Highway emergency vehicle dispatching method and device

Abstract

This application proposes a method and device for dispatching emergency vehicles on highways, which relates to the field of emergency dispatch technology. The method includes: collecting road data and generating a road network, which includes multiple nodes; screening the nodes to delete the end nodes and determining the remaining nodes as target nodes; obtaining emergency rescue related information and calculating the total time cost of each emergency vehicle under various decision variables; adjusting the decision variables according to constraints to reduce the time cost and obtaining the target value of the decision variable; and scheduling and dispatching each emergency vehicle according to the target value of the decision variable. By calculating the total time cost of each emergency vehicle in the road network and adjusting the decision variables according to constraints to reduce the time cost, the task scheduling and dispatching of the emergency vehicles is achieved, thereby improving the material transportation efficiency of the emergency rescue system.

Description

Technical Field

[0001] The present application relates to the technical field of emergency rescue dispatching, and in particular to a method and device for dispatching emergency vehicles on highways. Background Art

[0002] In highway incidents, emergency vehicle routing involves multiple complex decisions, especially in accident-prone areas. Key activities include dispatching a fleet of vehicles from a central warehouse or satellite facility to deliver supplies to those stranded. Conventional technologies rely on the dispatcher's judgment and lack scientific rationale. This results in longer transport times for emergency vehicles, lowering the efficiency of emergency supply delivery and reducing the operational efficiency of the emergency transportation system. Summary of the Invention

[0003] The present application aims to solve one of the technical problems in the related art at least to a certain extent.

[0004] To this end, the first purpose of this application is to propose a highway emergency vehicle dispatching method.

[0005] The second object of this application is to provide a device.

[0006] The third objective of this application is to provide an electronic device.

[0007] The fourth object of this application is to provide a computer-readable storage medium.

[0008] A fifth object of this application is to provide a computer program product.

[0009] To achieve the above objectives, the first embodiment of the present application proposes a highway emergency vehicle dispatching method, comprising:

[0010] Collect road data and generate a road network, which includes multiple nodes;

[0011] Screening the nodes to delete end nodes therein, and determining the remaining nodes as target nodes;

[0012] Obtain emergency rescue information and calculate the total time cost of each emergency vehicle under various decision variables;

[0013] Adjusting the decision variables according to the constraint conditions to reduce the time cost and obtaining the target value of the decision variables;

[0014] The tasks of the emergency vehicles are arranged and dispatched according to the target values ​​of the decision variables.

[0015] Optionally, screening the nodes to delete end nodes therein includes:

[0016] If there is no emergency material warehouse at the node, no task is connected to the node, the number of neighboring nodes of the node is less than or equal to 1, and the only neighboring node allows U-turns, then the node is determined to be an end node.

[0017] Optionally, the method further includes:

[0018] Calculate the shortest driving route from the end of each rescue mission to the start of each other mission, and determine the corresponding shortest driving time based on the turns on the driving route and calculate the time cost between two tasks.

[0019] Optionally, the step of obtaining emergency rescue related information and calculating the total time cost of each emergency vehicle under various decision variables includes:

[0020] Get the node set I corresponding to the rescue mission, the node set S corresponding to the material supply, the emergency vehicle set K, and the priority of each rescue mission;

[0021] The calculation formula of the total time cost is:

[0022]

[0023] Among them, T is the total time cost, I represents the rescue mission set, S represents the material supply mission set, z p is the longest single emergency vehicle cycle time of priority p, P is the priority number set, c LOS,p is the first weight, t i,j is the duration from rescue mission i to j, x i,j,k is the decision variable for emergency vehicle k to go from rescue mission i to j, α i,j is the congestion coefficient of the road between rescue missions i and j, is the priority indicator function of rescue mission i, c Fuel is the second weight, x i,j,k If the value of x is 1, the decision is to send k to perform task j after completing task i; i,j,k If the value of is 0, the decision is not to send k to perform task j after completing task i;

[0024]

[0025] Optionally, the constraints include:

[0026] The first constraint is: Among them, x dk,i,k is the decision variable for emergency vehicle k to depart from vehicle depot dk to rescue mission i;

[0027] Second constraint: Among them, xi,dk,k is the decision variable for emergency vehicle k to depart for the vehicle depot dk after completing rescue mission i;

[0028] The third constraint:

[0029] The fourth constraint:

[0030] Fifth constraint:

[0031]

[0032] Among them, t task,i is the duration of I∪S in rescue mission i, t i,j is the time cost of traveling from rescue mission i to rescue mission j, u i is the starting time of rescue mission i, U is the road resistance coefficient, u j is the starting time of rescue mission j;

[0033] The sixth constraint:

[0034] Among them, l i Supplies consumed for rescue mission i, L k is the maximum material load of emergency vehicle k, v i,k is the supplies of emergency vehicle k at the beginning of rescue mission i, v j,k supplies for emergency vehicle k at the start of rescue mission j;

[0035] Seventh constraint:

[0036] The eighth constraint:

[0037] Ninth constraint:

[0038] Tenth constraint:

[0039] Eleventh constraint:

[0040] Optionally, adjusting the decision variable according to the constraint condition to reduce the time cost and obtaining the target value of the decision variable includes:

[0041] adjusting the values ​​of the decision variables and calculating the total time cost;

[0042] The value of the decision variable when the total time cost is minimized is determined as the target value.

[0043] Optionally, the step of arranging and dispatching tasks for each emergency vehicle according to the target value of the decision variable includes:

[0044] If the x i,j,k If the value of x is 1, emergency vehicle k is sent to perform task j after completing task i; if the x i,j,k If the value of is 0, emergency vehicle k will not be sent to perform task j after completing task i.

[0045] To achieve the above objectives, a second embodiment of the present application provides a highway emergency vehicle dispatching device, comprising:

[0046] A road network generation module, used to collect road data and generate a road network, which includes multiple nodes;

[0047] A node screening module is used to screen the nodes to delete the end nodes therein and determine the remaining nodes as target nodes;

[0048] The time cost calculation module is used to obtain emergency rescue related information and calculate the total time cost of each emergency vehicle under various decision variables;

[0049] An optimization module, configured to adjust the decision variables according to the constraint conditions to reduce the time cost and obtain the target value of the decision variables;

[0050] The scheduling module is used to arrange and dispatch tasks for each emergency vehicle according to the target value of the decision variable.

[0051] To achieve the above-mentioned purpose, a third embodiment of the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0052] The memory stores computer-executable instructions;

[0053] The processor executes the computer-executable instructions stored in the memory to implement the method as described in any one of the first aspects.

[0054] To achieve the above-mentioned purpose, the fourth embodiment of the present application proposes a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by a processor, they are used to implement the method as described in any one of the first aspects.

[0055] To achieve the above-mentioned objectives, the fifth embodiment of the present application proposes a computer program product, which implements any one of the methods in the first aspect when executed by a processor.

[0056] The highway emergency vehicle dispatching method, device, electronic device and storage medium provided in this application calculate the total time cost of each emergency vehicle in the road network, adjust the decision variables according to the constraints to reduce the time cost, realize the task arrangement and dispatch of emergency vehicles, and improve the material transportation efficiency of the emergency rescue system.

[0057] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0059] Figure 1 A flowchart of a highway emergency vehicle dispatching method provided in an embodiment of the present application;

[0060] Figure 2 This is a structural diagram of a highway emergency vehicle dispatching device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0061] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0062] Planning the routes of emergency vehicles during highway incidents involves multiple complex decisions, especially in accident-prone areas. Key activities involve dispatching a fleet of vehicles from a central depot or satellite facilities to deliver supplies to victims of a disaster. A mixed-integer linear programming (MILP) model is proposed to minimize the total travel time of all emergency vehicles required to complete a given set of road networks with multiple priorities, while also reducing the maximum travel time of individual vehicles. The model is developed and empirically applied. Computational results demonstrate that the proposed solution effectively solves the problem and outperforms current solutions in practice. The proposed model helps planners optimize routes and evaluate resource allocation options.

[0063] To address this issue, the present invention provides a method for dispatching emergency vehicles on highways. Figure 1 This is a flow chart of a highway emergency vehicle dispatching method provided by an embodiment of the present application. Figure 1 As shown, the method includes the following steps:

[0064] Step 101, collecting road data and generating a road network, which includes a plurality of nodes;

[0065] In this embodiment, in a real-world road network, each road segment may have one or more lanes in each direction, so multiple passes may be required. The rescue mission performed by the emergency vehicle is defined as a single pass on a road segment, so each road segment in the real-world road network may generate a set of tasks. In the first step of data cleaning, we constructed a new directed network, treating the intersection in the original road network as a node and replacing the roads between the nodes with directed arcs, where each arc represents the action of passing through the road between the nodes. The travel time of the emergency vehicle on each arc is determined based on factors such as the length of the road, the speed of the emergency vehicle, and the road conditions.

[0066] Step 102: Screen the nodes to delete the end nodes therein, and determine the remaining nodes as target nodes.

[0067] Step 103 : Obtain emergency rescue related information and calculate the total time cost of each emergency vehicle under various decision variables.

[0068] In this embodiment, the road network includes

[0069] Step 104: Adjust the decision variables according to the constraint conditions to reduce the time cost and obtain the target value of the decision variables.

[0070] Step 105 : Arrange and dispatch tasks for each emergency vehicle according to the target value of the decision variable.

[0071] Optionally, the step 102 of screening the nodes to delete end nodes therein includes:

[0072] If there is no emergency material warehouse at the node, no task is connected to the node, the number of neighboring nodes of the node is less than or equal to 1, and the only neighboring node allows U-turns, then the node is determined to be an end node.

[0073] In this embodiment, adjacent nodes may be determined based on the distance between the nodes. A distance threshold is set. If the distance between the nodes is less than the distance threshold, the two nodes are determined to be adjacent nodes to each other.

[0074] The end node is the end of the road in the actual road network, with inconvenient transportation, no emergency material warehouse nearby, and no tasks to be processed at this node. Therefore, there is no need for emergency vehicles to go to this node. This node can be deleted to reduce the amount of calculation in the subsequent optimization process and improve calculation efficiency.

[0075] Optionally, the method further includes:

[0076] Calculate the shortest driving route from the end of each rescue mission to the start of each other mission, and determine the corresponding shortest driving time based on the turns on the driving route and calculate the time cost between two tasks.

[0077] Optionally, determining the corresponding shortest driving time according to the turns on the driving route includes:

[0078] Obtaining turns on the driving route and determining a turning angle corresponding to each turn;

[0079] Determining a delay penalty time corresponding to the turn according to the turning angle;

[0080] Adding the travel time without delay to the delay penalty time of each turn to obtain the shortest travel time;

[0081] The calculation formula for the delay penalty time is:

[0082] C(β1)=(β1 / 90)C 右转 +(90-β1)C 掉头 / 90

[0083] C(β2)=(β2-90)C 直行 / 90+(180-β2)C 右转 / 90

[0084] C(β3)=(β3-180)C 左转 / 90+(270-β3)C 直行 / 90

[0085] C(β4)=(β4-270)C 掉头 / 90+(360-β4)C 左转 / 90.

[0086] In this example, emergency vehicles are relatively large and heavy, often making it difficult to turn at intersections. Therefore, when calculating the travel time of an emergency vehicle along its route, the time delay caused by different types of turns (e.g., left turns, right turns, and U-turns) must be considered. In the case where an intersection does not include a 90-degree turn, a delay function is defined to provide a delay penalty.

[0087] Among them, β1, β2, β3, and β4 correspond to the four turning situations of 90-degree right turn, 180-degree straight-ahead, 270-degree left turn, and 360-degree U-turn, respectively. 左转 , C 右转 , C 直行 and C 掉头 is the known delay penalty time.

[0088] Optionally, the step of obtaining emergency rescue related information and calculating the total time cost of each emergency vehicle under various decision variables includes:

[0089] Get the node set I corresponding to the rescue mission, the node set S corresponding to the material supply, the emergency vehicle set K, and the priority of each rescue mission;

[0090] In this embodiment, the nodes in the road network include the following categories: nodes i and j corresponding to rescue missions, nodes s corresponding to material supply, and other ordinary nodes. Emergency vehicles k travel back and forth between nodes corresponding to missions and nodes corresponding to material supply to transport rescue supplies.

[0091] The emergency rescue transportation process is as follows: emergency vehicle k, after loading up with supplies from vehicle depot dk, departs for a designated node i to deliver supplies. It then receives instructions and determines the next node j for its rescue mission. If the remaining supplies on the rescue vehicle are sufficient for node j, emergency vehicle k can proceed directly to node j and deliver the supplies. If the remaining supplies on the rescue vehicle are insufficient for node j, emergency vehicle k can first proceed to the nearest supply node s to restock, then proceed to node j and deliver the supplies to node j, before returning to vehicle depot dk. This completes the emergency vehicle's cycle.

[0092] The calculation formula of the total time cost is:

[0093]

[0094] Among them, T is the total time cost, I represents the rescue mission set, S represents the material supply mission set, z p is the longest single emergency vehicle cycle time of priority p, P is the priority number set, c LOS,p is the first weight, t i,j is the duration from rescue mission i to j, x i,j,k is the decision variable for emergency vehicle k to go from rescue mission i to j, α i,j is the congestion coefficient of the road between rescue missions i and j, is the priority indicator function of rescue mission i, c Fuel is the second weight, x i,j,k If the value of x is 1, the decision is to send k to perform task j after completing task i; i,j,k If the value of is 0, the decision is not to send k to perform task j after completing task i;

[0095]

[0096] Optionally, the constraints include:

[0097] The first constraint is: Among them, x dk,i,k is the decision variable for emergency vehicle k to depart from vehicle depot dk to rescue mission i;

[0098] x dk,i,k The value of 1 indicates that the emergency vehicle k is sent from the vehicle warehouse dk to the rescue mission node i, x dk,i,k The value of 0 indicates that the emergency vehicle k is not sent from the vehicle warehouse dk to the rescue task node i. The first constraint ensures that any emergency vehicle k∈K departs from the vehicle warehouse dk.

[0099] Second constraint: Among them, x i,dk,k is the decision variable for emergency vehicle k to depart for vehicle depot dk after completing rescue mission i; x i,dk,k The value of 1 indicates that the emergency vehicle k returns to the vehicle warehouse dk after completing the rescue mission node i. i,dk,k The value of 0 indicates that the emergency vehicle k does not return to the vehicle warehouse dk after completing the rescue mission node i. The second constraint ensures that any emergency vehicle k∈K will return to the vehicle warehouse dk.

[0100] The third constraint:

[0101] The third constraint is used to ensure that any vehicle k∈K that enters a task node i or a supply node s will exit the previous task node i or supply node s.

[0102] The fourth constraint: It is used to limit the task of each rescue mission node i to only send one emergency vehicle k to perform it, and not to repeat the task of a node i.

[0103] Fifth constraint:

[0104]

[0105] Among them, t task,i is the duration of I∪S in rescue mission i, t i,j is the time cost of traveling from task i to task j, u i is the starting time of rescue mission i, U is the road resistance coefficient, u j is the starting time of rescue mission j. Without loss of generality, we start counting from time 0. For example, time 0, time 1, ..., time 100.

[0106] The sixth constraint:

[0107] Among them, li Supplies consumed for rescue mission i, L k is the maximum material load of emergency vehicle k, v i,k is the supplies of emergency vehicle k at the beginning of rescue mission i, v j,k The materials on emergency vehicle k at the beginning of rescue mission j are used to ensure that after the rescue mission i is completed, there are enough materials on emergency vehicle k to support the material consumption at rescue mission node j.

[0108] Seventh constraint: Used to limit the amount of materials on emergency rescue vehicles to less than the maximum material load capacity.

[0109] The eighth constraint:

[0110] The eighth constraint defines the minimum cycle time zp of a single emergency vehicle. The initial value of this variable is assumed to be the maximum cargo load of vehicle k∈K; however, in general, a different number of vehicles k∈K can be assumed.

[0111] Ninth constraint:

[0112] Tenth constraint: Set the initial time point of rescue mission i to 0;

[0113] Eleventh constraint:

[0114] Optionally, adjusting the decision variable according to the constraint condition to reduce the time cost and obtaining the target value of the decision variable includes:

[0115] adjusting the values ​​of the decision variables and calculating the total time cost;

[0116] The value of the decision variable when the time is minimized is determined as the target value.

[0117] In this embodiment, the values ​​of the decision variables can be adjusted under the premise of satisfying the above constraints to generate multiple sets of decision plans, each of which contains the values ​​of the decision variables corresponding to each emergency vehicle. These decision plans are substituted into the calculation formula of the total time cost and the total time cost is calculated. By comparison, the decision plan with the minimum total time cost is obtained, and the value of each decision variable therein is determined as the target value.

[0118] In a possible embodiment, the minimum value of the objective function T is calculated by a minimum algorithm, for example:

[0119] 1. Gradient Descent: Gradient descent is an iterative optimization algorithm suitable for continuously differentiable objective functions. It updates parameters along the negative gradient, gradually decreasing the objective function. Gradient descent comes in many varieties, including batch gradient descent, stochastic gradient descent, and mini-batch gradient descent.

[0120] 2. Newton's method: The Newton method is a second-order optimization algorithm that uses the second-order Taylor expansion of the objective function to find the minimum. The Newton method has a fast convergence rate, but it requires calculating the second-order derivative matrix (Hessian matrix) of the objective function, which can consume a large amount of memory and computing resources for large problems.

[0121] 3. Quasi-Newton method: The quasi-Newton method is an improvement on the Newton method. Instead of directly calculating the Hessian matrix, it accelerates the optimization process by approximating the Hessian matrix. Typical quasi-Newton methods include BFGS (Broyden-Fletcher-Goldfarb-Shanno) and L-BFGS (Limited-memory BFGS).

[0122] 4. Conjugate Gradient Method: The conjugate gradient method is a first-order optimization algorithm suitable for quadratic objective functions. It can find the minimum value within a finite number of steps and does not require storing the entire gradient history.

[0123] 5. Chalk Method: The Chalk Method (Conjugate Direction Method) is a first-order optimization algorithm suitable for non-quadratic objective functions. The Chalk Method accelerates the optimization process by constructing a set of conjugate directions.

[0124] 6. Coordinate Descent: Coordinate descent is a first-order optimization algorithm that updates only one parameter at a time. It is suitable for situations where the objective function is independent of all parameters. Coordinate descent can be parallelized and is suitable for large-scale problems.

[0125] 7. Random Search: Random search is a simple optimization method that randomly generates parameters and evaluates them on the objective function to find the minimum. Random search is suitable for situations where there is no clear gradient information or the gradient is difficult to calculate.

[0126] 8. Genetic Algorithm: A genetic algorithm is a heuristic optimization method that mimics the biological evolution process and gradually improves parameters through crossover, mutation, and selection operations. Genetic algorithms are suitable for multimodal and non-convex objective functions.

[0127] 9. Particle Swarm Optimization: Particle swarm optimization is a swarm intelligence optimization algorithm that simulates the hunting behavior of flocks of birds to find the minimum value. Particle swarm optimization is applicable to global optimization problems.

[0128] 10. Simulated Annealing: Simulated annealing is a heuristic optimization method that simulates the cooling process of a solid and allows the solution to escape from the local optimum. Simulated annealing is suitable for complex objective functions.

[0129] Optionally, the step of arranging and dispatching tasks for each emergency vehicle according to the target value of the decision variable includes:

[0130] If the x i,j,k If the value of x is 1, emergency vehicle k is sent to perform task j after completing task i; if the x i,j,k If the value of is 0, emergency vehicle k will not be sent to perform task j after completing task i.

[0131] In order to implement the above embodiments, the present application also proposes a highway emergency vehicle dispatching device. Figure 2 This is a schematic diagram of the structure of a highway emergency vehicle dispatching device provided in an embodiment of the present application. Figure 2 As shown, the device includes:

[0132] A road network generation module 210 is used to collect road data and generate a road network, which includes a plurality of nodes;

[0133] A node screening module 220 is configured to screen the nodes to delete end nodes and determine the remaining nodes as target nodes;

[0134] A time cost calculation module 230 is used to obtain emergency rescue related information and calculate the total time cost of each emergency vehicle under various decision variables;

[0135] An optimization module 240 is configured to adjust the decision variables according to the constraint conditions to reduce the time cost and obtain target values ​​of the decision variables;

[0136] The scheduling module 250 is used to arrange and dispatch tasks for each emergency vehicle according to the target value of the decision variable.

[0137] In order to implement the above embodiments, the present application also proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided by the above embodiments.

[0138] In order to implement the above embodiments, the present application also proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0139] In order to implement the above embodiments, the present application also proposes a computer program product, including a computer program, which implements the methods provided by the above embodiments when executed by a processor.

[0140] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in this application are in compliance with relevant laws and regulations and do not violate public order and good morals.

[0141] It is important to note that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold beyond these legitimate uses. Furthermore, such collection / sharing should be conducted only after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes the relevant user information before using the feature. Furthermore, any necessary steps must be taken to safeguard and secure access to such personal information and ensure that others with access to personal information comply with its privacy policy and procedures.

[0142] This application contemplates providing implementations that allow users to selectively block the use or access of personal information data. Specifically, this disclosure contemplates providing hardware and / or software to prevent or block access to such personal information data. Risks can be minimized by limiting data collection and deleting data once it is no longer needed. Furthermore, where applicable, such personal information can be de-identified to protect user privacy.

[0143] In the descriptions of the foregoing embodiments, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are mutually inconsistent.

[0144] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of such features. Throughout the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0145] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0146] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). Furthermore, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing it in another suitable manner if necessary, and then storing it in a computer memory.

[0147] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0148] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0149] In addition, the functional units in the various embodiments of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into a module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0150] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A highway emergency vehicle dispatching method, characterized in that: The following steps are involved: Collect road data and generate a road network, which includes multiple nodes; Screening the nodes to delete end nodes therein and determining the remaining nodes as target nodes, including: if there is no emergency material warehouse at the node, no task is connected to the node, the number of neighboring nodes of the node is less than or equal to 1, and the only neighboring node allows U-turn, then determining the node as an end node; Calculate the shortest driving route from the end of each rescue mission to the start of each other mission, and determine the corresponding shortest driving time based on the turns on the driving route and calculate the time cost between two missions; Obtaining turns on the driving route and determining a turning angle corresponding to each turn; Determining a delay penalty time corresponding to the turn according to the turning angle; Adding the travel time without delay to the delay penalty time of each turn to obtain the shortest travel time; The calculation formula for the delay penalty time is: in, β 1. β 2. β 3. β 4. Corresponding to the four turning situations of 90-degree right turn, 180-degree straight ahead, 270-degree left turn and 360-degree U-turn, C 左转 , C 右转 , C 直行 and C 掉头 Penalty time for known delays; Obtain emergency rescue information and calculate the total time cost of each emergency vehicle under various decision variables; Adjusting the decision variables according to the constraint conditions to reduce the time cost and obtaining the target value of the decision variables; Arranging and dispatching tasks for each emergency vehicle according to the target value of the decision variable; The acquisition of emergency rescue related information and calculation of the total time cost of each emergency vehicle under various decision variables include: Get the node set I corresponding to the rescue mission, the node set S corresponding to the material supply, the emergency vehicle set K and the priority of each rescue mission; The calculation formula of the total time cost is: Among them, T is the total time cost, I represents the rescue mission set, S represents the material supply mission set, is the longest single emergency vehicle cycle time of priority p, is a set of priority numbers, is the first weight, is the duration from rescue mission i to j, is the decision variable for emergency vehicle k to go from rescue mission i to j, if If the value of is 1, then emergency vehicle k is sent to perform task j after completing task i; if If the value of is 0, emergency vehicle k will not be sent to perform task j after completing task i; is the congestion coefficient of the road between rescue missions i and j, is the priority indicator function of rescue mission i, is the second weight, If the value of is 1, the decision is to send k to perform task j after completing task i; If the value of is 0, the decision is not to send k to perform task j after completing task i; 。 2. The method according to claim 1, characterized in that The constraints include: The first constraint is: ,in, is the decision variable for emergency vehicle k to depart from vehicle depot dk to rescue mission i; Second constraint: ,in, is the decision variable for emergency vehicle k to depart for the vehicle depot dk after completing rescue mission i; The third constraint: ; The fourth constraint: ; Fifth constraint: in, For rescue mission i I ∪ S duration, is the time cost of traveling from rescue mission i to rescue mission j, is the starting time point of rescue mission i, U is the road resistance coefficient, is the starting time of rescue mission j; The sixth constraint: in, Supplies consumed for rescue mission i, is the maximum material load of emergency vehicle k, is the supplies of emergency vehicle k at the beginning of rescue mission i, supplies for emergency vehicle k at the start of rescue mission j; Seventh constraint: ; The eighth constraint: ; Ninth constraint: ; Tenth constraint: ; Eleventh constraint: .

3. A highway emergency vehicle dispatching device, characterized in that: include: A road network generation module, used to collect road data and generate a road network, which includes multiple nodes; The node screening module is used to screen the nodes to delete the end nodes therein and determine the remaining nodes as target nodes, including: if there is no emergency material warehouse at the node, and no task is connected to the node, and the number of neighboring nodes of the node is less than or equal to 1, and the only neighboring node allows U-turns, then the node is determined to be an end node; it is also used to calculate the shortest driving route from the end of each rescue mission to the start of each other mission, and determine the corresponding shortest driving time and calculate the time cost between two tasks based on the turns on the driving route, obtain the turns on the driving route, determine the turning angle corresponding to each turn, and determine the delay penalty time corresponding to the turn based on the turning angle; add the driving time without delay and the delay penalty time of each turn to obtain the shortest driving time; wherein the calculation formula of the delay penalty time is: in, β 1. β 2. β 3. β 4. Corresponding to the four turning situations of 90-degree right turn, 180-degree straight ahead, 270-degree left turn and 360-degree U-turn, C 左转 , C 右转 , C 直行 and C 掉头 Penalty time for known delays; A time cost calculation module is used to obtain emergency rescue related information and calculate the total time cost of each emergency vehicle under various decision variables, adjust the decision variables according to constraints to reduce the time cost, and obtain the target value of the decision variables; A scheduling module, configured to arrange and dispatch tasks for each emergency vehicle according to the target value of the decision variable; The acquisition of emergency rescue related information and calculation of the total time cost of each emergency vehicle under various decision variables include: Get the node set I corresponding to the rescue mission, the node set S corresponding to the material supply, the emergency vehicle set K and the priority of each rescue mission; The calculation formula of the total time cost is: Among them, T is the total time cost, I represents the rescue mission set, S represents the material supply mission set, is the longest single emergency vehicle cycle time of priority p, is a set of priority numbers, is the first weight, is the duration from rescue mission i to j, is the decision variable for emergency vehicle k to go from rescue mission i to j, if If the value of is 1, then emergency vehicle k is sent to perform task j after completing task i; if If the value of is 0, emergency vehicle k will not be sent to perform task j after completing task i; is the congestion coefficient of the road between rescue missions i and j, is the priority indicator function of rescue mission i, is the second weight, If the value of is 1, the decision is to send k to perform task j after completing task i; If the value of is 0, the decision is not to send k to perform task j after completing task i; 。 4. An electronic device, characterized in that: include: a processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 2.

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