Concurrent simulation test method for IVCPS vehicle-mounted terminal

Abstract

The invention belongs to the field of Internet of Vehicles, and discloses an IVCPS vehicle-mounted terminal concurrent simulation test method, which comprises the following steps: S1, carrying out simulation construction on a traffic environment by using software, and constructing a vehicle end module, a cloud end module, a roadside facility module and a vehicle end information processing module according to an IVCPS scene; s2, based on a TCP / IP (Transmission Control Protocol / Internet Protocol) or UDP / IP (User Delivery Protocol / Internet Protocol) communication protocol, constructing communication modules between vehicles and roads, vehicle cloud and vehicles, and finishing information transmission and interaction between the vehicle and road cloud modules in a real local area network environment; s3, building a vehicle end performance monitoring module; and S4, establishing a vehicle end communication performance monitoring module. According to the method, the simulation environment can be flexibly adjusted, efficient interaction of information is realized, and the method can be used for monitoring the performance bottleneck in a concurrent scene.

Description

Technical Field

[0001] The present invention belongs to the field of Internet of Vehicles, and in particular relates to an IVCPS vehicle-mounted terminal concurrent simulation test method. Background Art

[0002] IVCPS (Intelligent Vehicle Cyber-Physical Systems) is a large system consisting of cyberspace and physical space components in the vehicle-road cloud. Due to the multi-agent characteristics of the system, there is a frequent need for information interaction between different agents. Due to the limited system resources of IVCPS, when different tasks initiate requests to the system at the same time, the system processing capacity will decrease.

[0003] At present, traditional traffic simulation systems have certain limitations, such as difficulty in flexibly adjusting the simulation environment, lack of diversified sensor simulation functions, etc. The patent of this invention mainly provides a concurrent performance bottleneck test method for the vehicle system in IVCPS facing V2V, V2C, V2I and other scenarios. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide an IVCPS vehicle terminal concurrent simulation test method. The present invention aims to solve the problems of certain limitations of traditional traffic simulation systems, difficulty in flexibly adjusting the simulation environment, lack of diversified sensor simulation functions, etc.

[0005] The present invention provides an IVCPS vehicle-mounted terminal concurrent simulation test method, comprising the following steps:

[0006] S1. Use software to simulate the traffic environment and build the vehicle-side module, cloud module, roadside facility module and vehicle-side information processing module according to the IVCPS scenario;

[0007] S2. Based on TCP / IP or UDP / IP communication protocol, build vehicle-road, vehicle-cloud, and vehicle-to-vehicle communication modules to complete information transmission and interaction between vehicle-road-cloud modules in a real local area network environment;

[0008] S3. Build vehicle-side performance monitoring module;

[0009] S4. Build a vehicle-side communication performance monitoring module.

[0010] Further, the step S1 includes the following sub-steps:

[0011] S1.1 uses PreScan to create a simulation environment that meets actual road conditions;

[0012] The simulation environment includes urban roads, highways, intersections and tunnels;

[0013] S1.2 configure different types of vehicle models and pedestrian models, and install sensor modules for each vehicle;

[0014] The sensor module is used to simulate real perception capabilities, and the sensor module is one or more of a camera, a laser radar, and a millimeter-wave radar;

[0015] S1.3 Set the dynamic behavior parameters of the vehicle and combine traffic lights and road signs to simulate actual traffic flow and traffic rules;

[0016] The dynamic behavior parameters of the vehicle include speed, acceleration and braking distance;

[0017] S1.4 Build vehicle-side module, cloud module, roadside facility module and vehicle-side information processing module;

[0018] Vehicle-side module: collects environmental information around the vehicle and the vehicle's own status information through a sensor module installed on the vehicle. The vehicle-side module is connected to the cloud module and the roadside facility module through a communication module;

[0019] Cloud module: The cloud here can be edge cloud, regional cloud, or central cloud, which performs calculations and decisions by receiving data information from multiple vehicle-side modules and roadside facility modules;

[0020] The cloud module can optimize the global traffic light scheduling strategy based on the received traffic flow information, or provide the vehicle-side module with optimal path planning, vehicle speed guidance calculation, etc. based on the real-time road conditions. The processing results are sent back to the vehicle-side module and the roadside facility module through the cloud module to guide the vehicle's driving behavior and the control strategy of the roadside facilities.

[0021] Roadside facility module: monitors the road environment in real time, collects traffic flow and pedestrian dynamic information, and broadcasts traffic prompt information to the vehicle-side module through the RSU;

[0022] Vehicle-side information processing module: real-time reception and concurrent processing of cloud-side, vehicle-side, road-side and vehicle-side perception data;

[0023] The vehicle-side information processing module includes a vehicle-side message arrangement module, a resource balancing allocation module, and a concurrent scheduling module (such as Figure 2As shown). The vehicle-side message arrangement module is responsible for receiving and integrating data from multiple information sources, including traffic instructions from the cloud, driving status data of adjacent vehicles, and real-time perception data from the vehicle's sensors. By setting information priority and timestamps, the vehicle-side message arrangement module can sort information according to predetermined rules to ensure that key data enters the processing queue first, thereby reducing the risk of information delay and data loss. The resource balancing allocation module is used to reasonably allocate computing resources and bandwidth in a concurrent processing environment to avoid processing bottlenecks. This module dynamically monitors the load of each processing unit and adjusts the resource allocation strategy in real time to ensure the overall stability of the system and effectively avoid overload caused by uneven resource allocation. The concurrent scheduling module uses an intelligent scheduling algorithm to automatically allocate processing tasks to different computing threads or processor cores when the system load reaches a certain threshold. This module ensures coordination and synchronization between multi-threaded tasks, avoids resource contention and data conflicts, and improves overall processing efficiency.

[0024] In addition, the roadside facility module works in collaboration with the cloud module to adjust the control strategy of traffic lights based on the optimization plan fed back by the cloud module to ensure smooth and safe road traffic.

[0025] Further, the step S2 includes the following sub-steps:

[0026] S2.1 Build a communication module based on TCP / IP or UDP / IP communication protocol in Simulink, and configure the network communication parameters of the vehicle-side module, cloud module, and roadside facility module;

[0027] S2.2 message sending;

[0028] In the vehicle terminal module, the data information collected by the vehicle is integrated and compressed through the communication module and sent to the cloud module;

[0029] S2.3 message arrangement and distribution;

[0030] In the process of message arrangement and distribution, the cloud module can not only integrate and process the received vehicle status information according to the priority and data type, but also perform protocol conversion and format conversion on the information. After the processing is completed, the cloud module sends the result to the vehicle;

[0031] S2.4 message processing;

[0032] The main vehicle receives sensor data from the cloud, road side, other vehicles and the vehicle's own sensors in real time through the communication module, and then completes the concurrent processing of messages through the vehicle-side information processing module.

[0033] Furthermore, in step S1.4, the information collected by the vehicle-side module includes vehicle speed, acceleration, vehicle position and road conditions ahead.

[0034] Furthermore, in step S1.4, the traffic prompt information broadcast by the roadside facility module includes congestion ahead, accident warning and speed limit reminder.

[0035] Furthermore, in step S1.4, the vehicle-side message arrangement module is responsible for receiving and integrating data from multiple information sources, including traffic instructions from the cloud, driving status data of adjacent vehicles, and real-time perception data from the vehicle's sensors. By setting information priority and timestamps, the message arrangement module can sort the information according to predetermined rules to ensure that key data enters the processing queue first, thereby reducing the risk of information delay and data loss.

[0036] The resource balancing module rationally allocates computing resources and bandwidth in a concurrent processing environment to avoid processing bottlenecks. The module dynamically monitors the load of each processing unit and adjusts the resource allocation strategy in real time to ensure the overall stability of the system and effectively avoid overload caused by uneven resource allocation.

[0037] The concurrent scheduling module uses an intelligent scheduling algorithm to automatically distribute processing tasks to different computing threads or processor cores when the system load reaches a certain threshold. This module ensures coordination and synchronization between multi-threaded tasks, avoiding resource competition and data conflicts, thereby improving overall processing efficiency.

[0038] Furthermore, in step S2.3, the cloud module also includes a self-organizing network module for managing the dynamic communication of the vehicle. When a vehicle drives out, the self-organizing network module will recycle the corresponding communication port; when a vehicle drives in, the self-organizing network module will assign a unique port number to the vehicle, thereby ensuring smooth and efficient communication between the vehicle and other vehicles, roadside facilities and the cloud.

[0039] Furthermore, the main vehicle in step S2.4 refers to the vehicle that receives and processes the sensor data from the cloud, the road end, other vehicles and the vehicle itself, and other vehicles in the local area network can be considered as side vehicles.

[0040] Furthermore, the specific steps of step S3 to build the vehicle-side performance monitoring module are:

[0041] First, configure JMeter to access the IP addresses of the vehicle and the cloud. By setting JMeter's HTTP request sampler or TCP / UDP request sampler, specify the IP address and the corresponding port number to send network requests to the vehicle and the cloud. Through JMeter's performance monitoring plug-in, real-time performance data of the vehicle and the cloud is collected, including CPU usage, memory usage, and network throughput, to monitor the bottleneck of system performance under high load conditions.

[0042] Furthermore, the specific steps of step S4 to build a vehicle-side communication performance monitoring module are:

[0043] Wireshark is deployed in the local area network environment where the IVCPS system is located. By configuring the monitoring interface, all inbound and outbound network traffic of the main vehicle is captured. By setting filters, TCP / IP or UDP / IP data packets between the main vehicle and the side vehicle are specifically captured to analyze the data transmission delay, packet loss rate and retransmission times, thereby providing accurate network traffic information and protocol analysis results.

[0044] Beneficial effects:

[0045] The present invention proposes a concurrent simulation test method for an IVCPS vehicle-mounted terminal, which can flexibly adjust the simulation environment. According to the IVCPS scenario, the present invention builds a vehicle-side module, a cloud module, a roadside facility module, and a vehicle-side information processing module. Each module can receive and send information to each other to achieve efficient information interaction. At the same time, communication modules between vehicles and roads, vehicles and clouds, and vehicles are constructed, and the information transmission and interaction between vehicle-road-cloud modules are completed in a real local area network environment using TCP / IP or UDP / IP communication protocols. In addition, vehicle-side performance monitoring and communication performance monitoring modules are also built, which can be used to monitor performance bottlenecks in concurrent scenarios.

[0046] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A schematic diagram of a concurrent simulation test of an IVCPS vehicle-mounted terminal of the present invention;

[0048] Figure 2 This is the architecture diagram of the vehicle-side information processing module;

[0049] Figure 3 This is a data transmission link diagram of the vehicle-mounted terminal concurrent simulation test in Example 1;

[0050] Figure 4 This is the overall architecture diagram of the vehicle terminal concurrent simulation test in Example 1;

[0051] Figure 5 This is a schematic diagram of a cross intersection scene;

[0052] Figure 6 It is the main vehicle communication receiving module;

[0053] Figure 7The main vehicle receives the speed information graph of the adjacent vehicle;

[0054] Figure 8 To monitor the performance of the main vehicle under different numbers of concurrent vehicles. DETAILED DESCRIPTION

[0055] In order to make the technical solutions, advantages and purposes of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the protection scope of this application.

[0056] like Figure 1 As shown, the present invention provides an IVCPS vehicle-mounted terminal concurrent simulation test method, comprising the following steps:

[0057] S1. Use software to simulate the traffic environment. According to the IVCPS scenario, build the vehicle-side module, cloud module, roadside facility module and vehicle-side information processing module. Each module can receive and send information to each other to achieve efficient information interaction;

[0058] S1.1 uses PreScan to create a simulation environment that meets actual road conditions, including complex scenes such as urban roads, highways, intersections, and tunnels;

[0059] S1.2 configure different types of vehicle models and pedestrian models, and install sensor modules for each vehicle;

[0060] The sensor module is used to simulate real perception capabilities. The sensor module is one or more of a camera, a laser radar, and a millimeter-wave radar;

[0061] S1.3 During the construction process, set the dynamic behavior parameters of the vehicle and combine roadside facility modules such as traffic lights and road signs to simulate actual traffic flow and traffic rules;

[0062] The dynamic behavior parameters of the vehicle include speed, acceleration, and braking distance;

[0063] S1.4 Build vehicle-side module, cloud module, roadside facility module and vehicle-side information processing module;

[0064] Vehicle-side module: collects environmental information around the vehicle and the vehicle's own status information through sensors installed on the vehicle. This information includes but is not limited to vehicle speed, acceleration, vehicle position, and road conditions ahead. After preliminary processing and packaging, the collected data is sent to the cloud module and roadside facility module through the communication module. In addition, the vehicle-side module also has powerful concurrent processing capabilities, and can decode, arrange, evenly distribute and process multi-source data in real time, ensuring that the vehicle can quickly make driving control decisions when receiving information from the cloud, roadside facilities, real-time perception of the vehicle, and neighboring vehicles.

[0065] Specifically, the concurrent message processing function in the vehicle-side module integrates and sorts messages from different information sources according to the importance and timestamp of the data, giving priority to key data. The balanced allocation function ensures the rational use of computing resources and bandwidth to avoid system overload. The concurrent scheduling function dynamically allocates processing tasks to multiple threads or multiple processor cores through an intelligent scheduling algorithm, thereby improving the response speed and processing efficiency of the overall system.

[0066] Through the synergistic effect of the above functions, the vehicle-side module can realize efficient processing of multi-source information in complex traffic environments, significantly improving the vehicle's intelligent decision-making capabilities and driving safety.

[0067] Cloud module: performs calculations and decisions by receiving data information from multiple vehicle-side modules and roadside facility modules.

[0068] The cloud module can optimize the global traffic light scheduling strategy based on the received traffic flow information, or provide the optimal path planning for the vehicle-side module based on the real-time road conditions. The processing results are sent back to the vehicle-side module and the roadside facility module through the cloud module to guide the vehicle's driving behavior and the control strategy of the roadside facilities.

[0069] Roadside facility module: monitors the road environment in real time, collects traffic flow and pedestrian dynamic information, and broadcasts traffic prompt information to the vehicle-side module through RSU, such as congestion ahead, accident warning, speed limit reminder, etc.

[0070] Vehicle-side information processing module: real-time reception and concurrent processing of cloud-side, vehicle-side, road-side and vehicle-side perception data.

[0071] The vehicle-side information processing module includes a vehicle-side message arrangement module, a resource balancing allocation module, and a concurrent scheduling module (such as Figure 2As shown). The vehicle-side message arrangement module is responsible for receiving and integrating data from multiple information sources, including traffic instructions from the cloud, driving status data of adjacent vehicles, and real-time perception data from the vehicle's sensors. By setting information priority and timestamps, the vehicle-side message arrangement module can sort information according to predetermined rules to ensure that key data enters the processing queue first, thereby reducing the risk of information delay and data loss; the resource balancing allocation module is used to reasonably allocate computing resources and bandwidth in a concurrent processing environment to avoid processing bottlenecks. This module dynamically monitors the load of each processing unit and adjusts the resource allocation strategy in real time to ensure the overall stability of the system and effectively avoid overload caused by uneven resource allocation. The concurrent scheduling module uses an intelligent scheduling algorithm to automatically allocate processing tasks to different computing threads or processor cores when the system load reaches a certain threshold. This module ensures coordination and synchronization between multi-threaded tasks, avoids resource contention and data conflicts, and improves overall processing efficiency.

[0072] In addition, the roadside facility module works in collaboration with the cloud module to adjust the control strategy of traffic lights based on the optimization plan fed back by the cloud module to ensure smooth and safe road traffic.

[0073] S2. Based on TCP / IP or UDP / IP communication protocol, build vehicle-road, vehicle-cloud, and vehicle-to-vehicle communication modules to complete information transmission and interaction between vehicle-road-cloud modules in a real local area network environment;

[0074] S2.1 Build a communication module based on TCP / IP or UDP / IP communication protocol in Simulink, configure the network communication parameters of the vehicle-side module, cloud module and roadside facility module, and assign a unique IP address and port number to each module to ensure that each module can communicate effectively within the local area network;

[0075] S2.2 message sending and processing;

[0076] In the vehicle terminal module, communication modules of various sensors are configured to integrate and compress the data information collected by the cloud, roadside, and the vehicle and adjacent vehicles, and receive them through the communication receiving module. Subsequently, these data will enter the message distribution module and be distributed to the corresponding data processing module according to the priority and data type. The data processing module parses and processes the received information, and then sends the processed information to the main vehicle module or other vehicles through the message sending module through the TCP / IP or UDP / IP protocol to ensure efficient processing and transmission of multi-source information in concurrent scenarios. In the cloud module, after the received data is processed, the optimized control instructions and information packets can be sent to the main vehicle module through the same communication module. The cloud module also includes a self-organizing network module for managing the dynamic communication of the vehicle. When the vehicle leaves, the self-organizing network module will recycle the corresponding communication port; when a vehicle enters, the module will assign it a unique port number, thereby ensuring smooth and efficient communication between the vehicle and other vehicles, roadside facilities and the cloud.

[0077] S3. Build vehicle-side and cloud-side performance monitoring modules;

[0078] The performance monitoring module uses Jmeter to access the IP of the main vehicle and collect the performance data of the main vehicle. First, you need to configure JMeter to access the IP addresses of the vehicle and the cloud. By setting JMeter's HTTP request sampler (or TCP / UDP request sampler), specify the IP addresses and corresponding port numbers of the vehicle and the cloud, so as to send network requests. Through JMeter's performance monitoring plug-in, you can collect the performance data of the main vehicle and the cloud in real time, including key indicators such as CPU usage, memory usage, and network throughput, and monitor the bottleneck of system performance under high load. For example, when the side car, cloud, and road send information to the main vehicle at the same time, you can monitor the consumption of the main vehicle's CPU or memory resources and the changes in throughput to identify the potential performance bottlenecks of the main vehicle's on-board system for subsequent optimization.

[0079] S4. Build a communication performance monitoring module;

[0080] The communication performance monitoring module deploys Wireshark in the local area network environment where the IVCPS system is located. By configuring the monitoring interface, all inbound and outbound network traffic of the main vehicle is captured. By setting filters, TCP / IP or UDP / IP data packets between the main vehicle and the side vehicle and the cloud are captured specifically to analyze key network performance indicators such as data transmission delay, packet loss rate, and number of retransmissions. By performing detailed monitoring and analysis of the communication between the main vehicle and the side vehicle and the cloud, Wireshark can provide accurate network traffic information and protocol analysis results. For example, when a large number of vehicles, roadside facilities, and cloud devices communicate at the same time, network congestion may occur, thereby increasing delays and packet loss rates. By capturing and analyzing the data streams in these concurrent scenarios with Wireshark, it is possible to detect an increase in the number of retransmissions due to network congestion, or a decrease in the efficiency of specific protocols under high concurrency. These bottleneck information can be used to further optimize the communication protocol and network configuration to improve the overall performance and reliability of the system under high concurrency conditions.

[0081] Example 1

[0082] In this example, an IVCPS urban intersection scenario is built to simulate the communication and control process between the main vehicle and ten adjacent vehicles when approaching or entering the intersection. The data transmission link diagram is shown in the figure below. Figure 3 As shown in the figure, the message sending, message monitoring, message arrangement and distribution, and message processing functions of the vehicle system are highlighted. The overall architecture diagram is shown in Figure 4 shown.

[0083] The following are the key elements of each step:

[0084] Step 1: Traffic scene construction

[0085] Use PreScan to build a two-way four-lane traffic scene, where each lane is 3.5 meters wide, the intersection length is 100 meters, and the maximum speed is 50 km / h. This scene is used to simulate the traffic behavior of the main vehicle and ten side vehicles at a crossroad, such as Figure 5 shown.

[0086] Step 2: Set up the main vehicle and the side vehicle

[0087] Configure the initial velocity, final velocity and acceleration of the main vehicle and the side vehicle (see Table 1 for details), and set up relevant intelligent sensors for each vehicle. These sensors are used to collect real-time status information such as vehicle speed, position, and driving direction.

[0088] Table 1 Vehicle speed parameters

[0089]

[0090] Step 3: Main vehicle, side vehicle and cloud configuration

[0091] In Simulink, communication modules based on UDP / IP protocol are set up for the main vehicle, the side vehicle and the cloud, and a fixed IP address and port number are assigned to each module to ensure stable communication between the vehicle and the cloud.

[0092] Main vehicle: IP address: 192.168.1.2, sending port: 5001, receiving port: 6001

[0093] Sidecar 1: IP address: 192.168.1.3, Sending port: 5002, Receiving port: 6002

[0094] Sidecar 2: IP address: 192.168.1.4, Sending port: 5003, Receiving port: 6003 ...

[0096] Cloud: IP address: 192.168.1.100, Sending port: 7000, Receiving port: 8000

[0097] Message sending: The adjacent car sends the real-time collected vehicle status information (such as speed, location, etc.) to the cloud through the configured communication module.

[0098] Message arrangement and distribution: During the message arrangement and distribution process, the cloud not only integrates and processes the received vehicle status information, but also performs protocol conversion and format conversion on the information. After processing, the cloud sends the results to the host vehicle in parallel to ensure that the host vehicle can receive this information in a unified format and protocol to support subsequent control decisions.

[0099] Message processing: The communication module of the main vehicle (such as Figure 6 The main vehicle is responsible for receiving and arranging information from the cloud. To ensure that the main vehicle can accurately receive and process information from the cloud and the side vehicles during high-speed movement, the system sets the sampling interval to 0.05 seconds and the simulation step to 0.5 seconds. With this configuration, the main vehicle can ensure high temporal resolution of data and reduce delays and errors in complex dynamic traffic environments.

[0100] After receiving the information, the message processing module of the host vehicle (such as Figure 2 The module has powerful concurrent processing capabilities and can arrange messages from the cloud and sidecars according to the importance and timestamp of the data, giving priority to key data. Then, the balanced allocation function is used to reasonably allocate computing resources to avoid system overload and ensure processing efficiency. Through the intelligent concurrent scheduling algorithm, the communication module dynamically allocates processing tasks to multiple threads or multiple processor cores, thereby further improving the system's response speed and processing capabilities.

[0101] During the simulation, the host vehicle can display the received speed information of the adjacent vehicle in real time (such as Figure 7 This process verifies the processing performance of the main vehicle communication module under high concurrency conditions, ensuring that the main vehicle can quickly make accurate driving control decisions after receiving multi-source information.

[0102] Step 4: JMeter Performance Monitoring

[0103] Use JMeter to monitor the system performance of the main vehicle: configure JMeter to sample requests to the IP address of the main vehicle to monitor the performance of the vehicle-mounted system. First, configure the HTTP request sampler or TCP / UDP request sampler in JMeter to specify the IP address and corresponding port number of the main vehicle to send network requests to the main vehicle. The specific steps include adding a sampler to the test plan and setting the IP address and port number of the main vehicle in the sampler. With these configurations, JMeter can send network requests and communicate with the main vehicle. Next, with the help of JMeter's performance monitoring plug-in, key performance data of the main vehicle is collected in real time, such as CPU utilization, memory usage, network throughput, etc. During the actual test process, you can monitor and record changes in performance indicators in different scenarios, such as Figure 8 As shown in the figure, the CPU, memory, and throughput change trends of the main vehicle under different numbers of concurrent vehicles are very important for evaluating the operating performance of the main vehicle under various load conditions and can provide a basis for system optimization.

[0104] Step 5: Wireshark communication monitoring

[0105] Use Wireshark to monitor the network traffic of the main vehicle:

[0106] Message monitoring and filtering: Capture specific communication data packets between the main vehicle and the side vehicle by configuring the monitoring interface and filter.

[0107] Message analysis: Analyze these data packets and evaluate the system's network performance indicators, including transmission delay, packet loss rate, and number of retransmissions. When five side vehicles send data to the main vehicle at the same time, the monitoring results of Wireshark show that the packet loss rate is 0%, indicating that in this concurrent situation, the main vehicle can stably receive all communication data packets from the side vehicles without any data loss, and the network communication performance is good. However, when the number of concurrent vehicles increases to ten, the analysis results of Wireshark show that the packet loss rate rises to 0.46%. This means that as the number of concurrent vehicles increases, the communication between the main vehicle and the side vehicles begins to be affected by the network bandwidth or other factors, resulting in slight packet loss. Although the packet loss rate is low, this result shows that the communication stability of the system is reduced under high concurrency conditions.

[0108] It is hereby declared that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions, which should be included in the scope of the claims of the present invention.

Claims

1. A concurrent simulation test method for an IVCPS vehicle-mounted terminal, characterized in that: The following steps are involved: S1. Use software to simulate the traffic environment and build the vehicle-side module, cloud module, roadside facility module and vehicle-side information processing module according to the IVCPS scenario; S2. Based on TCP / IP or UDP / IP communication protocol, build vehicle-road, vehicle-cloud, and vehicle-to-vehicle communication modules to complete information transmission and interaction between vehicle-road-cloud modules in a real local area network environment; S3. Build vehicle-side performance monitoring module; S4. Build a vehicle-side communication performance monitoring module.

2. According to claim 1, a concurrent simulation test method for an IVCPS vehicle terminal is characterized in that: The step S1 comprises the following sub-steps: S1.1 uses PreScan to create a simulation environment that meets actual road conditions; The simulation environment includes urban roads, highways, intersections and tunnels; S1.2 configure different types of vehicle models and pedestrian models, and install sensor modules for each vehicle; The sensor module is used to simulate real perception capabilities, and the sensor module is one or more of a camera, a laser radar, and a millimeter-wave radar; S1.3 Set the dynamic behavior parameters of the vehicle and combine traffic lights and road signs to simulate actual traffic flow and traffic rules; The dynamic behavior parameters of the vehicle include speed, acceleration and braking distance; S1.4 Build vehicle-side module, cloud module, roadside facility module and vehicle-side information processing module; Vehicle-side module: collects environmental information around the vehicle and the vehicle's own status information through a sensor module installed on the vehicle. The vehicle-side module is connected to the cloud module and the roadside facility module through a communication module; Cloud module: Receives data from multiple vehicle-side modules and roadside facility modules to make calculations and decisions; The cloud module can optimize the global traffic light scheduling strategy based on the received traffic flow information, or provide the vehicle-side module with the optimal path planning based on the real-time road conditions. The processing results are sent back to the vehicle-side module and the roadside facility module through the cloud module to guide the vehicle's driving behavior and the control strategy of the roadside facilities. Roadside facility module: monitors the road environment in real time, collects traffic flow and pedestrian dynamic information, and broadcasts traffic prompt information to the vehicle-side module through the RSU; Vehicle-side information processing module: real-time reception and concurrent processing of cloud-side, vehicle-side, road-side and vehicle-side perception data; In addition, the roadside facility module works in collaboration with the cloud module to adjust the control strategy of traffic lights based on the optimization plan fed back by the cloud module to ensure smooth and safe road traffic.

3. The IVCPS vehicle-mounted terminal concurrent simulation test method according to claim 2 is characterized in that: The step S2 comprises the following sub-steps: S2.1 Build a communication module based on TCP / IP or UDP / IP communication protocol in Simulink, and configure the network communication parameters of the vehicle-side module, cloud module, and roadside facility module; S2.2 message sending; In the vehicle terminal module, the side cars equipped with various sensors integrate and compress the data information collected by multiple side cars through the communication module and send it to the cloud module; S2.3 message arrangement and distribution; In the process of message arrangement and distribution, the cloud module can not only integrate and process the received vehicle status information according to the priority and data type, but also perform protocol conversion and format conversion on the information. After the processing is completed, the results are sent to the vehicle end; S2.4 message processing; The vehicle receives sensor data from the cloud, road, other vehicles and the vehicle's own sensors in real time through the communication module, and then completes the concurrent processing of messages through the vehicle-side information processing module.

4. The IVCPS vehicle-mounted terminal concurrent simulation test method according to claim 3 is characterized in that: In step S1.4, the information collected by the vehicle-side module includes vehicle speed, acceleration, vehicle position and road conditions ahead.

5. The IVCPS vehicle-mounted terminal concurrent simulation test method according to claim 4 is characterized in that: In step S1.4, the traffic prompt information broadcast by the roadside facility module includes congestion ahead, accident warning and speed limit reminder.

6. The IVCPS vehicle-mounted terminal concurrent simulation test method according to claim 5 is characterized in that: In step S2.3, the cloud module also includes a self-organizing network module for managing the dynamic communication of the vehicle. When a vehicle drives out, the self-organizing network module will recycle the corresponding communication port; when a vehicle drives in, the self-organizing network module will assign a unique port number to the vehicle, thereby ensuring smooth and efficient communication between the vehicle and other vehicles, roadside facilities and the cloud.

7. The IVCPS vehicle-mounted terminal concurrent simulation test method according to claim 6 is characterized in that: The specific steps of step S3 to build the vehicle-side performance monitoring module are: First, configure JMeter to access the IP address of the main vehicle. By setting JMeter's HTTP request sampler or TCP / UDP request sampler, specify the IP address and corresponding port number of the main vehicle to send network requests to the main vehicle. Through JMeter's performance monitoring plug-in, the performance data of the main vehicle is collected in real time, including CPU usage, memory usage, and network throughput, so as to monitor the bottleneck of system performance under high load conditions.

8. The IVCPS vehicle-mounted terminal concurrent simulation test method according to claim 7 is characterized in that: The specific steps of step S4 to build the vehicle-side communication performance monitoring module are: Deploy Wireshark in the local area network environment where the IVCPS system is located. By configuring the monitoring interface, all inbound and outbound network traffic of the main vehicle can be captured. By setting filters, TCP / IP or UDP / IP data packets between the main vehicle, side vehicles, road terminals and the cloud can be specifically captured to analyze the data transmission delay, packet loss rate and retransmission times, thereby providing accurate network traffic information and protocol analysis results.

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