occupy main roads or key intersections. Because initial route planning often leads to multiple vehicles using a few efficient routes, creating a "same trajectory" phenomenon, the halting of one vehicle can quickly trigger a chain reaction of subsequent vehicles stopping and waiting, causing widespread traffic congestion. This not only directly reduces the efficiency of individual vehicle transport and the overall loading-unloading cycle speed but may also delay emergency response due to road blockages, posing safety risks. Existing cloud control systems typically lack real-time, dynamic response capabilities to sudden failures. Once their route planning schemes are issued, they are difficult to adjust quickly to sudden changes in local road conditions during vehicle travel, failing to effectively address the problem of sudden drops in regional traffic capacity caused by breakdowns.

[0004] Therefore, there is an urgent need for an intelligent scheduling method that can detect vehicle malfunctions in real time, dynamically reconstruct the road network status, and quickly replan avoidance routes for affected vehicles, so as to minimize the impact of malfunctions on the overall transportation process and ensure the robustness and efficient continuous operation of the system. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the existing technology. To achieve the above objective, a fault response and dynamic path planning method for a mine cloud control and scheduling system is adopted to solve the problems mentioned in the background technology.

[0006] A fault response and dynamic path planning method for a mine cloud control and scheduling system includes the following steps:

[0007] Fault classification and takeover decision-making steps: Classify the fault information reported by the transport vehicles and predefine takeover attributes for each type of fault. The takeover attributes are used to decide whether the cloud control system will automatically take over the handling of the fault or the monitoring personnel will manually take over when the fault occurs. Road network modeling and initial route planning steps: Based on the preset road network topology of the transportation area, the graph search algorithm is used to calculate and assign the initial optimal driving path for the vehicles requesting to travel; Fault response and road network status update steps: Real-time monitoring of vehicle status; when a vehicle fault is detected, corresponding operations are performed based on the takeover attribute corresponding to the fault, and the passability status of the affected road segment in the global road network model is updated accordingly. Dynamic secondary path planning steps: In response to the road network status update, secondary path planning is triggered for associated vehicles blocked by faulty road sections, and feasible optimal or optimized driving paths are recalculated based on the updated road network model. Route issuance and execution control steps: The replanned route is issued to the corresponding affected vehicles, and they are controlled to travel according to the new route. At the same time, the original route is canceled or suspended.

[0008] As a further aspect of the present invention: the fault classification and takeover decision-making steps specifically include: Define a set of fault types ,in It represents a specific type of fault. Define a set of takeover types ,in It indicates "autonomous takeover in the cloud". This indicates that "monitoring personnel have taken over manually"; Establish takeover attribute mapping function For any fault type Through query function Determine the method of takeover.

[0009] As a further aspect of the present invention: in the fault response and road network status update step, the operations performed according to the takeover attribute include: like Then the cloud control system will automatically execute: mark the road segment where the faulty vehicle is currently located as impassable, and based on the preset conflict rules, associate and mark the adjacent or conflicting road segments within its influence range; like If the cloud control system enters a waiting state, it will continue to receive a manual takeover command from the monitoring personnel before marking the status of the relevant road sections according to the command.

[0010] As a further aspect of the present invention: the graph search algorithm used in the road network modeling and initial path planning steps is Dijkstra's algorithm, specifically implemented as follows: The transportation area road network is abstracted as a weighted directed graph or undirected graph G=(V,E), where the vertex set V represents road intersections or critical path points, and the edge set E represents road segments connecting vertices. For each edge Assign a weight w(u,v), where the weight represents the road segment length, estimated travel time, or comprehensive cost. Using the vertex corresponding to the vehicle's starting position as the source point, Dijkstra's algorithm is applied iteratively to calculate the shortest path to the target vertex, and the path sequence is recorded.

[0011] As a further aspect of the present invention: the dynamic quadratic path planning step specifically includes: Define road network update function ,in This represents the set of road segments that are occupied due to a fault; Call function h to remove or disable elements from the original graph G=(V,E). The relevant edges are used to obtain the updated graph. = ; The updated image For each affected vehicle, the path planning algorithm is rerun with its current location as the new source point to calculate a new path around the fault area.

[0012] As a further aspect of the present invention: in the fault response and road network status update step, the operation of updating the road network status includes: In the system's road network adjacency matrix or adjacency table, the weight of the edge corresponding to the faulty road segment is set to infinity or a special no-entry flag; and / or Add the faulty road segment and its associated conflicting road segments to the global no-entry list, and exclude these road segments in subsequent route planning.

[0013] As a further aspect of the present invention, a path confirmation step is also included: In scenarios where manual takeover mode or system configuration requirements are confirmed, the new path generated by the secondary planning is submitted to the dispatcher's monitoring interface for review; If a confirmation instruction is received within a preset time, the path will be used to issue and execute control steps. If no confirmation instruction is received within the time limit or a rejection instruction is received, the affected vehicles will continue to wait along the original route or the preset emergency parking strategy will be implemented.

[0014] As a further aspect of the present invention, it also includes: Continuously collect vehicle location, speed, status information, and global traffic flow data in real time; Based on real-time collected data, the cost weights of the global road network are dynamically adjusted periodically or by event triggering, and the adjusted weights are applied in the initial path planning step and / or the dynamic secondary path planning step for calculation.

[0015] As a further aspect of the present invention: based on an unmanned transportation scenario in a mine, wherein: The transport vehicle is an unmanned mining truck; The road network is a closed or semi-closed topology structure built based on mines, spoil heaps, crushing stations, maintenance points and connecting roads; The vehicle malfunctions include mechanical, electrical, or control system failures that occur in complex mine road conditions and high-load operating environments, which may cause the vehicle to lose its mobility or obstruct the passage of main roads. The core objective of the scheduling is to overcome the large-scale stagnation and congestion of subsequent vehicles caused by faulty vehicles occupying limited critical road resources, and to ensure the continuous and efficient transportation of ore from loading point to unloading point.

[0016] As a further aspect of the present invention, the method further includes at least the following sub-processes: Fault reporting and identification sub-process: The vehicle automatically detects and reports fault information to the cloud in real time through the on-board system. The cloud receives the information and completes the fault type identification. Takeover decision and response sub-process: The cloud queries the preset takeover attributes based on the identified fault type, and decides and executes automatic takeover operation or waits and executes manual takeover command accordingly; Dynamic road network update sub-process: Based on the takeover response results, mark the fault-occupied road segments and affected conflict road segments in the global road network model, and update the passability status of each road segment in real time; Secondary planning triggering and calculation sub-process: Based on the updated road network status, automatically initiate a secondary route planning application for the affected vehicles to the route planning module and start recalculation; Route review and execution sub-process: The recalculated new route is sent to the dispatch monitoring terminal for manual review when necessary. After confirmation or default approval after timeout, the new route is issued to the corresponding vehicle for execution, and the execution status is monitored.

[0017] Compared with the prior art, the present invention has the following technical advantages: The above technical solution constructs a closed-loop control process encompassing "classification decision-making, real-time planning, and dynamic adjustment." This method first categorizes vehicle malfunctions and pre-sets takeover strategies (automatic / manual) as the basis for system response decisions. Based on the mine road network topology model, it plans initial optimal routes for vehicles. When a malfunction is detected, the system automatically or manually updates the status of the faulty road segment in the global road network according to the pre-set strategy. Then, it triggers secondary path planning to recalculate detour routes for affected vehicles. Finally, the new routes are issued for execution, thus achieving dynamic continuation of transportation tasks. This effectively solves the problem of cascading traffic congestion caused by vehicle malfunctions in closed environments. Through intelligent malfunction classification and rapid response mechanisms, the system can minimize malfunction handling delays. Dynamic secondary planning allows for immediate avoidance of malfunction points, ensuring uninterrupted passage for other vehicles. This significantly improves the robustness, continuous operation efficiency, and road resource utilization of the overall transportation system, especially in environments such as mines where stringent requirements for transportation efficiency and safety exist, reducing production losses caused by unexpected shutdowns. Attached Figure Description

[0018] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings: Figure 1 This is a schematic diagram illustrating the steps of the path planning method according to an embodiment of this application; Figure 2 This is a flowchart of a path planning method according to an embodiment of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please refer to Figure 1 and 2 In this embodiment of the invention, a fault response and dynamic path planning method for a mine cloud control and scheduling system includes the following steps: Step S1, Fault Classification and Takeover Decision Step: Classify the fault information reported by the transport vehicles and predefine takeover attributes for each type of fault. The takeover attributes are used to decide whether the cloud control system will automatically take over the handling of the fault or the monitoring personnel will manually take over when the fault occurs. In this embodiment, the fault classification and takeover decision steps specifically include: Define a set of fault types ,in It represents a specific type of fault. Define a set of takeover types ,in It indicates "autonomous takeover in the cloud". This indicates that "monitoring personnel have taken over manually"; Establish takeover attribute mapping function For any fault type Through query function Determine the method of takeover.

[0021] Step S2, Road Network Modeling and Initial Path Planning: Based on the preset road network topology of the transportation area, the initial optimal driving path is calculated and assigned to the vehicles requesting to travel using a graph search algorithm; In this embodiment, the graph search algorithm used in the road network modeling and initial path planning steps is Dijkstra's algorithm, and the specific implementation includes: The transportation area road network is abstracted as a weighted directed graph or undirected graph G=(V,E), where the vertex set V represents road intersections or critical path points, and the edge set E represents road segments connecting vertices. For each edge Assign a weight w(u,v), where the weight represents the road segment length, estimated travel time, or comprehensive cost. Using the vertex corresponding to the vehicle's starting position as the source point, Dijkstra's algorithm is applied iteratively to calculate the shortest path to the target vertex, and the path sequence is recorded.

[0022] Specifically, the mathematical formula for Dijkstra's algorithm is as follows: Define the graph structure: The road network is modeled as a weighted graph G = (V, E), where V is the set of vertices (representing intersections or key points of a path). Let it be a set of edges (representing road segments).

[0023] For any edge Define the weight function (Indicates road length, travel time, or overall cost).

[0024] Set source , represents the starting vertex of the path planning.

[0025] Define the data structure: Distance array ,in This represents the current shortest path length from the source point S to the vertex u.

[0026] Precursor array ,in Record the predecessor vertex of vertex u in the shortest path.

[0027] Undetermined set of vertices Initially, it consists of all vertices.

[0028] The steps of the algorithm formula: 1. Initialization; 2. Iteratively solve for the shortest path; 3. Termination conditions: The algorithm terminates when Q is empty. At this point, the dist array records the shortest path lengths from the source vertex S to all vertices, and the prev array can be used to backtrack and construct the complete path.

[0029] This algorithm uses a greedy strategy to progressively determine the shortest path tree, ensuring that each time the vertex u with the smallest distance is selected from Q, dist[u] has reached the final shortest distance. The non-negativity of the weight w(u,v) is a prerequisite for the correctness of the algorithm.

[0030] Step S3, Fault Response and Road Network Status Update: Monitor vehicle status in real time. When a vehicle fault is detected, perform corresponding operations based on the takeover attribute corresponding to the fault, and update the passability status of the affected road segment in the global road network model accordingly. In this embodiment, the operations performed based on the takeover attribute in the fault response and road network status update steps include: like Then the cloud control system will automatically execute: mark the road segment where the faulty vehicle is currently located as impassable, and based on the preset conflict rules, associate and mark the adjacent or conflicting road segments within its influence range; like If the cloud control system enters a waiting state, it will continue to receive a manual takeover command from the monitoring personnel before marking the status of the relevant road sections according to the command.

[0031] In this embodiment, the operation of updating the road network status in the fault response and road network status update steps includes: In the system's road network adjacency matrix or adjacency table, the weight of the edge corresponding to the faulty road segment is set to infinity or a special no-entry flag; and / or Add the faulty road segment and its associated conflicting road segments to the global no-entry list, and exclude these road segments in subsequent route planning.

[0032] Specifically, firstly, vehicle malfunctions need to be categorized, and a "takeover attribute" needs to be added to the fault code table. This attribute will determine whether the system automatically takes over or requires manual intervention when a malfunction occurs. Mathematically, we can define a set of fault types F and a set of takeover types T: Define a set of fault types ,in It represents a specific fault type, that is, the i-th fault type; Define a set of takeover types ,in It indicates "autonomous takeover in the cloud". This indicates that "monitoring personnel have taken over manually"; For each fault We define a property takeover function. It will return the corresponding takeover type t: Establish takeover attribute mapping function For any fault type Through query function Determine the method of takeover.

[0033] when = When the system automatically marks the road where the disabled vehicle is located and its conflicting road sections as the disabled road; when = At this time, the system awaits manual takeover instructions from monitoring personnel.

[0034] Step S4, Dynamic Secondary Path Planning Step: In response to the road network status update, for associated vehicles blocked due to faulty road sections, secondary path planning is triggered, and feasible optimal or optimized driving paths are recalculated based on the updated road network model. In this embodiment, the dynamic secondary path planning step specifically includes: Define road network update function ,in This represents the set of road segments that are occupied due to a fault; Call function h to remove or disable elements from the original graph G=(V,E). The relevant edges are used to obtain the updated graph. = ; The updated image For each affected vehicle, the path planning algorithm is rerun with its current location as the new source point to calculate a new path around the fault area.

[0035] In the specific implementation steps, when a disabled vehicle is detected occupying the road, the system will trigger secondary path planning. This process requires updating the adjacency matrix and recalculating the shortest path. We can define an update function h(V, E, F) to represent the adjacency matrix update caused by the fault F:

[0036] V' and E' are the updated set of vertices and edges, excluding paths occupied by faults.

[0037] Step S5, Route Distribution and Execution Control Steps: The replanned route is distributed to the corresponding affected vehicles, and they are controlled to travel according to the new route. At the same time, the original route is canceled or suspended.

[0038] In this embodiment, a path confirmation step is also included: In scenarios where manual takeover mode or system configuration requirements are confirmed, the new path generated by the secondary planning is submitted to the dispatcher's monitoring interface for review; If a confirmation instruction is received within a preset time, the path will be used to issue and execute control steps. If no confirmation instruction is received within the time limit or a rejection instruction is received, the affected vehicles will continue to wait along the original route or the preset emergency parking strategy will be implemented.

[0039] This embodiment also includes: Continuously collect vehicle location, speed, status information, and global traffic flow data in real time; Based on real-time collected data, the cost weights of the global road network are dynamically adjusted periodically or by event triggering, and the adjusted weights are applied in the initial path planning step and / or the dynamic secondary path planning step for calculation.

[0040] In this embodiment, based on the unmanned transportation scenario in a mine, wherein: The transport vehicle is an unmanned mining truck; The road network is a closed or semi-closed topology structure built based on mines, spoil heaps, crushing stations, maintenance points and connecting roads; The vehicle malfunctions include mechanical, electrical, or control system failures that occur in complex mine road conditions and high-load operating environments, which may cause the vehicle to lose its mobility or obstruct the passage of main roads. The core objective of the scheduling is to overcome the large-scale stagnation and congestion of subsequent vehicles caused by faulty vehicles occupying limited critical road resources, and to ensure the continuous and efficient transportation of ore from loading point to unloading point.

[0041] In this embodiment, the method further includes at least the following sub-processes: Fault reporting and identification sub-process: The vehicle automatically detects and reports fault information to the cloud in real time through the on-board system. The cloud receives the information and completes the fault type identification. Takeover decision and response sub-process: The cloud queries the preset takeover attributes based on the identified fault type, and decides and executes automatic takeover operation or waits and executes manual takeover command accordingly; Dynamic road network update sub-process: Based on the takeover response results, mark the fault-occupied road segments and affected conflict road segments in the global road network model, and update the passability status of each road segment in real time; Secondary planning triggering and calculation sub-process: Based on the updated road network status, automatically initiate a secondary route planning application for the affected vehicles to the route planning module and start recalculation; Route review and execution sub-process: The recalculated new route is sent to the dispatch monitoring terminal for manual review when necessary. After confirmation or default approval after timeout, the new route is issued to the corresponding vehicle for execution, and the execution status is monitored.

[0042] Compared with the prior art, the present invention has the following significant advantages and beneficial effects: 1. Real-time response to vehicle malfunctions and rapid route replanning: Existing technologies often lack an immediate response mechanism when faced with vehicle malfunctions, leading to disabled vehicles occupying road resources and causing traffic congestion. This invention, by monitoring vehicle status in real time, immediately triggers a route replanning process upon detecting a malfunction, effectively avoiding traffic stoppages caused by disabled vehicles, reducing the probability of congestion, and improving overall transportation efficiency.

[0043] 2. Improve the safety and stability of mine car transportation within the mine: Safety is the primary consideration in mining operations. This invention reduces the risks of mining trucks traveling on complex road conditions and lowers the accident rate through intelligent path planning. Simultaneously, by optimizing the route, it reduces the travel time of mining trucks on adverse road conditions, thereby improving transportation stability and ensuring the continuity and safety of production operations.

[0044] 3. Achieve rapid and efficient transportation of ore within the mine: This invention, through algorithmic and data analysis, precisely calculates the optimal set of segmented roads, optimizing the ore transportation route. This not only shortens transportation time but also reduces transportation costs and improves transportation efficiency. Especially in the unique environment of mines, enabling rapid and efficient ore transportation is of great significance for improving mine production efficiency.

[0045] 4. The system can dynamically adjust the route planning based on the operating conditions of the mining area: The mining environment is complex and ever-changing. The system of this invention can dynamically adjust route planning based on real-time production conditions and road conditions. This flexibility allows the system to adapt to dynamic changes in mining production, respond promptly to various emergencies, and ensure that the transportation route is always in optimal condition.

[0046] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention. The scope of the invention is defined by the appended claims and their equivalents, all of which should be included within the scope of protection of the invention.

Claims

1. A fault response and dynamic path planning method for a mine cloud control and scheduling system, characterized in that, Includes the following steps: Fault classification and takeover decision-making steps: Classify the fault information reported by the transport vehicles and predefine takeover attributes for each type of fault. The takeover attributes are used to decide whether the cloud control system will automatically take over the handling of the fault or the monitoring personnel will manually take over when the fault occurs. Road network modeling and initial route planning steps: Based on the preset road network topology of the transportation area, the graph search algorithm is used to calculate and assign the initial optimal driving path for the vehicles requesting to travel; Fault response and road network status update steps: Real-time monitoring of vehicle status; when a vehicle fault is detected, corresponding operations are performed based on the takeover attribute corresponding to the fault, and the passability status of the affected road segment in the global road network model is updated accordingly. Dynamic secondary path planning steps: In response to the road network status update, secondary path planning is triggered for associated vehicles blocked by faulty road sections, and feasible optimal or optimized driving paths are recalculated based on the updated road network model. Route issuance and execution control steps: The replanned route is issued to the corresponding affected vehicles, and they are controlled to travel according to the new route. At the same time, the original route is canceled or suspended.

2. The fault response and dynamic path planning method for a mine cloud control and scheduling system according to claim 1, characterized in that, The fault classification and takeover decision-making steps specifically include: Define a set of fault types ,in It represents a specific type of fault. Define a set of takeover types ,in This indicates "autonomous cloud-based takeover". This indicates that "monitoring personnel have taken over manually"; Establish takeover attribute mapping function For any fault type Through query function Determine the method of takeover.

3. The fault response and dynamic path planning method for a mine cloud control and scheduling system according to claim 2, characterized in that, The operations performed based on the takeover attributes in the fault response and road network status update steps include: like Then the cloud control system will automatically execute: mark the road segment where the faulty vehicle is currently located as impassable, and based on the preset conflict rules, associate and mark the adjacent or conflicting road segments within its influence range; like If the cloud control system enters a waiting state, it will continue to receive a manual takeover command from the monitoring personnel before marking the status of the relevant road sections according to the command.

4. The fault response and dynamic path planning method for a mine cloud control and scheduling system according to claim 1, characterized in that, In the road network modeling and initial path planning steps, the graph search algorithm used is Dijkstra's algorithm, and its specific implementation includes: The transportation area road network is abstracted as a weighted directed graph or undirected graph G=(V,E), where the vertex set V represents road intersections or critical path points, and the edge set E represents road segments connecting vertices. For each edge Assign a weight w(u,v), where the weight represents the road segment length, estimated travel time, or comprehensive cost. Using the vertex corresponding to the vehicle's starting position as the source point, Dijkstra's algorithm is applied iteratively to calculate the shortest path to the target vertex, and the path sequence is recorded.

5. The fault response and dynamic path planning method for a mine cloud control and scheduling system according to claim 4, characterized in that, The dynamic quadratic path planning steps specifically include: Define road network update function ,in This represents the set of road segments that are occupied due to a fault; Call function h to remove or disable elements from the original graph G=(V,E). The relevant edges are used to obtain the updated graph. = ; The updated image For each affected vehicle, the path planning algorithm is rerun with its current location as the new source point to calculate a new path around the fault area.

6. The fault response and dynamic path planning method for a mine cloud control and scheduling system according to claim 5, characterized in that, The fault response and road network status update steps include the following operations for updating the road network status: In the system's road network adjacency matrix or adjacency table, the weight of the edge corresponding to the faulty road segment is set to infinity or a special no-entry flag; and / or Add the faulty road segment and its associated conflicting road segments to the global no-entry list, and exclude these road segments in subsequent route planning.

7. The fault response and dynamic path planning method for a mine cloud control and scheduling system according to claim 1, characterized in that, It also includes a route confirmation step: In scenarios where manual takeover mode or system configuration requirements are confirmed, the new path generated by the secondary planning is submitted to the dispatcher's monitoring interface for review; If a confirmation instruction is received within a preset time, the path will be used to issue and execute control steps. If no confirmation instruction is received within the time limit or a rejection instruction is received, the affected vehicles will continue to wait along the original route or the preset emergency parking strategy will be implemented.

8. The fault response and dynamic path planning method for a mine cloud control and scheduling system according to claim 1, characterized in that, Also includes: Continuously collect vehicle location, speed, status information, and global traffic flow data in real time; Based on real-time collected data, the cost weights of the global road network are dynamically adjusted periodically or by event triggering, and the adjusted weights are applied in the initial path planning step and / or the dynamic secondary path planning step for calculation.

9. The fault response and dynamic path planning method for a mine cloud control and scheduling system according to claim 1, characterized in that, Based on the scenario of unmanned transportation in mines, including: The transport vehicle is an unmanned mining truck; The road network is a closed or semi-closed topology structure built based on mines, spoil heaps, crushing stations, maintenance points and connecting roads; The vehicle malfunctions include mechanical, electrical, or control system failures that occur in complex mine road conditions and high-load operating environments, which may cause the vehicle to lose its mobility or obstruct the passage of main roads. The core objective of the scheduling is to overcome the large-scale stagnation and congestion of subsequent vehicles caused by faulty vehicles occupying limited critical road resources, and to ensure the continuous and efficient transportation of ore from loading point to unloading point.

10. The fault response and dynamic path planning method for a mine cloud control and scheduling system according to claim 1, characterized in that, The method also includes at least the following sub-processes: Fault reporting and identification sub-process: The vehicle automatically detects and reports fault information to the cloud in real time through the on-board system. The cloud receives the information and completes the fault type identification. Takeover decision and response sub-process: The cloud queries the preset takeover attributes based on the identified fault type, and decides and executes automatic takeover operation or waits and executes manual takeover command accordingly; Dynamic road network update sub-process: Based on the takeover response results, mark the fault-occupied road segments and affected conflict road segments in the global road network model, and update the passability status of each road segment in real time; Secondary planning triggering and calculation sub-process: Based on the updated road network status, automatically initiate a secondary route planning application for the affected vehicles to the route planning module and start recalculation; Route review and execution sub-process: The recalculated new route is sent to the dispatch monitoring terminal for manual review when necessary. After confirmation or default approval after timeout, the new route is issued to the corresponding vehicle for execution, and the execution status is monitored.

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