Road rescue-oriented transport resource dynamic matching and path planning method and system

Abstract

The application belongs to the technical field of road rescue, and particularly discloses a road rescue-oriented transport capacity resource dynamic matching and path planning method and system, which comprises the following steps: obtaining road rescue request information to calculate an event comprehensive emergency index, then querying callable rescue transport capacity resources, using the rescue transport capacity resources and the event comprehensive emergency index to perform multi-target dynamic matching of each rescue transport capacity resource, selecting the optimal target rescue transport capacity resource to perform real-time rescue planning path planning and rescue task dispatching, so as to realize fine and dynamic matching of transport capacity resources and rescue demand, and realize efficient scheduling of rescue resources. According to the application, the optimal rescue transport capacity resource near the rescue event site, rescue demand condition and rescue emergency degree can be dynamically matched, and the rescue path is planned and guided in combination with real-time position information, so that the road rescue efficiency and rescue resource utilization rate are significantly improved.

Description

Technical Field

[0001] This invention belongs to the field of road rescue technology, specifically relating to a method and system for dynamic matching and route planning of transportation resources for road rescue. Background Technology

[0002] Roadside assistance refers to a series of assistance services provided by professional rescue service organizations when a vehicle encounters a breakdown or emergency on the road, including towing, repair, tire replacement, emergency fuel delivery, water cooling, getting out of trouble, and on-site minor repairs.

[0003] With the continuous growth of car ownership, the demand for roadside assistance is increasing. Traditional roadside assistance dispatch methods mainly rely on manual dispatch or the principle of allocation based on proximity. The matching of rescue resources is based solely on static distance, failing to fully consider the actual situation of the rescue event and the differences in rescue needs. It ignores the current workload and task types that rescue resources can handle, resulting in a low degree of matching between rescue resources and events, and inefficient resource allocation. Furthermore, it lacks real-time and effective rescue route guidance, leading to untimely response times. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for dynamic matching and route planning of transportation resources for road rescue, in order to solve the above-mentioned problems existing in the prior art.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: Firstly, it provides methods for dynamic matching and route planning of transportation resources for roadside assistance, including: Obtain roadside assistance request information and extract the event location, event time, main fault type, number of affected lanes, and number of vehicles involved from the roadside assistance request information; The severity coefficient of the accident is determined based on the main fault type and the number of vehicles involved; the waiting time of the event is determined based on the time of the event; and the total number of lanes and the real-time traffic congestion coefficient of the road segment where the event occurred are determined based on the location of the event. The comprehensive urgency index of an event is calculated using the event waiting time, the number of affected lanes, the total number of lanes, the real-time traffic congestion coefficient, and the accident severity coefficient. The system queries a set of available rescue resources within a defined rescue radius near the location of the incident. This set of resources includes several available rescue resources and their corresponding resource status data. Based on the event location, the event's comprehensive urgency index, and the resource status data corresponding to each rescue capacity resource, multi-target dynamic matching is performed on each rescue capacity resource to determine the target rescue capacity resource; By utilizing the event location and resource status data of the target rescue capacity, real-time rescue route planning is performed on the target rescue capacity, generating a rescue planning route for the target rescue capacity. A road rescue mission is generated based on the location of the incident, and the road rescue mission and rescue planning route are sent to the target rescue transportation resources.

[0006] In one possible design, determining the accident severity coefficient based on the main fault type and the number of vehicles involved, determining the waiting time of the event based on the event occurrence time, and determining the total number of lanes and the real-time traffic congestion coefficient of the road segment where the event occurred based on the event location include: The main fault types are imported into a preset fault severity classification table for matching to determine the fault severity corresponding to the main fault type. The fault severity classification table contains several main fault types and the fault severity corresponding to each main fault type. The severity of the main fault type and the number of vehicles involved are substituted into a preset accident severity coefficient calculation model to obtain the accident severity coefficient. The accident severity coefficient calculation model is as follows:

[0007] Among them, S a The severity coefficient of an accident, Y(F) e Characterizing the main fault type F e The corresponding fault severity, V e The representation involves the number of vehicles, k is the set severity increment coefficient, and min() represents the minimum value operation; Subtract the event occurrence time from the current time to get the event waiting time; The location of the incident is imported into a pre-set road rescue map for matching and search to determine the corresponding road segment where the incident occurred. The traffic monitoring system is then connected to query and obtain the total number of lanes and real-time traffic congestion coefficient of the road segment where the incident occurred.

[0008] In one possible design, the calculation of the comprehensive urgency index of an event using the event waiting time, the number of affected lanes, the total number of lanes, the real-time traffic congestion coefficient, and the accident severity coefficient includes: The event waiting time, number of affected lanes, total number of lanes, real-time traffic congestion coefficient, and accident severity coefficient are substituted into a preset event comprehensive urgency index formula for calculation, resulting in the event comprehensive urgency index. The event comprehensive urgency index formula is as follows:

[0009] Where E represents the overall urgency index of the event, ΔT represents the waiting time of the event, and T m N is the set reference response time.e N represents the number of lanes affected. total ρ represents the total number of lanes, and S represents the real-time traffic congestion coefficient. a The accident severity coefficients are represented by ω1, ω2, ω3 and ω4, which are the first weight coefficient, the second weight coefficient, the third weight coefficient and the fourth weight coefficient, respectively, and ω1+ω2+ω3+ω4=1.

[0010] In one possible design, the resource status data includes real-time location, the number of currently accepted tasks, the maximum number of tasks that can be accepted, and a set of manageable fault types.

[0011] In one possible design, the process of dynamically matching various rescue resources based on event location, comprehensive event urgency index, and resource status data corresponding to each rescue resource to determine the target rescue resource includes: Select several rescue resources that have been accepted for less than the maximum number of tasks that can be accepted, whose set of fault types that can be handled includes the main fault type, and whose real-time location is the smallest distance from the event location as pre-selected rescue resources. The distance between the real-time location of each pre-selected rescue transport resource and the event location is determined. The event's comprehensive urgency index, the current number of tasks already undertaken by each pre-selected rescue transport resource, the maximum number of tasks each pre-selected rescue transport resource can undertake, and the distance between the real-time location of each pre-selected rescue transport resource and the event location are then substituted into a preset matching scoring formula to calculate the matching score for each pre-selected rescue transport resource. The matching scoring formula is as follows:

[0012] Where i represents the sequence number of the pre-selected rescue transport capacity resources, and M i E represents the matching score of the pre-selected rescue capacity resource i, E represents the overall urgency index of the event, and d represents the matching score of the pre-selected rescue capacity resource i. ie d represents the distance between the real-time location of the pre-selected rescue capacity resource i and the event location. max To set the rescue radius, load i Cap represents the number of missions currently undertaken by the pre-selected rescue capacity resource i. i The maximum number of tasks that the pre-selected rescue transport capacity resource i can undertake is represented by α and β, which are the first and second adjustment coefficients set respectively. The pre-selected rescue capacity resource with the highest matching score will be used as the target rescue capacity resource.

[0013] In one possible design, the step of using event location and resource status data of the target rescue capacity to perform real-time rescue route planning for the target rescue capacity, and generating a rescue route plan for the target rescue capacity, includes: The event location and the real-time location of the target rescue resources are marked on the pre-set road rescue map. Starting from the marked real-time location of the target rescue resources and ending at the marked event location, the rescue route is planned using either the A* algorithm or the Dijkstra algorithm to generate the rescue route for the target rescue resources.

[0014] In one possible design, after sending road rescue missions and rescue planning routes to the target rescue capacity resources, the method further includes: As the target rescue resources travel to the event location according to the road rescue mission and the rescue planning route, the real-time location of the target rescue resources is collected again at set time intervals. The real-time rescue route is re-planned using the event location and the latest real-time location of the target rescue resources, and the updated rescue planning route is sent to the target rescue resources.

[0015] In one possible design, if there are no corresponding rescue resources within the rescue radius near the event location, the rescue radius is gradually expanded, and the set of resources within the expanded rescue radius is re-queried.

[0016] Secondly, it provides a dynamic matching and route planning system for roadside assistance resources, including an information acquisition unit, a parameter determination unit, an index calculation unit, a resource query unit, a dynamic matching unit, a route planning unit, and a task dispatch unit, wherein: The information acquisition unit is used to acquire roadside assistance request information and extract the event location, event occurrence time, main fault type, number of affected lanes, and number of vehicles involved from the roadside assistance request information. The parameter determination unit is used to determine the accident severity coefficient based on the main fault type and the number of vehicles involved, to determine the waiting time of the event based on the event occurrence time, and to determine the total number of lanes and the real-time traffic congestion coefficient of the road segment where the event occurred based on the event location. The index calculation unit is used to calculate the comprehensive urgency index of an event using the event waiting time, the number of affected lanes, the total number of lanes, the real-time traffic congestion coefficient, and the accident severity coefficient. The resource query unit is used to query the set of transportation resources within a set rescue radius near the event location. The set of transportation resources includes several callable rescue transportation resources and resource status data corresponding to each rescue transportation resource. The dynamic matching unit is used to perform multi-target dynamic matching of various rescue resources based on the event location, the comprehensive urgency index of the event, and the resource status data corresponding to each rescue resource, so as to determine the target rescue resource. The route planning unit is used to perform real-time rescue route planning for the target rescue resources using event location and resource status data, and to generate the rescue planned route for the target rescue resources. The task dispatch unit is used to generate road rescue tasks based on the location of the event and send the road rescue tasks and rescue planning routes to the target rescue transportation resources.

[0017] Thirdly, it provides a dynamic matching and route planning system for transportation resources for roadside assistance, including: Memory, used to store instructions; The processor is configured to read instructions stored in the memory and execute any one of the above-described methods for dynamic matching and route planning of transportation resources for road rescue according to the instructions.

[0018] Fourthly, a computer-readable storage medium is provided, on which instructions are stored, which, when executed on a computer, cause the computer to execute any one of the methods for dynamic matching and route planning of transportation resources for road rescue as described in the first aspect. Simultaneously, a computer program product is also provided, which, when executed on a computer, executes any one of the methods for dynamic matching and route planning of transportation resources for road rescue as described in the first aspect.

[0019] Beneficial Effects: This invention calculates a comprehensive urgency index for roadside assistance requests, then queries available rescue resources. It utilizes these resources and the comprehensive urgency index to perform multi-target dynamic matching, selecting the optimal target rescue resource for real-time rescue route planning and task assignment. This enables refined and dynamic matching of resources with rescue needs, achieving efficient resource allocation. Furthermore, this invention dynamically matches nearby optimal rescue resources based on the location, needs, and urgency of the rescue event, and combines real-time location information to plan rescue routes and guide rescue efforts, significantly improving roadside assistance efficiency and resource utilization. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating the method in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the system configuration in Embodiment 2 of the present invention; Figure 3 This is a schematic diagram of the system configuration in Embodiment 3 of the present invention. Detailed Implementation

[0022] It should be noted that the descriptions of these embodiments are intended to aid in understanding the invention and do not constitute a limitation thereof. The specific structural and functional details disclosed herein are merely for describing exemplary embodiments of the invention. However, the invention may be embodied in many alternative forms and should not be construed as being limited to the embodiments described herein.

[0023] It should be understood that, unless otherwise explicitly specified and limited, the corresponding terms should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in the embodiments according to the specific circumstances.

[0024] Specific details are provided in the following description to provide a complete understanding of the exemplary embodiments. However, those skilled in the art will understand that the exemplary embodiments can be implemented without these specific details. For example, apparatus may be shown in block diagrams to avoid obscuring the examples with unnecessary details. In other embodiments, well-known processes, structures, and techniques may be omitted with non-essential details to avoid obscuring the embodiments.

[0025] Example 1: This embodiment provides a method for dynamic matching and route planning of transportation resources for roadside assistance, which can be applied to corresponding roadside assistance cloud servers, such as... Figure 1 As shown, the method includes the following steps: S1. Obtain roadside assistance request information, and extract the event location, event time, main fault type, number of affected lanes, and number of vehicles involved from the roadside assistance request information.

[0026] In practice, the cloud server can receive roadside assistance request information through a dedicated assistance channel, and then parse the roadside assistance request information to extract the event location, event time, main fault type, number of affected lanes, and number of vehicles involved.

[0027] S2. Determine the accident severity coefficient based on the main fault type and the number of vehicles involved, determine the waiting time of the event based on the time of the event, and determine the total number of lanes and the real-time traffic congestion coefficient of the road segment where the event occurred based on the location of the event.

[0028] In practice, the cloud server can import the main fault types into a preset fault severity classification table for matching, and determine the fault severity corresponding to the main fault type. The fault severity classification table contains several main fault types and the fault severity corresponding to each main fault type. For example, the fault severity of tire blowout, lack of oil, and battery depletion is 0.2, the fault severity of engine overheating and brake failure is 0.5, and the fault severity of vehicle fire, rollover, and collision deformation is 0.8.

[0029] Then, the severity of the main fault type and the number of vehicles involved are substituted into a preset accident severity coefficient calculation model to obtain the accident severity coefficient. The accident severity coefficient calculation model is as follows:

[0030] Among them, S a The severity coefficient of an accident, Y(F) e Characterizing the main fault type F e The corresponding fault severity, V e The representation involves the number of vehicles, and k is the set severity increment coefficient, such as 0.1. min() represents the minimum value operation.

[0031] Additionally, the waiting time for an event can be obtained by subtracting the event occurrence time from the current time. The event location can be imported into a pre-set roadside assistance map for matching and searching to determine the corresponding road segment where the event occurred, and then connected to the traffic monitoring system to query and obtain the total number of lanes and real-time traffic congestion coefficient (0~1) of the road segment where the event occurred.

[0032] S3. Calculate the overall urgency index of the event using the event waiting time, the number of affected lanes, the total number of lanes, the real-time traffic congestion coefficient, and the accident severity coefficient.

[0033] In practice, the cloud server substitutes the event waiting time, the number of affected lanes, the total number of lanes, the real-time traffic congestion coefficient, and the accident severity coefficient into a pre-set comprehensive event urgency index formula to calculate the comprehensive event urgency index. The comprehensive event urgency index formula is as follows:

[0034] Where E represents the overall urgency index of the event, ΔT represents the waiting time of the event, and T m N is the set reference response time. e N represents the number of lanes affected. total ρ represents the total number of lanes, and S represents the real-time traffic congestion coefficient. aThe accident severity coefficients are represented by ω1, ω2, ω3 and ω4, which are the first weight coefficient, the second weight coefficient, the third weight coefficient and the fourth weight coefficient, respectively, and ω1+ω2+ω3+ω4=1.

[0035] S4. Query the set of transportation resources within a set rescue radius near the event location. The set of transportation resources includes several callable rescue transportation resources and the resource status data corresponding to each rescue transportation resource.

[0036] In practice, the cloud server can query a set of available rescue resources within a designated rescue radius near the event location. This set of resources includes several available rescue resources and their corresponding resource status data. The resource status data may include real-time location, the number of currently accepted tasks, the maximum number of tasks that can be accepted, and a set of handleable fault types. If there are no corresponding rescue resources within the designated rescue radius near the event location, the cloud server can gradually expand the rescue radius based on a set step size and re-query the set of available resources within the expanded rescue radius.

[0037] S5. Based on the event location, the event's comprehensive urgency index, and the resource status data corresponding to each rescue capacity resource, perform multi-target dynamic matching of each rescue capacity resource to determine the target rescue capacity resource.

[0038] In practice, the cloud server first selects several rescue resources as pre-selected rescue resources, based on the following criteria: the number of currently accepted tasks is less than the maximum number of tasks that can be accepted; the set of fault types that can be handled includes the main fault type; and the distance between the real-time location and the event location is the smallest.

[0039] Then, the distance between the real-time location of each pre-selected rescue transport resource and the event location is determined. The event's overall urgency index, the number of tasks currently undertaken by each pre-selected rescue transport resource, the maximum number of tasks each pre-selected rescue transport resource can undertake, and the distance between the real-time location of each pre-selected rescue transport resource and the event location are substituted into a preset matching scoring formula to calculate the matching score for each pre-selected rescue transport resource. The matching scoring formula is as follows:

[0040] Where i represents the sequence number of the pre-selected rescue transport capacity resources, and M i E represents the matching score of the pre-selected rescue capacity resource i, E represents the overall urgency index of the event, and d represents the matching score of the pre-selected rescue capacity resource i. ie d represents the distance between the real-time location of the pre-selected rescue capacity resource i and the event location. max To set the rescue radius, load i Cap represents the number of missions currently undertaken by the pre-selected rescue capacity resource i.i The maximum number of tasks that the pre-selected rescue transport capacity resource i can undertake is represented by α and β, which are the first and second adjustment coefficients set respectively. Finally, the pre-selected rescue capacity resource with the highest matching score will be used as the target rescue capacity resource.

[0041] S6. Utilize the event location and resource status data of the target rescue capacity to perform real-time rescue route planning for the target rescue capacity, and generate the rescue planning route for the target rescue capacity.

[0042] In practice, the cloud server can mark the event location and the real-time location of the target rescue resources on a pre-set road rescue map. Starting from the marked real-time location of the target rescue resources and ending at the marked event location, the server can use the A* algorithm or Dijkstra algorithm to plan the rescue route and generate the rescue route for the target rescue resources.

[0043] S7. Generate a road rescue mission based on the location of the event, and send the road rescue mission and rescue planning route to the target rescue transportation resources.

[0044] In practice, the cloud server can generate a road rescue mission based on the location of the event, and then send the road rescue mission and the rescue planning route to the target rescue transportation resources, so that the target rescue transportation resources can go to the location of the event according to the rescue planning route after receiving the road rescue mission.

[0045] Furthermore, as the target rescue resources travel to the event location according to the road rescue mission and the rescue planning route, the cloud server can re-collect the real-time location of the target rescue resources at set time intervals. Then, using the event location and the latest real-time location of the target rescue resources, the server can re-plan the real-time rescue route, generate an updated rescue planning route, and send the updated rescue planning route to the target rescue resources, thereby optimizing the rescue route under real-time road conditions.

[0046] This method can dynamically match the best nearby rescue resources based on the location of the rescue event, the rescue needs, and the urgency of the rescue, and combine real-time location information to plan rescue routes and guide rescue efforts, significantly improving the efficiency of road rescue and the utilization rate of rescue resources.

[0047] Example 2: This embodiment provides a dynamic matching and route planning system for transportation resources for roadside assistance, such as... Figure 2 As shown, it includes an information acquisition unit, a parameter determination unit, an index calculation unit, a resource query unit, a dynamic matching unit, a path planning unit, and a task dispatching unit, wherein: The information acquisition unit is used to acquire roadside assistance request information and extract the event location, event occurrence time, main fault type, number of affected lanes, and number of vehicles involved from the roadside assistance request information. The parameter determination unit is used to determine the accident severity coefficient based on the main fault type and the number of vehicles involved, to determine the waiting time of the event based on the event occurrence time, and to determine the total number of lanes and the real-time traffic congestion coefficient of the road segment where the event occurred based on the event location. The index calculation unit is used to calculate the comprehensive urgency index of an event using the event waiting time, the number of affected lanes, the total number of lanes, the real-time traffic congestion coefficient, and the accident severity coefficient. The resource query unit is used to query the set of transportation resources within a set rescue radius near the event location. The set of transportation resources includes several callable rescue transportation resources and resource status data corresponding to each rescue transportation resource. The dynamic matching unit is used to perform multi-target dynamic matching of various rescue resources based on the event location, the comprehensive urgency index of the event, and the resource status data corresponding to each rescue resource, so as to determine the target rescue resource. The route planning unit is used to perform real-time rescue route planning for the target rescue resources using event location and resource status data, and to generate the rescue planned route for the target rescue resources. The task dispatch unit is used to generate road rescue tasks based on the location of the event and send the road rescue tasks and rescue planning routes to the target rescue transportation resources.

[0048] Example 3: This embodiment provides a dynamic matching and route planning system for transportation resources for roadside assistance, such as... Figure 3 As shown, at the hardware level, it includes: The data interface is used to establish data communication between the processor and external data terminals; Memory, used to store instructions; The processor is used to read the instructions stored in the memory and execute the dynamic matching and route planning method for road rescue resources in Embodiment 1 according to the instructions.

[0049] Optionally, the system also includes an internal bus, through which the processor, memory, and data interface can be interconnected. This internal bus can be a PCIe (Peripheral Component Interconnect Eexpress) bus, which can be divided into an address bus, a data bus, a control bus, etc. The memory can include, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Flash Memory, First Input First Output (FIFO), and / or First In Last Out (FILO). The processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0050] Example 4: This embodiment provides a computer-readable storage medium storing instructions. When these instructions are executed on a computer, the computer performs the dynamic matching and route planning method for roadside assistance resources as described in Embodiment 1. The computer-readable storage medium refers to a data storage medium, which may include, but is not limited to, floppy disks, optical disks, hard disks, flash memory, USB flash drives, and / or Memory Sticks. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0051] This embodiment also provides a computer program product that, when run on a computer, executes the dynamic matching and route planning method for roadside assistance resources described in Embodiment 1. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0052] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for dynamic matching and route planning of transportation resources for roadside assistance, characterized in that, include: Obtain roadside assistance request information and extract the event location, event time, main fault type, number of affected lanes, and number of vehicles involved from the roadside assistance request information; The severity coefficient of the accident is determined based on the main fault type and the number of vehicles involved; the waiting time of the event is determined based on the time of the event; and the total number of lanes and the real-time traffic congestion coefficient of the road segment where the event occurred are determined based on the location of the event. The comprehensive urgency index of an event is calculated using the event waiting time, the number of affected lanes, the total number of lanes, the real-time traffic congestion coefficient, and the accident severity coefficient. The system queries a set of available rescue resources within a defined rescue radius near the location of the incident. This set of resources includes several available rescue resources and their corresponding resource status data. Based on the event location, the event's comprehensive urgency index, and the resource status data corresponding to each rescue capacity resource, multi-target dynamic matching is performed on each rescue capacity resource to determine the target rescue capacity resource; By utilizing the event location and resource status data of the target rescue capacity, real-time rescue route planning is performed on the target rescue capacity, generating a rescue planning route for the target rescue capacity. A road rescue mission is generated based on the location of the incident, and the road rescue mission and rescue planning route are sent to the target rescue transportation resources.

2. The method for dynamic matching and route planning of transportation resources for roadside assistance according to claim 1, characterized in that, The process of determining the accident severity coefficient based on the main fault type and the number of vehicles involved, determining the waiting time of the event based on the event occurrence time, and determining the total number of lanes and real-time traffic congestion coefficient of the road segment where the event occurred based on the event location includes: The main fault types are imported into a preset fault severity classification table for matching to determine the fault severity corresponding to the main fault type. The fault severity classification table contains several main fault types and the fault severity corresponding to each main fault type. The severity of the main fault type and the number of vehicles involved are substituted into a preset accident severity coefficient calculation model to obtain the accident severity coefficient. The accident severity coefficient calculation model is as follows: Among them, S a The severity coefficient of an accident, Y(F) e Characterizing the main fault type F e The corresponding fault severity, V e The representation involves the number of vehicles, k is the set severity increment coefficient, and min() represents the minimum value operation; Subtract the event occurrence time from the current time to get the event waiting time; The location of the incident is imported into a pre-set road rescue map for matching and search to determine the corresponding road segment where the incident occurred. The traffic monitoring system is then connected to query and obtain the total number of lanes and real-time traffic congestion coefficient of the road segment where the incident occurred.

3. The method for dynamic matching and route planning of transportation resources for roadside assistance according to claim 1, characterized in that, The comprehensive urgency index of an event is calculated using factors such as the event's waiting time, the number of affected lanes, the total number of lanes, the real-time traffic congestion coefficient, and the accident severity coefficient. This includes: The event waiting time, number of affected lanes, total number of lanes, real-time traffic congestion coefficient, and accident severity coefficient are substituted into a preset event comprehensive urgency index formula for calculation, resulting in the event comprehensive urgency index. The event comprehensive urgency index formula is as follows: Where E represents the overall urgency index of the event, ΔT represents the waiting time of the event, and T m N is the set reference response time. e N represents the number of lanes affected. total ρ represents the total number of lanes, and S represents the real-time traffic congestion coefficient. a The accident severity coefficients are represented by ω1, ω2, ω3 and ω4, which are the first weight coefficient, the second weight coefficient, the third weight coefficient and the fourth weight coefficient, respectively, and ω1+ω2+ω3+ω4=1.

4. The method for dynamic matching and route planning of transportation resources for roadside assistance according to claim 1, characterized in that, The resource status data includes real-time location, current number of tasks already accepted, maximum number of tasks that can be accepted, and a set of manageable fault types.

5. The method for dynamic matching and route planning of transportation resources for roadside assistance according to claim 4, characterized in that, The process involves multi-target dynamic matching of various rescue resources based on event location, comprehensive event urgency index, and resource status data corresponding to each rescue resource, to determine the target rescue resources, including: Select several rescue resources that have been accepted for less than the maximum number of tasks that can be accepted, whose set of fault types that can be handled includes the main fault type, and whose real-time location is the smallest distance from the event location as pre-selected rescue resources. The distance between the real-time location of each pre-selected rescue transport resource and the event location is determined. The event's comprehensive urgency index, the current number of tasks already undertaken by each pre-selected rescue transport resource, the maximum number of tasks each pre-selected rescue transport resource can undertake, and the distance between the real-time location of each pre-selected rescue transport resource and the event location are then substituted into a preset matching scoring formula to calculate the matching score for each pre-selected rescue transport resource. The matching scoring formula is as follows: Where i represents the sequence number of the pre-selected rescue transport capacity resources, and M i E represents the matching score of the pre-selected rescue capacity resource i, E represents the overall urgency index of the event, and d represents the matching score of the pre-selected rescue capacity resource i. ie d represents the distance between the real-time location of the pre-selected rescue capacity resource i and the event location. max To set the rescue radius, load i Cap represents the number of missions currently undertaken by the pre-selected rescue capacity resource i. i The maximum number of tasks that the pre-selected rescue transport capacity resource i can undertake is represented by α and β, which are the first and second adjustment coefficients set respectively. The pre-selected rescue capacity resource with the highest matching score will be used as the target rescue capacity resource.

6. The method for dynamic matching and route planning of transportation resources for roadside assistance according to claim 4, characterized in that, The process of using event location and resource status data of target rescue resources to perform real-time rescue route planning for target rescue resources, generating a planned rescue route for the target rescue resources, includes: The event location and the real-time location of the target rescue resources are marked on the pre-set road rescue map. Starting from the marked real-time location of the target rescue resources and ending at the marked event location, the rescue route is planned using either the A* algorithm or the Dijkstra algorithm to generate the rescue route for the target rescue resources.

7. The method for dynamic matching and route planning of transportation resources for roadside assistance according to claim 6, characterized in that, After sending road rescue missions and rescue planning routes to the target rescue transportation resources, the method further includes: As the target rescue resources travel to the event location according to the road rescue mission and the rescue planning route, the real-time location of the target rescue resources is collected again at set time intervals. The real-time rescue route is re-planned using the event location and the latest real-time location of the target rescue resources, and the updated rescue planning route is sent to the target rescue resources.

8. The method for dynamic matching and route planning of transportation resources for roadside assistance according to claim 1, characterized in that, If there are no corresponding rescue resources within the rescue radius near the event location, the rescue radius is gradually expanded, and the set of resources within the expanded rescue radius is re-queried.

9. A dynamic matching and route planning system for transportation resources for roadside assistance, characterized in that, It includes an information acquisition unit, a parameter determination unit, an index calculation unit, a resource query unit, a dynamic matching unit, a path planning unit, and a task dispatch unit, among which: The information acquisition unit is used to acquire roadside assistance request information and extract the event location, event occurrence time, main fault type, number of affected lanes, and number of vehicles involved from the roadside assistance request information. The parameter determination unit is used to determine the accident severity coefficient based on the main fault type and the number of vehicles involved, to determine the waiting time of the event based on the event occurrence time, and to determine the total number of lanes and the real-time traffic congestion coefficient of the road segment where the event occurred based on the event location. The index calculation unit is used to calculate the comprehensive urgency index of an event using the event waiting time, the number of affected lanes, the total number of lanes, the real-time traffic congestion coefficient, and the accident severity coefficient. The resource query unit is used to query the set of transportation resources within a set rescue radius near the event location. The set of transportation resources includes several callable rescue transportation resources and resource status data corresponding to each rescue transportation resource. The dynamic matching unit is used to perform multi-target dynamic matching of various rescue resources based on the event location, the comprehensive urgency index of the event, and the resource status data corresponding to each rescue resource, so as to determine the target rescue resource. The route planning unit is used to perform real-time rescue route planning for the target rescue resources using event location and resource status data, and to generate the rescue planned route for the target rescue resources. The task dispatch unit is used to generate road rescue tasks based on the location of the event and send the road rescue tasks and rescue planning routes to the target rescue transportation resources.

10. A dynamic matching and route planning system for transportation resources for roadside assistance, characterized in that, include: Memory, used to store instructions; The processor is configured to read instructions stored in the memory and execute the method for dynamic matching and route planning of transportation resources for road rescue as described in any one of claims 1-8 according to the instructions.

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