A SUMO-based highway reconstruction and expansion simulation scenario construction and its evacuation and rescue decision-making method and system

Abstract

The present invention discloses a SUMO-based highway reconstruction and expansion simulation scenario construction and its evacuation and rescue decision-making method and system. The method comprises the following steps: Step 1: Based on the rescue and evacuation route plans during the highway reconstruction and expansion period, combined with traffic flow operation parameters, a dynamic scheme combination decision model is established; Step 2: Traffic simulation during the highway reconstruction and expansion period is performed using SUMO simulation software to simulate the traffic operation status of the reconstruction and expansion section under traffic accident conditions; Step 3: Multiple rescue and evacuation routes are implemented in the reconstruction and expansion simulation, simulation data is collected, and regression fitting is performed on the decision model. The simulation results are statistically analyzed and the validity of the decision model is verified. The system comprises a model construction module, a traffic simulation module, and a result verification module. By constructing a scheme decision model and determining the appropriate rescue and evacuation plan under the current traffic conditions based on input traffic flow parameters, the present invention achieves rapid rescue and evacuation of accidents during reconstruction and expansion, effectively restoring normal traffic flow operation.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic simulation, and in particular to a SUMO-based highway reconstruction and expansion simulation scenario construction and an evacuation and rescue decision-making method and system. Background Art

[0002] Recently, the level of intelligent transportation in my country has continued to improve, the deep integration of the Internet and transportation has been accelerated, and intelligent transportation has become a key component of the development of smart cities in China. In order to reduce the time and cost of testing, avoid the risks of on-site testing, and improve the efficiency of testing and optimization, digital twin technology has been widely used in intelligent transportation systems. Traffic simulation technology based on digital twins has developed rapidly. In addition, with the continuous and in-depth application of simulation technology in the field of transportation, by constructing complex simulation scenarios and conducting simulation analysis, a decision-making basis is provided for actual traffic management and control solutions. The present invention takes the highway reconstruction and expansion road as the scenario, studies the rescue and evacuation plan decision-making under this scenario, combines the two-dimensional traffic simulation software SUMO for scenario construction and data analysis, and is committed to developing a rescue and evacuation decision-making method during highway reconstruction and expansion.

[0003] Among the large amount of previous research materials, there has not been a relatively systematic study on rescue and evacuation during highway reconstruction and expansion. There is a lack of decision-making basis for plans in different scenarios. The plans proposed in some studies have not been verified by scientific means, and the effectiveness of the proposed plans cannot be guaranteed. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a SUMO-based highway reconstruction and expansion simulation scenario construction and its evacuation and rescue decision-making method and system. By constructing a scenario decision model and judging the appropriate rescue and evacuation plan under the current traffic conditions based on input traffic flow parameters, rapid rescue and evacuation of accidents during reconstruction and expansion can be achieved, and normal traffic flow operation can be effectively restored.

[0005] To solve the above technical problems, the present invention provides a SUMO-based highway reconstruction and expansion simulation scenario construction and evacuation and rescue decision-making method, comprising the following steps:

[0006] Step 1: Based on the rescue and evacuation route plan during the highway reconstruction and expansion period, a dynamic plan combination decision model is established in combination with traffic flow operation parameters;

[0007] Step 2: Use SUMO simulation software to conduct traffic simulation during the highway reconstruction and expansion period, simulating the traffic operation status of the reconstruction and expansion section under the traffic accident state;

[0008] Step 3: Implement multiple rescue and evacuation routes in the renovation and expansion simulation, collect simulation data and perform regression fitting on the decision model, statistically analyze the simulation results and verify the effectiveness of the decision model.

[0009] Furthermore, in step 1, based on the rescue and evacuation route plan during the highway reconstruction and expansion period, a dynamic scheme combination decision model is established in combination with traffic flow operation parameters, specifically including the following steps:

[0010] Step 11: Analyze conventional rescue routes for accident scenarios during the highway reconstruction and expansion period, and determine feasible rescue routes based on the actual conditions of the road section, so that rescue vehicles can enter the highway through the nearest interchanges upstream and downstream of the highway and reach the accident scene;

[0011] Step 12: Analyze the conventional vehicle evacuation routes after the accident scene rescue is implemented, and determine feasible evacuation routes based on the actual rescue situation to enable stranded social vehicles to quickly leave the accident scene;

[0012] Step 13: Establish a decision regression model. When an accident occurs and blocks all traffic in one direction, calculate the rescue time and road restoration time required for different evacuation routes and rescue routes based on the traffic status indicators at the time of the accident, and determine the optimal matching solution between the rescue route and the evacuation route.

[0013] Furthermore, in step 13, the decision regression model is established as follows:

[0014] v ij =β ij,0 +β ij.1 X ij,2 +β ij,3 X ij,4 +...+β ij,n X ij,n +ε

[0015]

[0016] Among them, X ij,1 ,X ij,2 ,...,X ij,n is the independent variable X ij The n eigencomponent matrix of ; and are predicted values, all calculated by the regression model; v ij and c ij are real values, which are obtained from a large amount of simulation data in the early stage; and is the average of all true values; β ij,0 ,β ij,1 ,...,β ij,n and γ ij,0 ,γij,1 ,...,γ ij,n is the model parameter vector, each component of which is the parameter of each combination of evacuation route and rescue route, which is the optimization object; the subscript ij represents the i-th evacuation plan combined with the j-th rescue plan.

[0017] Furthermore, in step 2, SUMO simulation software is used to perform traffic simulation during the highway reconstruction and expansion period. The simulation of the traffic operation status of the reconstruction and expansion section under the traffic accident state specifically includes the following steps:

[0018] Step 21: Build a SUMO simulation environment. Extract highway sections from the map database and import them into SUMO. Use SUMO's netedit interface to modify the simulated section attributes based on the actual conditions of the reconstruction and expansion area. Close the emergency lane and add an expansion road. Collect relevant data on the highway reconstruction and expansion area, including traffic flow and vehicle speed, to build a basic simulation environment.

[0019] Step 22: Determine the number of emergency rescue points and rescue vehicles based on the emergency rescue and accident situation. Add the information of the emergency rescue points and rescue vehicles to the simulation environment. Apply a path search algorithm to search for the shortest path from the emergency rescue point to the evacuation point in the road network. Evaluate the searched path, taking into account road congestion and vehicle speed factors, and calculate the feasibility and efficiency of the path.

[0020] Step 23: Preheat the simulation scene, set the accident point location, simulate the accident and implement relevant control measures;

[0021] Step 24: Based on the characteristics of the highway reconstruction and expansion area, in order to maintain consistency with normal traffic conditions, a special simulated road and a special driving route are built, and a reverse emergency lane is set on the inner side of the simulated road. The opening condition of the lane is set to that there are no vehicles in the corresponding forward lane, that is, all vehicles have been evacuated.

[0022] Furthermore, in step 3, multiple rescue and evacuation routes are implemented in the reconstruction and expansion simulation, simulation data is collected and regression fitting is performed on the decision model, and the simulation results are statistically analyzed and the effectiveness of the decision model is verified. Specifically, the following steps are included:

[0023] Step 31: By giving the evacuation routes of congested vehicles, evacuate the vehicles at the accident site and control the upstream and downstream traffic flows to simulate the evacuation process. By giving the number of rescue vehicles and the driving routes, simulate the emergency rescue process.

[0024] Step 32: Wait for the road to clear and end the simulation. Simultaneously collect simulation data, including emergency rescue time, evacuation time, and vehicle congestion. Analyze and evaluate the simulation results based on three scenarios: two-way traffic in the opposite lane, U-turn on the central median, and two-way short release.

[0025] Step 33: Clean the simulation data, process missing values ​​and outliers, and perform normalization and dimensionality reduction.

[0026] Step 34: Fit the regression model based on the obtained simulation data, and use the least squares method to establish a linear regression prediction model. Under different conditions, multiple sets of rescue time and road traffic restoration time are obtained to obtain the best linear regression function.

[0027] Step 35: Evaluate the established regression model and verify the effectiveness of the decision model in a simulation environment. Under a given accident scenario, collect the accident scenario road traffic operation indicators, input them into the decision model to obtain the solution decision results, test them in the simulation scenario, and compare and verify them with the total time indicators of other solution combinations.

[0028] Furthermore, in step 31, by giving the evacuation routes of congested vehicles, the vehicles at the accident site are evacuated, and the upstream and downstream traffic flows are controlled to simulate the evacuation process. By giving the number of rescue vehicles and the driving routes, the simulation of the emergency rescue process specifically includes the following steps:

[0029] Step 311: Determine the initial conditions of the route, set the rescue vehicle and emergency evacuation point, define the rescue vehicle ID and the location of the emergency evacuation point in route.rou.xml; initialize the route information, and configure the initial route for each rescue vehicle. These routes are based on the pre-set traffic network and feasible driving paths;

[0030] Step 312: Start the simulation using the Traci interface, and execute each simulation step repeatedly by looping until the set conditions are met or the rescue / evacuation is completed. During the simulation, the rescue vehicle's route is dynamically adjusted according to the real-time traffic conditions and road network status.

[0031] Step 313: Modify the vehicle driving settings to avoid the vehicle from detouring due to encountering congested areas or accident scenes;

[0032] Step 314: By monitoring the arrival of the rescue vehicle at key road nodes, determine whether the route needs to be adjusted. If the rescue vehicle is close to the accident scene, it is necessary to adjust the driving path according to the set rescue route, that is, select one of the upward forward rescue, downward forward rescue, and downward reverse rescue directions;

[0033] Step 315: When the simulation reaches the set step length, the evacuation simulation begins, and the vehicles on the edge before the accident section drive along the evacuation route.

[0034] Step 316: The rescue vehicle drives away from the accident edge, and the vehicle drives on the accident edge. The simulation runs normally until the step ends.

[0035] Accordingly, a SUMO-based highway reconstruction and expansion simulation scenario construction and its evacuation and rescue decision-making system includes: a model building module, a traffic simulation module and a result verification module; the model building module is based on the rescue and evacuation route plan during the highway reconstruction and expansion period, combined with traffic flow operation parameters to establish a dynamic plan combination decision model; the traffic simulation module uses SUMO simulation software to perform traffic simulation during the highway reconstruction and expansion period, and simulates the traffic operation status of the reconstruction and expansion section under the traffic accident state; the result verification module realizes multiple rescue and evacuation routes in the reconstruction and expansion simulation, collects simulation data and performs regression fitting on the decision model, statistically analyzes the simulation results and verifies the effectiveness of the decision model.

[0036] The beneficial effects of the present invention are as follows: the present invention focuses on rescue and evacuation decisions in the scenario of highway reconstruction and expansion, constructs a simulation scenario of highway reconstruction and expansion, and fits a regression decision model based on the traffic flow parameters in the simulation scenario, effectively finding the optimal rescue and evacuation plan in the accident scenario, helping traffic flow to resume normal operation, and conducting simulation verification of the plan and decision, illustrating the effectiveness of the decision-making method; the present invention focuses on a dynamic system framework with high compatibility, and can provide rescue and evacuation decisions for reconstruction and expansion accident scenarios under various conditions, effectively improving rescue efficiency and reducing the impact of accidents on traffic. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is an illustration of the rescue route of the present invention.

[0038] Figure 2 It is an illustration of the evacuation route of the present invention.

[0039] Figure 3 Build a demonstration diagram for the simulation environment of the present invention. DETAILED DESCRIPTION

[0040] A SUMO-based highway reconstruction and expansion simulation scenario construction and evacuation and rescue decision-making method includes the following steps:

[0041] Step 1: Based on the rescue and evacuation route plan during the highway reconstruction and expansion period, combined with traffic flow operation parameters, a dynamic scheme combination decision model is established. The specific steps include the following:

[0042] Step 1.1: Combined construction of highway rescue routes and evacuation routes;

[0043] Step 1: Common highway rescue routes such as Figure 1 As shown in the rescue route diagram, it is generally divided into upward forward rescue, downward forward rescue and downward reverse rescue, so that the rescue vehicle enters the highway through the nearest interchange upstream or downstream of the highway and arrives at the accident scene;

[0044] Step 2: Common highway evacuation routes such as Figure 2 As shown in the (Evacuation Route Illustration), it is generally divided into time-sharing alternating traffic, U-turn traffic and lane-by-lane traffic to allow stranded vehicles to leave the accident scene;

[0045] Step 3: Determine a feasible combination of rescue routes and evacuation routes based on the actual conditions of the road section where the accident occurred.

[0046] Step 1.2: Establishment of scheme combination decision model;

[0047] The regression function uses the least squares method to build a linear regression prediction model. The least squares method is a mathematical optimization technique widely used for data fitting.

[0048] Step 1: Regression model input. The input variables are:

[0049] ① Traffic state variables: upstream traffic flow, downstream traffic flow, and two-way average speed. These variables can be directly observed or calculated in traffic scenarios and can reflect the current traffic state through traffic calculations.

[0050] ② Distance variable: distance L between points AP1 , L P1X , L XP2 , L P2B Distance and vehicle speed are the most important variables for determining rescue time and recovery time.

[0051] Step 2: Regression model output. The output variables are:

[0052] ① Rescue time matrix V=(v ij ) 4×3 .v ij It represents the rescue time required for the i-th evacuation route combined with the j-th rescue route.

[0053] ②Road restoration time matrix C=(c ij ) 4×3 . c ij It represents the road restoration time required for the i-th evacuation route combined with the j-th rescue route.

[0054] Step 3: Perform feature engineering on the input data, including data cleaning, variable selection and normalization. Then, these features X ij As an independent variable, rescue time v ij and road recovery time c ij Used them as dependent variables to establish a linear regression model.

[0055] Step 4: The regression function uses the least squares method to build a linear regression prediction model. The least squares method is a mathematical optimization technique widely used in data fitting.

[0056] v ij =β ij,0 +β ij.1 X ij,2 +β ij,3 X ij,4 +...+β ij,n X ij,n +ε

[0057]

[0058] Among them, X ij,1 ,X ij,2 ,...,X ij,n is the independent variable X ij The n eigencomponent matrix of ; and are predicted values, all calculated by the regression model; v ij and c ij are real values, which are obtained from a large amount of simulation data in the early stage; and is the average of all true values; β ij,0 ,β ij,1 ,...,β ij,n and γ ij,0 ,γ ij,1 ,...,γ ij,n is a model parameter vector, where each component is the parameter of each evacuation route and rescue route combination, which is the optimization object. The subscript ij represents the i-th evacuation plan combined with the j-th rescue plan.

[0059] Step 1.3: Evaluate the effectiveness of decision-making route selection.

[0060] The specific process of this step is based on the above steps 1.1 and 1.2:

[0061] Step 1: Calculate the rescue time. The rescue time is the time from the accident to the arrival of rescue vehicles at the accident site. During this time, the number of evacuation vehicles and rescue vehicles are intertwined. The rescue time can reflect the impact of different evacuation routes and rescue routes on the rescue effect.

[0062] Step 2: Calculate the road restoration time. This time is the time from the accident to the full restoration of two-way road traffic to normal. It can reflect the overall impact of different evacuation routes and rescue routes on traffic.

[0063] Step 3: Based on the rescue time and road restoration time, calculate the total time from the accident to the completion of evacuation. The plan combination with the shortest total time is the optimal rescue and evacuation plan.

[0064] Step 2: Based on Step 1, SUMO simulation software is used to conduct traffic simulation during the highway reconstruction and expansion period, simulating the traffic operation status of the reconstruction and expansion section under the traffic accident state. This is achieved by the following steps:

[0065] Step 2.1: Build the SUMO simulation environment;

[0066] Step 1: Extract highway sections from the map database and import them into SUMO. Use SUMO's netedit interface to modify the section attributes based on the actual conditions of the reconstruction and expansion area. Close the emergency lane and add an expansion road. Collect relevant data on the highway reconstruction and expansion area, including traffic flow and vehicle speed, to build a basic simulation environment.

[0067] Step 2: Accident Location Definition. Here, the accident section AB is divided into five sections: A-P1-X-P2-B. X is the accident point, A and B are the nearest interchanges upstream and downstream of the accident point, and P1 and P2 are the nearest emergency U-turn points on the median upstream and downstream of the accident point.

[0068] Step 2.2: Traffic accident scene construction

[0069] Step 1: Select the specific highway section edge where the accident occurred, determine its edge_id, and set relevant parameters and conditions according to the accident type to be simulated (such as vehicle collision).

[0070] Step 2: Edit the net.xml file. In the SUMO road network file, mark or modify the road section where the accident occurred. You can set specific road section attributes such as lowering the speed limit.

[0071] Step 3: Set the accident impact. Use the add.xml file to define the specific impact of the accident. Set the "Variable Speed ​​Flag" to temporarily change the speed limit, and use the "Lane Closed" command to simulate the situation where a lane is blocked due to an accident.

[0072] Step 4: Configure vehicle behavior by modifying the rou.xml file to preset detour routes for vehicles that may be affected by the accident.

[0073] Step 2.3: Modeling emergency rescue needs;

[0074] Step 1: Input the rescue point locations, rescue vehicle information, and pre-set routes into the simulation software. Adjust simulation settings, such as time, weather, and traffic flow, to simulate different rescue scenarios, and determine the number of emergency rescue points and rescue vehicles.

[0075] Step 2: Select an appropriate path search algorithm based on the network structure. For example, the Dijkstra algorithm is suitable for unweighted graphs, while the A* algorithm is suitable for path search with heuristic information. Perform a path search for each emergency rescue point to find the shortest path to each evacuation point.

[0076] Step 2.4: Vehicle route construction

[0077] Add roads according to the special requirements of rescue and evacuation routes. In the process of building the simulated road network, set up reverse emergency lanes on the inner side of the simulated roads, and set the opening condition of the lanes to be no vehicles on the corresponding forward lanes. Considering the realization of the rescue route, set up a road at the temporary isolation zone and set a certain speed limit to simulate the actual engineering rescue situation. Figure 3 shown.

[0078] Step 3: Implement multiple rescue and evacuation routes in the renovation and expansion simulation, collect simulation data and perform regression fitting on the decision model, compile statistics on the simulation results and verify the effectiveness of the decision model.

[0079] The implementation of step 3 requires that the solution combination in step 1 and the accident scenario and rescue requirements in step 2 are determined, and then simulation and effectiveness verification are carried out. The specific steps are as follows:

[0080] Step 3.1: Implementation of rescue and evacuation route simulation;

[0081] Step 1: Determine the initial route conditions and set the rescue vehicle and emergency evacuation point. Define the rescue vehicle ID and the location of the emergency evacuation point in route.rou.xml. Initialize the route information and configure an initial route for each rescue vehicle based on the pre-defined traffic network and feasible driving paths.

[0082] Step 2: Use the Traci interface to initiate the simulation, looping through each simulation step until the set conditions are met or the rescue / evacuation is complete. During the simulation, the rescue vehicle's route is dynamically adjusted based on real-time traffic conditions and road network status.

[0083] Step 3: Modify the vehicle's driving settings to avoid detours due to congested areas or accident scenes.

[0084] Step 4: By monitoring the rescue vehicle's arrival at key road nodes, determine whether the route needs to be adjusted. If the rescue vehicle approaches the accident scene, it is necessary to adjust the driving path further according to the set rescue route, that is, choose one of the upward forward rescue, downward forward rescue and downward reverse rescue directions.

[0085] Step 5: When the simulation runs to the set step length, the evacuation simulation begins, and the vehicles on the edge before the accident section drive according to the evacuation route.

[0086] Step 6: After the rescue vehicle leaves the accident edge, the vehicle can drive on the accident edge and the simulation runs normally until the step ends.

[0087] Step 3.2: Collect and analyze simulation results data;

[0088] Simulation data was acquired using detectors within the simulation software, primarily the Multi-Entry-Exit Detectors (E3) detector in SUMO. The E3 detector's output values, nVehEntered and meanSpeed, were selected as the two-way traffic volume and average speed, respectively. Accident locations and upstream and downstream interchange locations were derived from road network data, as shown in Table 1.

[0089] Table 1 Detector output and parameter meaning

[0090]

[0091] Step 3.3: Simulation data statistics

[0092] The simulation data were statistically analyzed and the experiments were initially divided into 9 groups. Each group was divided into different groups according to the combination of evacuation routes and rescue routes. The A-P1, P2-B, and P1-X distance data were set. At the same time, the road traffic volume was changed. The average speed of social vehicles, forward traffic density, rescue time, and evacuation time indicators were statistically analyzed, as shown in the following table.

[0093]

[0094] Step 3.4: Regression model establishment

[0095] The regression model was fitted according to the obtained simulation data, and the least square method was used to establish a linear regression prediction model. Multiple groups of rescue time and road restoration time were obtained under different conditions, and the optimal linear regression function was obtained.

[0096] Step 3.5: Verify the validity of the decision function

[0097] The established regression model is evaluated and the effectiveness of the decision model is verified in a simulation environment. Under a given accident scenario, the accident scenario road operation indicators are collected and input into the decision model to obtain the solution decision results. The results are tested in the simulation scenario and compared with the total time indicators of other solution combinations for verification.

[0098] Accordingly, a SUMO-based highway reconstruction and expansion simulation scenario construction and its evacuation and rescue decision-making system includes: a model building module, a traffic simulation module and a result verification module; the model building module is based on the rescue and evacuation route plan during the highway reconstruction and expansion period, combined with traffic flow operation parameters to establish a dynamic plan combination decision model; the traffic simulation module uses SUMO simulation software to perform traffic simulation during the highway reconstruction and expansion period, and simulates the traffic operation status of the reconstruction and expansion section under the traffic accident state; the result verification module realizes multiple rescue and evacuation routes in the reconstruction and expansion simulation, collects simulation data and performs regression fitting on the decision model, statistically analyzes the simulation results and verifies the effectiveness of the decision model.

[0099] The above shows and describes the basic principles and main processes of the present invention, focusing on rescue and evacuation decisions in the scenario of highway reconstruction and expansion. A simulation scenario of highway reconstruction and expansion is constructed, and a regression decision model is fitted based on the traffic flow parameters in the simulation scenario. The optimal rescue and evacuation plan in the accident scenario is effectively found, helping traffic flow to return to normal operation. The plan and decision are simulated and verified to illustrate the effectiveness of the decision-making method. The present invention focuses on a dynamic system framework with high compatibility. It can provide rescue and evacuation decisions for reconstruction and expansion accident scenarios in various states, effectively improving rescue efficiency and reducing the impact of accidents on traffic.

Claims

1. A SUMO-based highway reconstruction and expansion simulation scenario construction and evacuation and rescue decision-making method, characterized by: The steps include: Step 1: Based on the rescue and evacuation route plan during the highway reconstruction and expansion period, a dynamic scheme combination decision model is established in combination with traffic flow operation parameters. The specific steps include the following: Step 11: Analyze conventional rescue routes for accident scenarios during the highway reconstruction and expansion period, and determine feasible rescue routes based on the actual conditions of the road section, so that rescue vehicles can enter the highway through the nearest interchanges upstream and downstream of the highway and reach the accident scene; Step 12: Analyze the conventional vehicle evacuation routes after the rescue operation at the accident scene, and determine feasible evacuation routes based on the actual rescue situation to enable stranded vehicles to quickly leave the accident scene; Step 13: Establish a decision regression model. When an accident occurs and blocks all traffic in one direction, the rescue time and road restoration time required for different evacuation routes and rescue routes are calculated based on the traffic status indicators at the time of the accident, and the optimal matching solution between the rescue route and the evacuation route is determined. The specific steps of establishing the decision regression model are as follows: v ij =b ij,0 +b ij.1 X ij,2 +b ij,3 X ij,4 +...+b ij,n X ij,n +e Among them, X ij,1 ,X ij,2 ,...,X ij,n is the independent variable X ij The n eigencomponent matrix of ; and are predicted values, all calculated by the regression model; v ij and c ij are real values, which are obtained from a large amount of simulation data in the early stage; and is the average of all true values; β ij,0 ,β ij,1 ,...,β ij,n and γ ij,0 ,γ ij,1 ,...,γ ij,n is the model parameter vector, each component of which is the parameter of each combination of evacuation route and rescue route, which is the optimization object; the subscript ij represents the i-th evacuation plan combined with the j-th rescue plan; Step 2: Use SUMO simulation software to conduct traffic simulation during the highway reconstruction and expansion period, simulating the traffic operation status of the reconstruction and expansion section under the traffic accident state; Step 3: Implement multiple rescue and evacuation routes in the renovation and expansion simulation, collect simulation data and perform regression fitting on the decision model, statistically analyze the simulation results and verify the effectiveness of the decision model.

2. The SUMO-based highway reconstruction and expansion simulation scenario construction and evacuation and rescue decision-making method as claimed in claim 1 is characterized in that: In step 2, SUMO simulation software is used to simulate traffic during the highway reconstruction and expansion period. The simulation of traffic operation status of the reconstruction and expansion section under the traffic accident state specifically includes the following steps: Step 21: Build a SUMO simulation environment. Extract highway sections from the map database and import them into SUMO. Use SUMO's netedit interface to modify the simulated section attributes based on the actual conditions of the reconstruction and expansion area. Close the emergency lane and add an expansion road. Collect relevant data on the highway reconstruction and expansion area, including traffic flow and vehicle speed, to build a basic simulation environment. Step 22: Determine the number of emergency rescue points and rescue vehicles based on the emergency rescue and accident situation. Add the information of the emergency rescue points and rescue vehicles to the simulation environment. Apply a path search algorithm to search for the shortest path from the emergency rescue point to the evacuation point in the road network. Evaluate the searched path, taking into account road congestion and vehicle speed factors, and calculate the feasibility and efficiency of the path. Step 23: Preheat the simulation scene, set the accident point location, simulate the accident and implement relevant control measures; Step 24: Based on the characteristics of the highway reconstruction and expansion area, in order to maintain consistency with normal traffic conditions, a special simulated road and a special driving route are built, and a reverse emergency lane is set on the inner side of the simulated road. The opening condition of the lane is set to that there are no vehicles in the corresponding forward lane, that is, all vehicles have been evacuated.

3. The SUMO-based highway reconstruction and expansion simulation scenario construction and evacuation and rescue decision-making method as claimed in claim 1 is characterized in that: In step 3, multiple rescue and evacuation routes are implemented in the reconstruction and expansion simulation, simulation data is collected and regression fitting is performed on the decision model, simulation results are statistically analyzed, and the effectiveness of the decision model is verified. The specific steps include the following: Step 31: By giving the evacuation routes of congested vehicles, evacuate the vehicles at the accident site and control the upstream and downstream traffic flows to simulate the evacuation process. By giving the number of rescue vehicles and the driving routes, simulate the emergency rescue process. Step 32: Wait for the road to be cleared and end the simulation, and simultaneously collect simulation data, including emergency rescue time, evacuation time, and vehicle congestion; The simulation results were analyzed and evaluated based on three scenarios: two-way traffic in the opposite lane, U-turn on the central median, and two-way short release. Step 33: Clean the simulation data, process missing values ​​and outliers, and perform normalization and dimensionality reduction. Step 34: Fit the regression model based on the obtained simulation data, and use the least squares method to establish a linear regression prediction model. Under different conditions, multiple sets of rescue time and road traffic restoration time are obtained to obtain the best linear regression function. Step 35: Evaluate the established regression model and verify the effectiveness of the decision model in a simulation environment. Under a given accident scenario, collect the accident scenario road traffic operation indicators, input them into the decision model to obtain the solution decision results, test them in the simulation scenario, and compare and verify them with the total time indicators of other solution combinations.

4. The SUMO-based highway reconstruction and expansion simulation scenario construction and evacuation and rescue decision-making method as claimed in claim 3 is characterized in that: In step 31, by giving the evacuation routes of congested vehicles, the vehicles at the accident site are evacuated, and the upstream and downstream traffic flows are controlled to simulate the evacuation process. By giving the number of rescue vehicles and the driving routes, the simulation of the emergency rescue process specifically includes the following steps: Step 311: Determine the initial conditions of the route, set the rescue vehicle and emergency evacuation point, define the rescue vehicle ID and the location of the emergency evacuation point in route.rou.xml; initialize the route information, and configure the initial route for each rescue vehicle. These routes are based on the pre-set traffic network and feasible driving paths; Step 312: Start the simulation using the Traci interface, and execute each simulation step repeatedly by looping until the set conditions are met or the rescue / evacuation is completed. During the simulation, the rescue vehicle's route is dynamically adjusted according to the real-time traffic conditions and road network status. Step 313: Modify the vehicle driving settings to avoid the vehicle from detouring due to encountering congested areas or accident scenes; Step 314: By monitoring the arrival of the rescue vehicle at key road nodes, determine whether the route needs to be adjusted. If the rescue vehicle is close to the accident scene, it is necessary to adjust the driving path according to the set rescue route, that is, select one of the upward forward rescue, downward forward rescue, and downward reverse rescue directions; Step 315: When the simulation reaches the set step length, the evacuation simulation begins, and the vehicles on the edge before the accident section drive along the evacuation route. Step 316: The rescue vehicle drives away from the accident edge, and the vehicle drives on the accident edge. The simulation runs normally until the step ends.

5. A system for constructing a SUMO-based highway reconstruction and expansion simulation scenario and its evacuation and rescue decision-making method according to claim 1, characterized in that: include: Model building module, traffic simulation module and result verification module; The model building module establishes a dynamic scheme combination decision model based on the rescue and evacuation route plans during the highway reconstruction and expansion period, combined with traffic flow operation parameters; the traffic simulation module uses SUMO simulation software to simulate traffic during the highway reconstruction and expansion period, simulating the traffic operation status of the reconstruction and expansion section under the state of traffic accidents; the result verification module implements multiple rescue and evacuation routes in the reconstruction and expansion simulation, collects simulation data and performs regression fitting on the decision model, statistically analyzes the simulation results and verifies the effectiveness of the decision model.

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