A Distributed Microscopic Traffic Simulation Method for Highways Based on Vehicle Group Decomposition

Abstract

The present invention belongs to the field of intelligent transportation technology, and specifically discloses a method for highway distributed micro-traffic simulation based on vehicle group decomposition. The method first configures simulation data and parameters in the simulation startup phase; then the road network status and vehicle position decompose all vehicles on the road into several vehicle groups; secondly, the vehicle status of all vehicle groups is synchronously updated by distributed simulation; finally, it is judged whether the simulation is finished according to the simulation time. The present invention improves the simulation efficiency by dividing a large-scale simulation task into multiple small-scale simulation tasks by means of vehicle group decomposition, and performs synchronous calculations through distributed simulation, thereby meeting the large-scale and high-complexity requirements of highway micro-traffic simulation. And by considering the influence of weather factors and special vehicles in the process of vehicle group decomposition for refined decomposition, the authenticity and accuracy of the simulation are enhanced.

Description

Technical Field

[0001] The invention belongs to the field of intelligent transportation technology and relates to a highway distributed microscopic traffic simulation method based on vehicle group decomposition. Background Art

[0002] With the development of intelligent transportation, highways, as a test site for the deep integration and innovation of new technologies such as Beidou, 5G, big data, Internet of Things, cloud computing, and artificial intelligence, are representatives of the integrated development of traditional infrastructure and new infrastructure, and are also the future development trend of highway transportation. In the actual production process, directly using new technologies for on-site testing will lead to high implementation costs and major safety hazards. Simulation technology is an effective means to reproduce the essential process of evolution in the actual system through model deduction, thereby analyzing the application effects of different equipment and solutions on highways.

[0003] With the growth of highway scale, complexity of environment and diversification of scenarios, the computational load of highway micro-traffic simulation continues to increase. The efficiency of conventional simulation calculations cannot meet the requirements of application scenarios and has certain limitations.

[0004] Prior art, such as the Chinese invention patent application with application publication number CN202310913874.5, discloses a real-time microscopic traffic simulation method and system for a highway network based on SUMO, which utilizes real-time fusion data to dynamically update the traffic flow and vehicle behavior model to improve the time effectiveness of the SUMO simulation model and output single-vehicle-level and traffic flow indicator data.

[0005] Existing technologies, such as the Chinese invention patent application with application publication number CN202310132182.7, discloses a dynamic prediction method and system for highway bottlenecks based on micro-traffic simulation. It uses Vissim simulation software to draw basic sections and ramp sections of highways, inputs traffic volume and vehicle flow ratio, evaluates and outputs data, and evaluates the status of future bottleneck points based on predicted future traffic demand, thereby improving the accuracy of highway bottleneck prediction.

[0006] Another example of prior art is the highway congestion tracing analysis and control method based on micro-traffic simulation disclosed in the Chinese invention patent application with application publication number CN202211654602.X. It uses micro-traffic simulation to analyze road section congestion, accurately controls congested sections, improves the overall operating efficiency of the highway, and achieves an improvement in the overall operating status and service level of the highway.

[0007] Although the above-mentioned existing technologies can solve some problems in their respective corresponding scenarios, they are unable to solve the problem of insufficient efficiency of microscopic traffic simulation on large-scale highways. Summary of the invention

[0008] In view of this, in order to solve the problems raised in the above background technology, a highway distributed microscopic traffic simulation method based on vehicle group decomposition is proposed.

[0009] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides a highway distributed micro-traffic simulation method based on vehicle group decomposition, the method comprising the following steps: Step 1, simulation start: configure simulation road network data, simulation traffic data, weather parameters and simulation parameters.

[0010] Step 2: Vehicle group decomposition and update: Extract the real-time vehicle sequence data of each road section, and decompose and update the vehicle group based on it.

[0011] Step 3: Distributed simulation promotion of vehicle groups: Real-time update of vehicle status in each vehicle group.

[0012] Step 4: Simulation end judgment: Set the simulation end condition. If the simulation end condition is met, end the simulation. If the simulation end condition is not met, return to step 2.

[0013] In a preferred embodiment of the present invention, the simulated road network data includes section length, section speed limit, number of section lanes, entrance and exit ramp locations, and section node locations.

[0014] In a preferred embodiment of the present invention, the specific configuration process of configuring the simulated road network data is as follows: the road network is divided into a number of continuous road sections according to the positions of the road section nodes, and a continuous road section area set A is constructed.

[0015] Define the spatial area X corresponding to each continuous road segment s , s represents the number of each continuous road section, s = 1, 2, ... n.

[0016] In a preferred embodiment of the present invention, the simulated traffic data includes road network entrance traffic, entrance ramp traffic, and exit ramp traffic.

[0017] In a preferred embodiment of the present invention, the weather parameters are configured as follows: according to the boundaries of different weather environments, the continuous road segment area set A is weather marked, and the spatial area X corresponding to each continuous road segment is updated accordingly. s .

[0018] In a preferred embodiment of the present invention, the simulation parameters include simulation duration, upper limit of capacity of a single vehicle group and simulation step length.

[0019] In a preferred embodiment of the present invention, the specific execution process of step 2 is as follows: B1, updating the vehicle segment sequence ID of each continuous segment s .

[0020] B2. The vehicle segment sequence IDs of each continuous segment are divided according to the upper limit of the capacity of a single vehicle group. s Decompose into several vehicle group sequences and construct the vehicle group sequence set F for each continuous road section s , and record the sequence of each vehicle group corresponding to each continuous road section as ID s,m , m represents the sequence of each vehicle group, m=1,2,......M, m∈F s , all vehicle group sequences in the sth continuous road segment are equivalent to the vehicle road segment sequence ID s , ID s,1 ∪ID s,2 ∪......ID s,M =ID s .

[0021] B3, when the vehicle group sequence ID s,m It includes setting special vehicles, marking the vehicle group sequence, decomposing the vehicle group sequence separately, and assigning ID s,m Expand to ID s,m-1 、ID s,m-2 and ID s,m-3 , ID s,m-2 For the vehicle group that includes the set special vehicles, the vehicle group sequence set F of the continuous road section is updated at the same time s .

[0022] In a preferred embodiment of the present invention, the updating rule of the vehicle segment sequence is as follows: when the vehicle position enters the continuous segment space area X s , the vehicle is determined to be located in the sth continuous road segment, that is, the vehicle serial number is added to the vehicle road segment sequence ID corresponding to the sth continuous road segment. s middle.

[0023] When the vehicle position leaves the continuous road segment space area X s When the vehicle is not located in a continuous section, it is determined that the vehicle is located in the sth continuous section, and the vehicle section sequence ID corresponding to the sth continuous section is s Delete the vehicle serial number.

[0024] In a preferred embodiment of the present invention, the real-time updating of the vehicle status in each vehicle group includes: updating the vehicle group sequence ID of all continuous road sections according to the vehicle following model; s,m The longitudinal position of the vehicles in the system is updated synchronously.

[0025] According to the vehicle lane-changing model, the vehicle group sequence for all continuous sections is calculated. The vehicle group sequence for all continuous sections is calculated. s,m The lateral positions of the vehicles in the system are updated synchronously.

[0026] In a preferred embodiment of the present invention, the simulation end condition is that the accumulated simulation step length is less than the simulation duration.

[0027] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention reduces the scale of highway micro-traffic simulation problems by decomposing vehicle groups, and accelerates the calculation speed by distributed simulation, effectively solving the problem of insufficient efficiency of current large-scale highway micro-traffic simulation and meeting the large-scale and high-complexity requirements of highway micro-traffic simulation.

[0028] (2) The present invention realizes the grouping of all vehicles on the expressway network by utilizing vehicle group decomposition, and divides all vehicles into several vehicle groups according to the road section and specific location of the vehicles, thereby reducing the scale of the simulation problem and improving the convenience and operability of the simulation.

[0029] (3) The present invention utilizes a distributed simulation framework to synchronously update the vehicle status of all vehicle groups, thereby achieving the deduction of the status of all vehicles in the road network and effectively reducing the simulation calculation time of each step, thereby greatly improving the simulation efficiency.

[0030] (4) The present invention further refines the vehicle group decomposition method according to weather parameters, and then configures the weather environment of each vehicle group, thereby enhancing the authenticity of the simulation. In addition, by separately dividing special vehicle groups, the simulation environment of special vehicles can be separately configured, and refined simulation and refined decomposition of vehicle groups can be achieved, thereby enhancing the authenticity and accuracy of the simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0032] Figure 1 It is a schematic diagram of the connection of each module of the system of the present invention.

[0033] Figure 2 This is a schematic diagram of the decomposition of a vehicle group on a one-way two-lane highway in Example 1.

[0034] Figure 3 This is a schematic diagram of the distributed simulation of a vehicle group on a one-way two-lane highway in Example 1.

[0035] Figure 4 This is a schematic diagram of the vehicle group decomposition of the road network including four expressways in Example 2.

[0036] Figure 5This is a schematic diagram of the distributed simulation of vehicle groups on a road network including four highways in Example 2. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] Embodiment 1

[0039] See also Figure 1 and Figure 2 As shown, the invention content is explained by taking a one-way two-lane highway as an example. The present invention provides a highway distributed microscopic traffic simulation method based on vehicle group decomposition, the method comprising: step one, simulation start: configuring simulation road network data, simulation traffic data, weather parameters and simulation parameters.

[0040] Specifically, the simulated road network data includes the length of the section, the speed limit of the section, the number of lanes in the section, the entrance and exit ramp locations and the section node locations. In the present embodiment, the section length is 10 kilometers, the speed limit of the section is 120 kilometers per hour, and the number of lanes in the section is 2. Since there are no section nodes in a single section in the present embodiment, the road network is not divided, and the definition of continuous section sets and spatial areas is not performed.

[0041] Specifically, the simulated traffic data includes the road network entrance traffic, entrance ramp traffic, and exit ramp traffic, and in this embodiment, the road network entrance traffic, entrance ramp traffic, and exit ramp traffic are taken as 3500 standard vehicles / hour.

[0042] Specifically, the simulation parameters include simulation duration, the upper limit of the capacity of a single vehicle group and the simulation step length. In this embodiment, the simulation duration is 6000 seconds, the upper limit of the capacity of a single vehicle group is 100 standard vehicles, and the simulation step length is 1 second.

[0043] In yet another specific aspect, weather parameters include, but are not limited to, sunny days, rainy days, and snowy days.

[0044] Step 2: Vehicle group decomposition and update: Extract the real-time vehicle sequence data of each road section, and perform vehicle group decomposition and vehicle group update based on it, including: B1, update the vehicle segment sequence ID of each continuous road section s .

[0045] When the vehicle position enters the continuous road segment space area X s, the vehicle is determined to be located in the sth continuous road segment, that is, the vehicle serial number is added to the vehicle road segment sequence ID corresponding to the sth continuous road segment. s middle.

[0046] When the vehicle position leaves the continuous road segment space area X s When the vehicle is not located in a continuous section, it is determined that the vehicle is located in the sth continuous section, and the vehicle section sequence ID corresponding to the sth continuous section is s Delete the vehicle serial number.

[0047] In a specific embodiment, the specific updating process in step B1 is illustrated as follows: the number of vehicles on the way on consecutive road segments is N, and a vehicle road segment sequence ID is constructed, ID = {1, 2, 3, ..., N-1, N}.

[0048] When a vehicle enters a road section, the newly added vehicle serial number NEW is added to the vehicle road section sequence ID, ID = {NEW, 1, 2, 3, ..., N-1, N};

[0049] When a vehicle leaves a road section, for example, a vehicle with a vehicle number N leaves a road section, the vehicle number is deleted from the vehicle road section sequence ID, ID = {NEW, 1, 2, 3, ..., N-1}.

[0050] B2. The vehicle segment sequence IDs of each continuous segment are divided according to the upper limit of the capacity of a single vehicle group. s Decompose into several vehicle group sequences and construct the vehicle group sequence set F for each continuous road section s , and record the sequence of each vehicle group corresponding to each continuous road section as ID s,m , m represents the sequence of each vehicle group, m=1,2,......M, m∈F s , all vehicle group sequences in the sth continuous road segment are equivalent to the vehicle road segment sequence ID s , ID s,1 ∪ID s,2 ∪......ID s,M =ID s .

[0051] B3, when the vehicle group sequence ID s,m It includes setting special vehicles, marking the vehicle group sequence, decomposing the vehicle group sequence separately, and assigning ID s,m Expand to ID s,m-1 、ID s,m-2 and ID s,m-3 , ID s,m-2 For the vehicle group that includes the set special vehicles, the vehicle group sequence set F of the continuous road section is updated at the same time s .

[0052] In a specific embodiment, the specific decomposition process of vehicle group decomposition is exemplified as follows: according to the upper limit of the capacity of a single vehicle group being 100 standard vehicles, each vehicle section sequence of the road section is decomposed into M vehicle group sequences, which are represented in sequence as follows: vehicle group sequence 1: {1, 2, ..., 100}, vehicle group sequence 2: {101, 102, ..., 200}, vehicle group sequence 3: {201, 202, ..., 300}, ... vehicle group sequence M: {99×M+1, 99×M+2, ..., 100×M}.

[0053] The embodiment of the present invention realizes the grouping of all vehicles on the expressway network by utilizing the vehicle group decomposition method, and divides all vehicles into several vehicle groups according to the road section and specific location of the vehicles, thereby reducing the scale of the simulation problem and improving the convenience and operability of the simulation.

[0054] Step 3: Distributed simulation of vehicle groups: Real-time update of the vehicle status in each vehicle group, including: synchronous update of the longitudinal position of all vehicles in the vehicle group sequence according to the vehicle following model, specifically, establishing M simulation processes, corresponding to each vehicle group in turn, such as Figure 3 shown.

[0055] According to the vehicle lane-changing model, the lateral positions of all vehicles in the vehicle group sequence are synchronously updated. Specifically, M simulation processes are established respectively, corresponding to each vehicle group in turn, such as Figure 3 shown.

[0056] It should be added that the vehicle following model and the vehicle lane changing model are relatively mature models currently available, and their specific execution process and execution principles will not be elaborated here.

[0057] The embodiment of the present invention synchronously updates the vehicle status of all vehicle groups by utilizing a distributed simulation framework, thereby achieving the deduction of the status of all vehicles in the road network and effectively reducing the simulation calculation time of each step, thereby greatly improving the simulation efficiency.

[0058] Step 4: Simulation end judgment: Set the simulation end condition. If the simulation end condition is met, end the simulation. If the simulation end condition is not met, return to step 2.

[0059] Specifically, the simulation end condition is that the cumulative simulation step is less than the simulation duration. In this embodiment, the simulation duration is 6000 seconds and the simulation step is 1 second, that is, 6000 cycles are required.

[0060] The embodiments of the present invention reduce the scale of highway micro-traffic simulation problems by decomposing vehicle groups, and accelerate the calculation speed through distributed simulation, thereby effectively solving the problem of insufficient efficiency of current large-scale highway micro-traffic simulation and meeting the large-scale and high-complexity requirements of highway micro-traffic simulation.

[0061] Embodiment 2

[0062] like Figure 4 As shown, the invention content is explained by taking a road network including four expressways as an example.

[0063] Step 1: Start the simulation, including: 1) Configure the simulation network data: Configure the road network of four one-way two-lane expressway lines, with an average length of 10 kilometers, a speed limit of 120 kilometers per hour, and 2 lanes. The road network is divided into 4 continuous sections according to the node positions, and a continuous section area set A is constructed, where A = {line 1, line 2, line 3, line 4}. At the same time, the spatial area X included in each continuous section is defined. s , X s ={X 线路1 ,X 线路2 ,X 线路3 ,X 线路4}, s represents the number of each continuous road section, s = 1, 2, 3, 4.

[0064] 2) Configure simulation traffic data: Configure the entrance traffic, entrance ramp traffic and exit ramp traffic of four one-way two-lane expressway lines to be 3500 standard vehicles per hour.

[0065] 3) Configure simulation parameters: Set the simulation duration to 6000 seconds, the upper limit of the capacity of a single vehicle group to 100 standard vehicles, and the simulation step to 1 second.

[0066] Step 2: Vehicle group decomposition and update: Extract the real-time vehicle sequence data of each road section, and decompose and update the vehicle group based on it.

[0067] Specifically, the specific process of step two is as follows: Y1. Record the vehicles on the four road sections as N1, N2, N3 and N4 respectively, and construct a vehicle section sequence, which is: ID1 = {1,2,...,N-1,N1}, ID1 = {1,2,...,N-1,N2}, ID1 = {1,2,...,N-1,N3}, ID1 = {1,2,...,N-1,N4}.

[0068] Y2. When a vehicle enters a road section, the newly added vehicle serial number NEW is added to the vehicle road section sequence. Taking road section 1 as an example, ID1 = {NEW, 1, 2, ..., N-1, N1}.

[0069] Y3. When a vehicle leaves the road section, for example, a vehicle with a vehicle serial number of N1 leaves the road section, the vehicle serial number is deleted from the vehicle road section sequence, ID1 = {NEW, 1, 2, ..., N-1}.

[0070] Y4. According to the upper limit of the capacity of a single vehicle group of 100 standard vehicles, the vehicle segment sequences of Section 1, Section 2, Section 3 and Section 4 are decomposed into vehicle groups M1, M2, M3 and M4:

[0071] It should be added that the vehicle group sequence of section 1 is: ID 1,1 ={1,2,...,100}, ID 1,2 ={101,102,...,200},...

[0072] Among them, the vehicle group sequence of section 2 is: ID 2,1 ={1,2,...,100}, ID 2,2 ={101,102,...,200},...

[0073] Among them, the vehicle group sequence of section 3 is: ID 3,1 ={1,2,...,100}, ID 3,2 ={101,102,...,200},...

[0074] Among them, the vehicle group sequence of section 4 is: ID 4,1 ={1,2,...,100}, ID 4,2 ={101,102,...,200},...

[0075] Step 3: Distributed simulation of vehicle groups: Real-time update of the vehicle status in each vehicle group, including: synchronous update of the longitudinal position of all vehicles in the vehicle group sequence according to the vehicle following model, specifically establishing M1+M2+M3+M4 simulation processes, corresponding to each vehicle group in turn, such as Figure 5 shown.

[0076] According to the vehicle lane-changing model, the lateral positions of all vehicles in the vehicle group sequence are synchronously updated. Specifically, M1+M2+M3+M4 simulation processes are established respectively, corresponding to each vehicle group in turn, such as Figure 5 shown.

[0077] Step 4: Simulation end judgment: Set the simulation end condition. If the simulation end condition is met, end the simulation. If the simulation end condition is not met, return to step 2.

[0078] It should be added that the simulation end condition is the same as the simulation end condition in the first embodiment and will not be described again.

[0079] Embodiment 3

[0080] When different weather parameters are included, the weather parameters are configured. The specific configuration process is as follows: the four continuous road sections formed after the road network division constitute a continuous road section area set A, where A = {line 1, line 2, line 3, line 4}.

[0081] Assuming that part of route 4 is cloudy and part is rainy, route 4 is marked with weather conditions, such as: -阴天 ,Line 4 -小雨}, update the continuous road section area set A to A = {Route 1, Route 2, Route 3, Route 4 -阴天 ,Line 4 -小雨}.

[0082] Embodiment 4

[0083] When a special vehicle is included, it is assumed that the vehicle group sequence of section 1 includes the special vehicle, and then the B3 step is described by an example, which is specifically described as follows: the vehicle group sequence of section 1 after the vehicle group decomposition is recorded as ID 1,1 ={1,2,...,100}, ID 1,2 ={101,102,...,200},...

[0084] Assumption ID 1,1 Vehicles with serial numbers 50 to 60 are set as special vehicles, so 1,1 Expands to: ID 1,1-1 ={1,2,...49}, ID 1,1-2 ={50,51,...60}, ID 1,1-3 ={61,62,...100}.

[0085] The embodiment of the present invention further refines the vehicle group decomposition method according to weather parameters, and then configures the weather environment of each vehicle group, thereby enhancing the authenticity of the simulation. In addition, by separately dividing special vehicle groups, the simulation environment of special vehicles can be separately configured, and refined simulation and refined decomposition of vehicle groups can be achieved, thereby enhancing the authenticity and accuracy of the simulation.

[0086] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A highway distributed microscopic traffic simulation method based on vehicle group decomposition, characterized by: The method comprises the following steps: Step 1: Start the simulation: configure the simulated road network data, simulated traffic data, weather parameters and simulation parameters; Step 2: Vehicle group decomposition and update: extract the real-time vehicle sequence data of each road section, and perform vehicle group decomposition and vehicle group update based on the data; Step 3: Distributed simulation promotion of vehicle groups: real-time update of vehicle status in each vehicle group; Step 4, simulation end judgment: set the simulation end condition, if the simulation end condition is met, end the simulation; if the simulation end condition is not met, return to step 2; The simulation parameters include the upper limit of the capacity of a single vehicle group; The specific implementation process of step 2 is as follows: B1. Update the vehicle segment sequence of each continuous segment ; B2. Sequence the vehicle sections of each continuous section according to the upper limit of the capacity of a single vehicle group. Decompose into several vehicle group sequences and construct a set of vehicle group sequences for each continuous road section , and record the sequence of each vehicle group corresponding to each continuous road section as , represents the sequence of each vehicle group, , , No. All vehicle group sequences in a continuous road segment are equivalent to the vehicle segment sequence , ; B3, when the vehicle group sequence It includes setting special vehicles, marking the vehicle group sequence, decomposing the vehicle group sequence separately, and Expand to , and , For a group of vehicles that includes a set of special vehicles, update the group sequence set of continuous sections at the same time .

2. The method for highway distributed microscopic traffic simulation based on vehicle group decomposition according to claim 1 is characterized by: The simulated road network data includes road section length, road section speed limit, road section lane number, entrance and exit ramp locations and road section node locations.

3. The highway distributed microscopic traffic simulation method based on vehicle group decomposition according to claim 2 is characterized by: The specific configuration process of configuring the simulation road network data is as follows: Divide the road network into several continuous sections according to the location of the section nodes, and construct a continuous section area set ; Define the spatial area corresponding to each continuous road segment , Indicates the number of each continuous road segment, .

4. The highway distributed microscopic traffic simulation method based on vehicle group decomposition according to claim 1 is characterized by: The simulated traffic data includes road network entrance traffic, entrance ramp traffic, and exit ramp traffic.

5. The highway distributed microscopic traffic simulation method based on vehicle group decomposition according to claim 3 is characterized by: Configure weather parameters. The specific configuration process is as follows: According to the boundaries of different weather environments, continuous road sections are grouped together Perform weather annotation and update the spatial area corresponding to each continuous road segment accordingly .

6. The highway distributed microscopic traffic simulation method based on vehicle group decomposition according to claim 3 is characterized by: The simulation parameters also include simulation duration and simulation step length.

7. The highway distributed microscopic traffic simulation method based on vehicle group decomposition according to claim 1 is characterized by: The updating rules of the vehicle segment sequence are as follows: When the vehicle position enters the continuous road segment space area When the vehicle is determined to be in the In a continuous road section, the vehicle serial number is added to the The vehicle segment sequence corresponding to the continuous segment middle; When the vehicle position leaves the continuous road segment space area When the vehicle is determined not to be located in the continuous section, In a continuous section, from The vehicle segment sequence corresponding to the continuous segment Delete the vehicle serial number.

8. The method for highway distributed microscopic traffic simulation based on vehicle group decomposition according to claim 1 is characterized by: The real-time updating of the vehicle status in each vehicle group includes: According to the vehicle following model, the vehicle group sequence of all continuous sections The longitudinal positions of the vehicles in the system are updated synchronously; According to the vehicle lane-changing model, the vehicle group sequence of all continuous sections The lateral positions of the vehicles in the system are updated synchronously.

9. The highway distributed microscopic traffic simulation method based on vehicle group decomposition according to claim 6 is characterized by: The simulation end condition is that the cumulative simulation step length is less than the simulation duration.

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