Road emergency vehicle scheduling method and device

Abstract

The invention provides a road emergency vehicle scheduling method and device, and relates to the technical field of emergency scheduling, and the method comprises the steps: collecting road data, and generating a road network which comprises a plurality of nodes; screening the nodes to delete end nodes in the nodes, and determining the remaining nodes as target nodes; emergency rescue related information is acquired, and the total time cost of each emergency vehicle under various decision variables is calculated; adjusting the decision variable according to a constraint condition to reduce the time cost, and obtaining a target value of the decision variable; and performing task arrangement and scheduling on each emergency vehicle according to the target value of the decision variable. The total time cost of each emergency vehicle in the road network is calculated, and the decision variable is adjusted according to the constraint condition to reduce the time cost, so that task arrangement and scheduling of the emergency vehicles are realized, and the material transportation efficiency of the emergency rescue system is improved.

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 a highway. Background Art

[0002] In highway accidents, the route planning of emergency vehicles involves many complex decisions, especially in accident-prone areas. The main activities include dispatching a fleet of vehicles from a central warehouse or satellite facility to provide supplies to people in distress. In related technologies, dispatching is based on the dispatcher's experience and judgment, which lacks scientific basis, resulting in a longer time for emergency vehicles to transport supplies, resulting in lower efficiency in the transportation of emergency supplies, and reducing the operating 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 some extent.

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

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

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

[0007] A fourth objective of the present application is to provide a computer-readable storage medium.

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

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

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

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

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

[0013] Adjust the decision variable according to the constraint condition to reduce the time cost and obtain the target value of the decision variable;

[0014] The tasks of various 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, 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.

[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 obtaining of 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 from rescue mission i to 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 constraint conditions 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 vehicle warehouse dk after completing rescue mission i;

[0028] The third constraint is:

[0029] The fourth constraint is:

[0030] The fifth constraint is:

[0031]

[0032] Among them, t task,i is the duration of rescue mission i belonging to I∪S, 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 point of rescue mission j;

[0033] The sixth constraint is:

[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] The seventh constraint:

[0036] The eighth constraint is:

[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 value of the decision variable 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 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-mentioned purpose, the second embodiment of the present application proposes a highway emergency vehicle dispatching device, comprising:

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

[0047] A node screening module, used for screening the nodes to delete the end nodes therein and determining 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, used 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 schedule tasks for each emergency vehicle according to the target value of the decision variable.

[0051] To achieve the above-mentioned purpose, the third aspect of the present application provides an electronic device, including: 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 aspect embodiment of the present application proposes a computer-readable storage medium, in which computer-readable storage medium is stored computer execution instructions, and when the computer execution 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 purpose, the fifth aspect of the present application proposes a computer program product, which implements any method in the first aspect when executed by a processor.

[0056] The highway emergency vehicle dispatching method, device, electronic device and storage medium provided in the present application calculate the total time cost of each emergency vehicle in the road network, adjust the decision variables according to constraints to reduce the time cost, thereby realizing task arrangement and dispatching of emergency vehicles and improving 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 the 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 schematic diagram of a process flow of a highway emergency vehicle dispatching method provided in an embodiment of the present application;

[0060] Figure 2 A schematic diagram of the structure of a highway emergency vehicle dispatching device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0061] The embodiments of the present application are described in detail below, and examples of the embodiments 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] In highway incidents, the routing of emergency vehicles involves multiple complex decisions, especially in accident-prone areas. The main activity involves dispatching a fleet of vehicles from a central warehouse or satellite facilities to provide supplies to people in distress. A mixed integer linear programming (MILP) model is proposed to minimize the total run time of all emergency vehicles required to complete a given set of road networks with multiple priorities and reduce the maximum run time of a single vehicle. The model is developed and empirically applied. Computational results show that the proposed solution can effectively solve the problem and the model results are also better than the current solutions in practice. The proposed model helps planners optimize routes and evaluate resource allocation options.

[0063] To address this problem, the present application provides a method for dispatching emergency vehicles on a highway. Figure 1 The following is a flow chart of a method for dispatching emergency vehicles on a highway provided by an embodiment of the present application. Figure 1 As shown, the method comprises 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, taking 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 roads between the nodes. The travel time of the emergency vehicle on each arc is determined according to 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 variable according to the constraint condition to reduce the time cost and obtain the target value of the decision variable.

[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 the end nodes therein includes:

[0072] 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.

[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 point 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 turning angles 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 of 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 embodiment, emergency vehicles are relatively large and heavy, and often have difficulty turning at intersections. Therefore, when calculating the travel time of emergency vehicles on the driving 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 the intersection does not contain 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 obtaining of 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 supplies, and other common nodes. Emergency vehicles k travel back and forth between nodes corresponding to missions and nodes corresponding to material supplies to transport rescue supplies.

[0091] The transportation process of emergency rescue is as follows: emergency vehicle k sets out from the vehicle warehouse dk after being filled with supplies, and goes to the designated node i to provide supplies for node i; then receives instructions and determines the node j for the next rescue mission. If the remaining supplies on the rescue vehicle are sufficient to provide to node j at this time, the emergency vehicle k can directly drive to node j and provide supplies to node j; if the remaining supplies on the rescue vehicle are not sufficient to provide to node j at this time, the emergency vehicle k can first drive to the nearest supply node s to replenish supplies, then drive to node j and provide supplies to node j, and finally return to the vehicle warehouse dk. The above is the process of a cycle of emergency vehicles.

[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 from rescue mission i to 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 constraint conditions 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 it is decided not to send emergency vehicle k from the vehicle warehouse dk to the rescue mission 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 go to vehicle warehouse 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 task of the rescue task node i. The second constraint ensures that any emergency vehicle k∈K will return to the vehicle warehouse dk.

[0100] The third constraint is:

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

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

[0103] The fifth constraint is:

[0104]

[0105] Among them, t task,i is the duration of rescue mission i belonging to I∪S, 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 point of rescue mission j. Without loss of generality, it is calculated from time 0. For example, the 0th time, the 1st time, ..., the 100th time.

[0106] The sixth constraint is:

[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 It is the supplies of emergency vehicle k at the beginning of rescue mission j; it is used to ensure that after the rescue mission i is completed, there are enough supplies on emergency vehicle k to support the material consumption of rescue mission node j.

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

[0109] The eighth constraint is:

[0110] The eighth constraint defines the minimum value of the 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 value of the decision variable 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. The decision plan with the smallest total time cost is obtained by comparison, 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 method: Gradient descent method is an iterative optimization algorithm suitable for continuously differentiable objective functions. The algorithm updates parameters along the negative gradient direction so that the objective function gradually decreases. Gradient descent method is divided into batch gradient descent, stochastic gradient descent and mini-batch gradient descent.

[0120] 2. Newton's method: Newton's method is a second-order optimization algorithm that uses the second-order Taylor expansion of the objective function to find the minimum point. Newton's method has a faster convergence speed, but it needs to calculate the second-order derivative matrix (Hessian matrix) of the objective function, which may consume a lot of memory and computing resources for large problems.

[0121] 3. Quasi-Newton method: The quasi-Newton method is an improvement on the Newton method. It does not need to directly calculate the Hessian matrix, but 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. The conjugate gradient method can find the minimum value within a limited number of steps and does not need to store all gradient histories.

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

[0124] 6. Coordinate descent method: Coordinate descent method 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 each parameter. Coordinate descent method 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 their values ​​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: Genetic Algorithm is a heuristic optimization method that imitates the biological evolution process and gradually improves parameters through crossover, mutation and selection operations. Genetic Algorithm is suitable for multi-peak and non-convex objective functions.

[0127] 9. Particle Swarm Optimization: Particle swarm optimization is a group intelligence optimization algorithm that simulates the predation behavior of bird flocks 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 solid cooling process and allows jumping out of the local optimal solution. 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 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 comprises:

[0132] A road network generation module 210, for collecting road data and generating a road network, including a plurality of nodes;

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

[0134] A time cost calculation module 230, for obtaining emergency rescue related information and calculating the total time cost of each emergency vehicle under various decision variables;

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

[0136] The scheduling module 250 is used to arrange and schedule 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 should be noted that personal information from users should be collected for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. In addition, such collection / sharing should be carried out after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign the agreement / authorization including authorization of relevant user information before the user uses the function. In addition, any necessary steps should be taken to protect and safeguard access to such personal information data and ensure that others who have access to personal information data comply with its privacy policy and procedures.

[0142] The present application is expected to provide an implementation scheme for users to selectively block the use or access of personal information data. That is, the present disclosure is expected to provide hardware and / or software to prevent or block access to such personal information data. Once the personal information data is no longer needed, the risk can be minimized by limiting data collection and deleting the data. In addition, when applicable, such personal information is de-identified to protect the privacy of the user.

[0143] In the description of the aforementioned embodiments, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means 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 representations 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, without contradiction.

[0144] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0145] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment 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 not be performed in 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 technicians in the technical field to which the embodiments of the present application belong.

[0146] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, 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 in other suitable ways if necessary, and then stored in a computer memory.

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

[0148] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0149] In addition, each functional unit in each embodiment 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 one 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 can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify 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, including multiple nodes; Screening the nodes to delete end nodes therein, and determining the remaining nodes as target nodes; Obtain emergency rescue related information and calculate the total time cost of each emergency vehicle under various decision variables; Adjust the decision variable according to the constraint condition to reduce the time cost and obtain the target value of the decision variable; The tasks of various emergency vehicles are arranged and dispatched according to the target values ​​of the decision variables.

2. The method according to claim 1, characterized in that The step of screening the nodes to delete the end nodes therein comprises: 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.

3. The method according to claim 2, characterized in that The method further comprises: 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.

4. The method according to claim 3, characterized in that The determining of the corresponding shortest driving time according to the turns on the driving route includes: Obtaining turns on the driving route and determining turning angles corresponding to each turn; Determining a delay penalty time corresponding to the turn according to the turning angle; The travel time without delay and the delay penalty time of each turn are added to obtain the shortest travel time.

5. The method according to claim 3, characterized in that: The acquisition of emergency rescue related information and calculation of the total time cost of each emergency vehicle under various decision variables includes: 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, 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 from rescue mission i to 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; 6. The method according to claim 5, characterized in that The constraints include: 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; Second constraint: Among them, x i,dk,k is the decision variable for emergency vehicle k to depart for vehicle warehouse dk after completing rescue mission i; The third constraint is: The fourth constraint is: The fifth constraint is: Among them, t task,i is the duration of rescue mission i belonging to I∪S, 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 point of rescue mission j; The sixth constraint is: 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; The seventh constraint: The eighth constraint is: Ninth constraint: Tenth constraint: Eleventh constraint:

7. The method according to claim 6, characterized in that The step of adjusting the decision variable according to the constraint condition to reduce the time cost and obtaining the target value of the decision variable includes: adjusting the value of the decision variable and calculating the total time cost; The value of the decision variable when the total time cost is minimized is determined as the target value.

8. The method according to claim 7, characterized in that The step of arranging and dispatching tasks for each emergency vehicle according to the target value of the decision variable includes: 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 i,j,k If the value of is 0, emergency vehicle k will not be sent to perform task j after completing task i.

9. 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, including multiple nodes; A node screening module, used for screening the nodes to delete the end nodes therein and determining the remaining nodes as target nodes; 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; An optimization module, used to adjust the decision variables according to the constraint conditions to reduce the time cost and obtain the target value of the decision variables; The scheduling module is used to arrange and schedule tasks for each emergency vehicle according to the target value of the decision variable.

10. 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 8.

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