Scheme verification method based on vehicle and road cloud integrated system simulation

Abstract

The invention discloses a scheme verification method based on vehicle and road cloud integrated system simulation, and belongs to the technical field of intelligent driving, and the technical key points are that the method comprises the following steps: 1, importing a basic map, editing road facilities, importing a dynamic traffic flow, and generating a specific simulation scene; 2, a vehicle dynamics model and a vehicle end sensor model are built, an automatic driving algorithm is imported, and an automatic driving simulation vehicle is built; step 3, cloud control platform docking is carried out, and a communication mode is established through the cloud control platform; 4, carrying out a simulation test, collecting traffic information, issuing the traffic information to the cloud control platform and the intelligent networked automobile, and receiving a task and roadside information issued by the cloud control platform by the intelligent networked automobile; and step 5, simulation result analysis: evaluating a test result from multiple dimensions, and outputting an evaluation result, and the system has the advantages of continuously uploading vehicle state information and roadside sensing information, and issuing a cloud instruction, so that the whole system is organically combined.

Description

Technical Field

[0001] The present invention relates to the field of intelligent driving technology, and in particular to a solution verification method based on vehicle-road-cloud integrated system simulation. Background Art

[0002] In the fields of automotive technology, intelligent driving and simulation testing, simulation of autonomous driving is becoming increasingly important. On the one hand, it can greatly save manpower and material resources, avoid the waste of resources by immature algorithms and the loss caused by potential safety hazards. On the other hand, in the "Guidelines for the Management of Access of Intelligent Connected Vehicle Manufacturers and Products (Trial) (Draft for Comments)", requirements for simulation testing are put forward. If intelligent connected vehicle companies want to complete product access, they must also join the simulation testing link. At the same time, software-in-the-loop simulation can be tested repeatedly, which can verify the robustness of the algorithm and ensure the safety of dangerous working conditions that are difficult to measure in reality.

[0003] With the introduction of the concept of "vehicle-road-cloud integration" and the continuous enrichment of its connotation, the large-scale construction and application of intelligent connected vehicles, road-road-cloud integration are also exploring the implementation process. Intelligent connected vehicles, roadside intelligent equipment, central cloud, regional cloud and edge cloud platforms should organically combine various parts to realize the management of urban intelligent connected vehicles. How to effectively demonstrate the overall effectiveness of the plan and how to provide practical solutions in the early stage are urgent problems to be solved. Twin simulation of actual scenarios and system simulation of vehicle-road-cloud integration are carried out to verify the feasibility of the plan. The current simulation technology mainly focuses on the simulation of vehicle algorithms. The simulation of roadside equipment and the access to the cloud control platform are not involved in the integration of vehicle-road-cloud. For the construction of vehicle-road-cloud integration, the solution verification method for verifying the simulation of the overall solution is still blank. Summary of the invention

[0004] In view of the deficiencies in the prior art, an embodiment of the present invention aims to provide a solution verification method based on vehicle-road-cloud integrated system simulation to solve the problems in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: A solution verification method based on vehicle-road-cloud integrated system simulation includes the following steps: Step 1: Import basic maps, edit road facilities and dynamic traffic flows, and generate specific simulation scenarios; Step 2: Build the vehicle dynamics model and vehicle-side sensor model, import the autonomous driving algorithm, and build the autonomous driving simulation vehicle; Step 3: Connect to the cloud control platform and establish communication through the cloud control platform; Step 4: Conduct simulation tests, collect traffic information and publish it to the cloud control platform and intelligent connected vehicles. The intelligent connected vehicles receive tasks and roadside information issued by the cloud control platform. Step 5: Simulation result analysis: evaluate the test results from multiple dimensions and output the evaluation results.

[0006] As a further solution of the present invention, the generation of the specific simulation scene in step 1 includes importing a basic map, editing road facilities and importing dynamic traffic flows; Basic map import, import standard format map into the scene; Edit road facilities and arrange intelligent roadside equipment such as roadside units; Dynamic traffic flow import: import dynamic traffic flow from traffic flow simulation software and perform joint simulation.

[0007] As a further solution of the present invention, the autonomous driving simulation vehicle construction in step 2 includes vehicle model construction and vehicle algorithm introduction; Vehicle model construction, including the construction of vehicle dynamics model and vehicle-side sensor model; Vehicle algorithm import, connect the autonomous driving algorithm to the corresponding vehicle to enable it to have autonomous driving capabilities.

[0008] As a further solution of the present invention, the simulation test in step five runs the simulation system to test and verify the efficiency of the overall vehicle-road-cloud integration solution.

[0009] As a further solution of the present invention, the simulation result analysis in step five includes analyzing the evaluation output, and the analysis is performed based on the data of the simulation test process.

[0010] A solution verification method based on vehicle-road-cloud integrated system simulation includes systems and modules, including the following systems and modules: A scenario system that imports scenario-specific maps in a standard format, sets static obstacles, imports roadside modules into the scenario, and accesses dynamic traffic flows through interfaces; A vehicle system that configures the parameters of the dynamic model and sensor model of the simulated vehicle to make it fit the real vehicle to the greatest extent possible, and connects to the algorithm module to enable the vehicle to drive automatically; A cloud control system, communication interface + cloud control platform, which can access the complete city-level service management platform in the simulation system, and can also access the parts related to the vehicle side and road side; An analysis system analyzes and evaluates the current solution from multiple dimensions based on the data generated during the overall operation of the simulation system, and generates an evaluation report with charts.

[0011] As a further solution of the present invention, the scene system further includes: A map module that imports standard format maps into the scene to form a static map basis; A roadside module to configure the type, quantity and distribution of roadside equipment; A traffic flow module is connected to the dynamic traffic flow to achieve joint simulation with the traffic flow simulation software.

[0012] As a further solution of the present invention, the vehicle system further includes: A vehicle dynamics module, which makes the physical characteristics of the simulated vehicle close to the real vehicle by selecting the vehicle body and configuring the dynamic parameters; A vehicle-side sensor module that configures the performance, quantity, and location of vehicle-side sensors to form a simulated intelligent driving hardware system; A vehicle algorithm module that connects the autonomous driving algorithm to the simulation system.

[0013] In summary, compared with the prior art, the embodiments of the present invention have the following beneficial effects: The present invention refers to the construction of a vehicle dynamics model and a vehicle-side sensor model through the construction of a vehicle model. By building a vehicle dynamics model, the dynamic parameters of the vehicle are simulated. The vehicle-side sensor model builds the sensor system of the autonomous driving vehicle in a virtual environment based on the physical model. Since more than one vehicle number or model may be built in the large-scale construction and application of vehicle-road-cloud integration, it supports editing and configuring multiple vehicle models and importing them into the scene. The autonomous driving algorithm runs in the environment where the simulation test host is located or other operating systems, such as a dedicated domain controller, and the autonomous driving algorithm drives the simulated vehicle through communication.

[0014] In order to more clearly illustrate the structural features and effects of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 The present invention is a flowchart of a solution verification method based on vehicle-road-cloud integrated system simulation according to an embodiment of the present invention.

[0016] Figure 2 4 is a structural block diagram of a vehicle-road-cloud integrated simulation system according to an embodiment of the present invention.

[0017] Figure 3 Schematic diagram of data flow of a solution verification method based on vehicle-road-cloud integrated system simulation according to an embodiment of the present invention Figure numerals: 1-scenario system, 101-map import interface, 102-traffic flow simulation software communication interface, 11-map module, 12-roadside module, 13-traffic flow module, 2-vehicle system, 201-intelligent driving algorithm communication interface, 21-vehicle dynamics module, 22-vehicle-side sensor module, 23-vehicle algorithm module, 3-cloud control system, 301-cloud control platform communication interface, 4-analysis system DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0020] In one embodiment, a solution verification method based on vehicle-road-cloud integrated system simulation is described in detail in Figure 1 to Figure 3 , including the following steps: Step 1: Import basic maps, edit road facilities and dynamic traffic flows, and generate specific simulation scenarios; Step 2: Build the vehicle dynamics model and vehicle-side sensor model, import the autonomous driving algorithm, and build the autonomous driving simulation vehicle; Step 3: Connect to the cloud control platform and establish communication through the cloud control platform; Step 4: Conduct simulation tests, collect traffic information and publish it to the cloud control platform and intelligent connected vehicles. The intelligent connected vehicles receive tasks and roadside information issued by the cloud control platform. Step 5: Simulation result analysis: evaluate the test results from multiple dimensions and output the evaluation results.

[0021] For further information, see Figure 1 to Figure 3 , the specific simulation scenario generation in step 1 includes basic map import, road facility editing and dynamic traffic flow import; Basic map import, import standard format map into the scene; Edit road facilities and arrange intelligent roadside equipment such as roadside units; Dynamic traffic flow import: import dynamic traffic flow from traffic flow simulation software and perform joint simulation.

[0022] For further information, see Figure 1 to Figure 3 , the autonomous driving simulation vehicle construction in step 2 includes vehicle model construction and vehicle algorithm import; Vehicle model construction, including the construction of vehicle dynamics model and vehicle-side sensor model; Vehicle algorithm import, connect the autonomous driving algorithm to the corresponding vehicle to enable it to have autonomous driving capabilities.

[0023] For further information, see Figure 1 to Figure 3 In the simulation test in step five, the simulation system is run to test and verify the efficiency of the overall vehicle-road-cloud integration solution.

[0024] For further information, see Figure 1 to Figure 3 The simulation result analysis in step five includes analyzing the evaluation output and performing analysis based on the data of the simulation test process.

[0025] A solution verification method based on vehicle-road-cloud integrated system simulation includes systems and modules, including the following systems and modules: A scenario system that imports scenario-specific maps in a standard format, sets static obstacles, imports roadside modules into the scenario, and accesses dynamic traffic flows through interfaces; A vehicle system that configures the parameters of the dynamic model and sensor model of the simulated vehicle to make it fit the real vehicle to the greatest extent possible, and connects to the algorithm module to enable the vehicle to drive automatically; A cloud control system, communication interface + cloud control platform, which can access the complete city-level service management platform in the simulation system, and can also access the parts related to the vehicle side and road side; An analysis system analyzes and evaluates the current solution from multiple dimensions based on the data generated during the overall operation of the simulation system, and generates an evaluation report with charts.

[0026] For further information, see Figure 1 to Figure 3 , the scene system further includes: A map module that imports standard format maps into the scene to form a static map basis; A roadside module to configure the type, quantity and distribution of roadside equipment; A traffic flow module is connected to the dynamic traffic flow to achieve joint simulation with the traffic flow simulation software.

[0027] For further information, see Figure 1 to Figure 3 , the vehicle system further comprises: A vehicle dynamics module, which makes the physical characteristics of the simulated vehicle close to the real vehicle by selecting the vehicle body and configuring the dynamic parameters; A vehicle-side sensor module that configures the performance, quantity, and location of vehicle-side sensors to form a simulated intelligent driving hardware system; A vehicle algorithm module that connects the autonomous driving algorithm to the simulation system In this embodiment, a specific simulation scenario is generated. The first step of the simulation is to build the basic scenario of the simulation, which is the vehicle operating environment of the simulation test and the main functional unit of the roadside intelligent device. It includes basic map import, road facility editing and dynamic traffic flow import.

[0028] Basic map import refers to importing a specific scene map into the scene interface in a standard map format, such as XODR format, and adding other static scene elements such as static obstacles, traffic signs, etc. as the basis for simulation testing.

[0029] Road facility editing refers to the layout editing of road side units (RSU), road side perception, computing and other equipment, and treating them as a whole as part of the intelligent road side infrastructure in the vehicle-road-cloud integration solution.

[0030] Dynamic traffic flow import refers to connecting to dynamic traffic flow software and adding dynamic traffic flow elements based on the constructed static scene.

[0031] The second step of the simulation is to build a simulated vehicle, which is divided into vehicle model building and vehicle algorithm import. It is the core of ordinary autonomous driving simulation testing. In the vehicle-road-cloud integrated system simulation method based on a specific scenario, it is the realization of the vehicle element.

[0032] Vehicle model building refers to the building of vehicle dynamics models and vehicle-side sensor models. The vehicle dynamics model may include the vehicle body, suspension system, steering system, braking system, power system, transmission system, etc. By building the vehicle dynamics model, the dynamic parameters of the vehicle are simulated. The vehicle-side sensor model builds the sensor system of the autonomous driving vehicle in a virtual environment based on the physical model, which may include cameras, radars, lidars, global positioning systems (GPS), inertial measurement units (IMU), ultrasonic radars, etc. Since more than one vehicle may be built in the large-scale construction and application of vehicle-road-cloud integration, it supports editing and configuring multiple vehicle models and importing them into the scene.

[0033] Vehicle algorithm import refers to connecting the autonomous driving algorithm to the corresponding vehicle to enable it to have the ability of autonomous driving. The autonomous driving algorithm runs in the environment where the simulation test host is located or other operating systems, such as a dedicated domain controller, and the autonomous driving algorithm drives the simulated vehicle through communication.

[0034] Cloud control platform docking. After the scene and vehicle are built, the system has the initial ability to run, and the system is docked with the cloud control platform through the communication interface. Intelligent connected vehicles and intelligent roadside facilities upload basic data to the cloud control platform, and the cloud control platform sends instructions to the vehicle and road ends, and monitors the execution of tasks by the vehicle and road ends in real time. The docking communication method is mainly http, and some are mqtt type interfaces.

[0035] Simulation test. The scene and vehicle model are built, and the connection with the cloud control platform is established to run the simulation test system. Single vehicle operation or vehicle group operation can be realized. At the same time, the vehicle, roadside and cloud control platform communicate with each other in real time to realize vehicle-road-cloud integration.

[0036] Analysis of simulation results. Based on the information received by the cloud control platform, the utilization rate of roadside information by vehicles, the overall operating status of vehicles, overall safety and other factors, the vehicle-road-cloud integration solution for special scenarios is analyzed.

[0037] The method of the present invention is also characterized in that it includes the following systems and modules: A scenario system that can import scenario-specific maps in standard formats, set static obstacles, import roadside modules into the scenario, and access dynamic traffic flows through interfaces. Includes: A map module that imports standard format maps into the scene to form a static map basis.

[0038] A roadside module that can configure the type, quantity and distribution of roadside equipment, and supports automatic and manual distribution.

[0039] A traffic flow module is connected to the dynamic traffic flow to achieve joint simulation with the traffic flow simulation software.

[0040] A vehicle system that can configure the parameters of the dynamic model and sensor model of the simulated vehicle to make it fit the real vehicle to the greatest extent possible. It can also be connected to the self-driving algorithm to enable the vehicle to drive automatically. It includes: A vehicle dynamics module makes the physical characteristics of the simulated vehicle close to those of the real vehicle by selecting the vehicle body and configuring the dynamic parameters.

[0041] A vehicle-side sensor module configures the specific performance, quantity and position of the vehicle-side camera, lidar, millimeter-wave radar, ultrasonic radar, inertial navigation combination, OBU, etc. to form a simulated intelligent driving hardware system.

[0042] A vehicle algorithm module connects the executable algorithm to the simulation system. When the simulation is running, the algorithm module continuously receives information from the cloud control module and the scene module, feeds it back to the intelligent driving algorithm, and controls the simulated vehicle to drive in the scene according to the instructions of the intelligent driving algorithm.

[0043] A cloud control system is mainly a communication interface + cloud control platform. In the simulation system, it can be connected to the complete city-level service management platform, and can also be connected to the parts related to the vehicle and roadside, such as the regional cloud-based cloud control platform.

[0044] An analysis system analyzes and evaluates the current solution from multiple dimensions based on the data generated during the overall operation of the simulation system, such as vehicle speed, acceleration, number and severity of traffic violations, roadside green wave efficiency, and the delay in the cloud control platform receiving data, and generates an evaluation report with charts.

[0045] Figure 1 is a flow chart of a solution verification method based on vehicle-road-cloud integrated system simulation according to an embodiment of the present invention, and the process includes the following steps: Step S101 is to import a basic map in a standard format into the simulation system and set static obstacles.

[0046] Step S102 is to set and edit the intelligent roadside facilities and import the simulation scene.

[0047] Step S103 is to import the dynamic traffic flow into the simulation system. In the embodiment of the present invention, the traffic flow is imported from the Simulation of Urban Mobility (SUMO) simulation software. In SUMO, the Network, Route and SUMO configuration file are configured based on the specific scenario road network. The configured traffic flow is connected to the vehicle-road-cloud integrated simulation system for joint simulation.

[0048] Step S201 is to build a vehicle dynamics model based on actual vehicle performance parameters, and configure the vehicle body, suspension system, steering system, braking system, power system, transmission system, etc.

[0049] Step S202 is to build a vehicle-side sensor model, configure the type, quantity, and location of the vehicle-side sensors, and adjust the parameters of the sensors.

[0050] Step 203 is to import the autonomous driving algorithm and connect the corresponding autonomous driving algorithm to the built vehicle model. The general autonomous driving algorithm is divided into perception, decision-making planning and control modules. One or more modules are imported according to the simulation focus. In the embodiment of the present invention, three modules are imported to verify the overall algorithm.

[0051] Step S300 is to connect with the cloud control platform and establish an effective communication method. In the embodiment of the present invention, the http communication method is adopted.

[0052] Step S400 is to conduct a simulation test. During the test, the roadside equipment continuously collects traffic information and publishes it to the cloud control platform and the intelligent connected vehicle. The intelligent connected vehicle receives the tasks and roadside information issued by the cloud control platform, and comprehensively adjusts the path planning and control decisions based on the information it perceives. At the same time, the intelligent connected vehicle continuously sends its own status information to the roadside facilities and the cloud control platform to ensure the controllable circulation of the overall information of the system.

[0053] Step S500, after a simulation test is completed, the simulation results are automatically analyzed according to the data in the process, the test results are evaluated from multiple dimensions, and the evaluation results are output.

[0054] An embodiment of the present invention proposes a solution verification method based on vehicle-road-cloud integrated system simulation. Figure 2 It is a structural block diagram of a vehicle-road-cloud integrated simulation system according to some embodiments of the present invention.

[0055] Scene system 1 is used to build dynamic and static scenes. It is the environment for simulating vehicle operation and the cornerstone of the simulation system. It includes: The map module 11 imports a standard format map into the scene through the map import interface 101 to form a static map basis.

[0056] The roadside module 12 configures RSU, camera, lidar, millimeter-wave radar, multi-access edge computing (MEC), etc. according to the solution requirements to form a roadside module as part of the scenario module.

[0057] The traffic flow module 13 is connected to the dynamic traffic flow through the traffic flow simulation software communication interface 102. In the embodiment of the present invention, the traffic flow simulation software SUMO is selected to run the collaborative script to realize the joint simulation.

[0058] Vehicle system 2 is used to build the intelligent connected vehicle model and is the core of the vehicle-road-cloud integrated system. It includes: The vehicle dynamics module 21 selects the vehicle body and configures the dynamic parameters so that the physical characteristics of the simulated vehicle are close to those of the real vehicle.

[0059] The vehicle-side sensor module 22 configures the specific performance, quantity and position of the vehicle-side camera, lidar, millimeter-wave radar, ultrasonic radar, inertial navigation combination, OBU, etc. to form a simulated intelligent driving hardware system.

[0060] The vehicle algorithm module 23 connects the executable algorithm to the simulation system through the intelligent driving algorithm communication interface 201. When the simulation is running, the algorithm module continuously receives information from the cloud control module and the scene module, feeds back to the intelligent driving algorithm, and controls the simulated vehicle to travel in the scene according to the intelligent driving algorithm instructions. In an embodiment of the present invention, the communication between the intelligent driving algorithm and the vehicle algorithm module in the simulation system is realized through ROS2.

[0061] The cloud control system 3 continuously uploads vehicle status information and roadside sensing information through the cloud control platform communication interface 301, and issues cloud commands, so that the entire system is organically integrated. In the embodiment of the present invention, http is used for communication.

[0062] Analysis system 4 records the scenario operation data, analyzes and evaluates the vehicle-road-cloud integration system from multiple dimensions based on the data, and provides an evaluation report.

[0063] Combine the following Figure 3 , that is, a schematic diagram of data flow of a solution verification method based on vehicle-road-cloud integrated system simulation according to some embodiments of the present invention, further illustrating the flow direction of data in the simulation software during the simulation operation.

[0064] Scenario system 1, mainly the roadside system, uploads real-time road conditions, traffic flow, accident information, etc. to the cloud control system, and uploads road congestion information, traffic light status, traffic time alarms, etc. to the vehicle system. At the same time, it uploads road condition data such as road slipperiness and visibility to help vehicles make smarter driving decisions; the scenario system obtains software updates, configuration changes and other instructions from the cloud control system, and may also obtain global traffic information. The scenario system obtains status information such as vehicle location from the vehicle side to achieve better vehicle-road collaboration.

[0065] Vehicle system 2 uploads basic vehicle status data, such as speed, acceleration, location information, as well as sensor data and safety time data, to the cloud control platform, and transmits basic vehicle status information to the scene system. If the vehicle detects an obstacle or traffic hazard ahead, it will also send a warning message to the roadside unit; the vehicle system obtains vehicle management instructions and global traffic information from the cloud control module, and obtains real-time road condition information from the scene system, such as traffic light status, road construction conditions, accident warnings, etc., as well as environmental perception information, so that the vehicle can achieve beyond-visual-range perception and eliminate blind spots.

[0066] The cloud control system 3 sends software update, configuration change and other instructions, as well as global traffic information to the scene system, and sends vehicle management instructions and global traffic information to the vehicle system; obtains basic vehicle status data such as speed, acceleration, location information, as well as sensor data and safety time data from the vehicle system, and obtains real-time road conditions, traffic flow, emergency accidents and other information from the scene system.

[0067] Analysis system 4 obtains data generated during the overall operation process from the scene system, vehicle system and cloud control system, such as vehicle speed, acceleration, number and severity of traffic violation, roadside green wave efficiency, time delay of cloud control platform receiving data, completion status of cloud control platform instructions and other information.

[0068] The present invention describes a solution verification method based on vehicle-road-cloud integrated system simulation. Intelligent connected vehicles, intelligent roadside facilities and cloud control platforms can be organically combined to jointly complete the simulation, which can realize the simulation verification of the large-scale construction and application of intelligent connected vehicles, vehicle-road-cloud integration.

[0069] The basic principles, main features and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above specific embodiments. The above specific embodiments and the description in the specification are only for further illustrating the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which should be included in the scope of the present invention to be protected. The scope of the present invention to be protected is defined by the claims and their equivalents.

[0070] Those skilled in the art can understand that all or part of the steps in the method for implementing the above-mentioned embodiments can be completed by instructing the relevant hardware through a program, and the program is stored in a storage medium, including several instructions for making a (may be a single-chip microcomputer, chip, etc.) or a processor execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0071] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A solution verification method based on vehicle-road-cloud integrated system simulation, characterized in that: The following steps are involved: Step 1: Import basic maps, edit road facilities and dynamic traffic flows, and generate specific simulation scenarios; Step 2: Build the vehicle dynamics model and vehicle-side sensor model, import the autonomous driving algorithm, and build the autonomous driving simulation vehicle; Step 3: Connect to the cloud control platform and establish communication through the cloud control platform; Step 4: Conduct simulation tests, collect traffic information and publish it to the cloud control platform and intelligent connected vehicles. The intelligent connected vehicles receive tasks and roadside information issued by the cloud control platform. Step 5: Simulation result analysis: evaluate the test results from multiple dimensions and output the evaluation results.

2. The solution verification method based on vehicle-road-cloud integrated system simulation according to claim 1 is characterized in that: The specific simulation scenario generation in step 1 includes basic map import, road facility editing and dynamic traffic flow import; Basic map import, import standard format map into the scene; Edit road facilities and arrange intelligent roadside equipment such as roadside units; Dynamic traffic flow import: import dynamic traffic flow from traffic flow simulation software and perform joint simulation.

3. The solution verification method based on vehicle-road-cloud integrated system simulation according to claim 2 is characterized in that: The autonomous driving simulation vehicle construction in step 2 includes vehicle model construction and vehicle algorithm import; Vehicle model construction, including the construction of vehicle dynamics model and vehicle-side sensor model; Vehicle algorithm import, connect the autonomous driving algorithm to the corresponding vehicle to enable it to have autonomous driving capabilities.

4. The solution verification method based on vehicle-road-cloud integrated system simulation according to claim 3 is characterized in that: The simulation test in step five runs the simulation system to test and verify the efficiency of the overall vehicle-road-cloud integration solution.

5. The solution verification method based on vehicle-road-cloud integrated system simulation according to claim 4 comprises a system and a module, characterized in that: The simulation result analysis in step five includes analyzing the evaluation output, and performing the analysis based on the data of the simulation test process.

6. The solution verification method based on vehicle-road-cloud integrated system simulation according to claims 1-5 comprises a system and a module, characterized in that: Includes the following systems and modules: A scenario system that imports scenario-specific maps in a standard format, sets static obstacles, imports roadside modules into the scenario, and accesses dynamic traffic flows through interfaces; A vehicle system that configures the parameters of the dynamic model and sensor model of the simulated vehicle to make it fit the real vehicle to the greatest extent possible, and connects to the algorithm module to enable the vehicle to drive automatically; A cloud control system, communication interface + cloud control platform, which can access the complete city-level service management platform in the simulation system, and can also access the parts related to the vehicle side and road side; An analysis system analyzes and evaluates the current solution from multiple dimensions based on the data generated during the overall operation of the simulation system, and generates an evaluation report with charts.

7. The solution verification method based on vehicle-road-cloud integrated system simulation according to claim 6 is characterized in that: The scene system also includes: A map module that imports standard format maps into the scene to form a static map basis; A roadside module to configure the type, quantity and distribution of roadside equipment; A traffic flow module is connected to the dynamic traffic flow to achieve joint simulation with the traffic flow simulation software.

8. The solution verification method based on vehicle-road-cloud integrated system simulation according to claim 7 is characterized in that: The vehicle system further includes: A vehicle dynamics module, which makes the physical characteristics of the simulated vehicle close to the real vehicle by selecting the vehicle body and configuring the dynamic parameters; A vehicle-side sensor module that configures the performance, quantity, and location of vehicle-side sensors to form a simulated intelligent driving hardware system; A vehicle algorithm module that connects the autonomous driving algorithm to the simulation system.

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