An IVCPS vehicle terminal concurrent simulation test method

Abstract

The application 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. using software to simulate and build a traffic environment, and according to an IVCPS scene, building a vehicle terminal module, a cloud module, a roadside facility module and a vehicle terminal information processing module; S2. based on a TCP / IP or UDP / IP communication protocol, constructing a communication module between a vehicle, a road and a cloud, and completing information transmission and interaction between the vehicle-road-cloud modules in a real local area network environment; S3. building a vehicle terminal performance monitoring module; and S4. building a vehicle terminal communication performance monitoring module. The application can flexibly adjust a simulation environment, realize efficient information interaction, and can be used for monitoring performance bottlenecks in a concurrent scene.

Description

Technical Field

[0001] This invention belongs to the field of vehicle networking, specifically relating to an IVCPS vehicle terminal concurrent simulation test method. Background Technology

[0002] IVCPS (Intelligent Vehicle Cyber-Physical Systems) is a large system composed of information space and physical space components in the vehicle-road-cloud framework. Due to the multi-agent nature of the system, there are frequent information interaction needs between different agents. Because IVCPS has limited system resources, when different tasks simultaneously send requests to the system, it will lead to a decrease in system processing capacity.

[0003] Currently, traditional traffic simulation systems have certain limitations, such as difficulty in flexibly adjusting the simulation environment and a lack of diverse sensor simulation functions. This invention patent mainly provides a method for testing the concurrent performance bottlenecks of onboard systems in IVCPS under V2V, V2C, and V2I scenarios. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a concurrent simulation testing method for IVCPS vehicle-mounted terminals. This invention aims to address the limitations of traditional traffic simulation systems, such as the difficulty in flexibly adjusting the simulation environment and the lack of diverse sensor simulation functions.

[0005] This invention provides a concurrent simulation testing method for an IVCPS vehicle terminal, comprising the following steps:

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

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

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

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

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

[0011] S1.1 Use PreScan to create a simulation environment that matches 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, lidar, and millimeter-wave radar.

[0015] S1.3 sets the dynamic behavior parameters of the vehicle and combines them with traffic lights and road signs to simulate actual traffic flow and traffic rules;

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

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

[0018] Vehicle-side module: The 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 communicates with 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 makes decisions by receiving data 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 module with optimal route planning and speed guidance calculation based on real-time road conditions. The processing results are sent back to the vehicle module and roadside facility module through the cloud module to guide the vehicle's driving behavior and the control strategy of the roadside facility.

[0021] Roadside facility module: Real-time monitoring of the road environment, collection of traffic flow and pedestrian dynamic information, and broadcasting traffic information to the vehicle-side module via RSU;

[0022] Vehicle-side information processing module: receives and processes cloud-based, vehicle-side, and roadside data as well as the vehicle's own sensing data in real time;

[0023] The vehicle-side information processing module includes a vehicle-side message orchestration module, a resource balancing allocation module, and a concurrent scheduling module (such as...). Figure 2(As shown). The vehicle-side message orchestration module is responsible for receiving and integrating data from multiple information sources, including traffic instructions from the cloud, driving status data from neighboring vehicles, and real-time perception data from the vehicle's own sensors. By setting information priorities and timestamps, the vehicle-side message orchestration module can sort information according to predetermined rules, ensuring that critical data enters the processing queue first, thereby reducing the risk of information delays and data loss. The resource balancing allocation module is used to rationally 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, thereby ensuring the overall performance stability of the system and effectively avoiding overload caused by uneven resource allocation. The concurrent scheduling module adopts an intelligent scheduling algorithm. When the system load reaches a certain threshold, it automatically allocates processing tasks to different computing threads or processor cores. 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 and the cloud module work together to adjust the control strategy of traffic lights based on the optimization schemes fed back by the cloud module, so as to ensure smooth and safe road traffic.

[0025] Furthermore, 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 module, cloud module and roadside facility module;

[0027] S2.2 Message sending;

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

[0029] S2.3 Message Orchestration and Distribution;

[0030] During message orchestration and distribution, the cloud module can not only integrate and process the received vehicle status information according to priority and data type, but also perform protocol conversion and format conversion on the information. After processing, the cloud module sends the results to the vehicle.

[0031] S2.4 Message Processing;

[0032] The main vehicle receives real-time sensor data from the cloud, roadside, other vehicles, and its own sensors via the communication module, and then performs concurrent processing of the 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 information broadcast by the roadside facility module includes traffic congestion ahead, accident warnings, and speed limit reminders.

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

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

[0037] The concurrent scheduling module employs an intelligent scheduling algorithm that automatically distributes processing tasks across 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 contention 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 vehicles. When a vehicle leaves, the self-organizing network module will reclaim the corresponding communication port; when a vehicle enters, 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, in step S2.4, the "master vehicle" refers to the vehicle that receives and processes sensor data from the cloud, the roadside, other vehicles, and the vehicle itself. Other vehicles within the local area network can be considered as "side vehicles."

[0040] Furthermore, the specific steps for building the vehicle-side performance monitoring module in step S3 are as follows:

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

[0042] Furthermore, the specific steps for building the vehicle-side communication performance monitoring module in step S4 are as follows:

[0043] Deploy Wireshark in the local area network environment where the IVCPS system is located, and capture all network traffic entering and leaving the master vehicle by configuring the listening interface. By setting filters, specifically capture TCP / IP or UDP / IP packets between the master vehicle and the neighboring vehicles, and analyze the data transmission latency, packet loss rate and retransmission count, thereby providing accurate network traffic information and protocol analysis results.

[0044] Beneficial effects:

[0045] This invention proposes a concurrent simulation testing method for IVCPS vehicle-mounted terminals, which allows for flexible adjustment of the simulation environment. Based on the IVCPS scenario, this invention constructs a vehicle-side module, a cloud module, a roadside facility module, and a vehicle-side information processing module. These modules can receive and send information to each other, achieving efficient information interaction. Simultaneously, communication modules are built between vehicles and the road, vehicles and the cloud, and vehicles themselves, utilizing TCP / IP or UDP / IP communication protocols to complete information transmission and interaction between the vehicle-road-cloud modules in a real local area network environment. Furthermore, vehicle-side performance monitoring and communication performance monitoring modules are also constructed, which can be used to monitor performance bottlenecks under concurrent scenarios.

[0046] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of a concurrent simulation test of an IVCPS vehicle terminal according to the present invention;

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

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

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

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

[0052] Figure 6 Main vehicle communication receiving module;

[0053] Figure 7The main vehicle receives speed information from the adjacent vehicle.

[0054] Figure 8 For monitoring the performance of the main vehicle under different concurrent vehicle numbers. Detailed Implementation

[0055] To make the technical solutions, advantages, and objectives of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the protection scope of this application.

[0056] like Figure 1 As shown, this invention provides a concurrent simulation testing method for an IVCPS vehicle terminal, comprising the following steps:

[0057] S1. Use software to simulate and build the traffic environment. Based on the IVCPS scenario, build 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 matches real-world road conditions, including complex scenarios 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 can be one or more of the following: camera, lidar, and millimeter-wave radar.

[0061] During the construction process, S1.3 sets the dynamic behavior parameters of vehicles and combines them with roadside facility modules such as traffic lights and road signs to simulate actual traffic flow and traffic rules.

[0062] Vehicle dynamic behavior parameters include speed, acceleration, and braking distance;

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

[0064] Vehicle-mounted module: This module collects environmental information and vehicle status information from sensors installed on the vehicle. This information includes, but is not limited to, vehicle speed, acceleration, vehicle position, and road conditions ahead. After initial processing and packaging, the collected data is transmitted to the cloud module and roadside infrastructure module via the communication module. Furthermore, the vehicle-mounted module possesses powerful concurrent processing capabilities, enabling real-time decoding, orchestration, balanced distribution, and processing of multi-source data. This ensures that the vehicle can quickly make driving control decisions upon receiving information from the cloud, roadside infrastructure, its own real-time perception systems, and neighboring vehicles.

[0065] Specifically, the message concurrency processing function in the vehicle module integrates and sorts messages from different information sources based on the importance and timestamp of the data, prioritizing the processing of critical data. The balanced allocation function ensures the reasonable use of computing resources and bandwidth to avoid system overload. The concurrency scheduling function uses intelligent scheduling algorithms to dynamically allocate processing tasks to multiple threads or multiple processor cores, improving the overall system response speed and processing efficiency.

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

[0067] Cloud module: It performs calculations and makes decisions by receiving data 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 vehicle-side module with the optimal route planning based on 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 facility.

[0069] Roadside facility module: Real-time monitoring of the road environment, collection of traffic flow and pedestrian dynamic information, and broadcasting traffic alerts such as congestion ahead, accident warnings, and speed limit reminders to the vehicle-side module via RSU.

[0070] Vehicle-side information processing module: receives and processes cloud-based, vehicle-side, and roadside data as well as the vehicle's own sensing data in real time.

[0071] The vehicle-side information processing module includes a vehicle-side message orchestration module, a resource balancing allocation module, and a concurrent scheduling module (such as...). Figure 2(As shown). The vehicle-side message orchestration module is responsible for receiving and integrating data from multiple information sources, including traffic instructions from the cloud, driving status data from neighboring vehicles, and real-time perception data from the vehicle's sensors. By setting information priorities and timestamps, the vehicle-side message orchestration module can sort information according to predetermined rules, ensuring that key data enters the processing queue first, thereby reducing the risk of information delays and data loss. The resource balancing allocation module is used to rationally 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, thereby ensuring the overall performance stability of the system and effectively avoiding overload caused by uneven resource allocation. The concurrent scheduling module adopts an intelligent scheduling algorithm, which automatically allocates 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 and the cloud module work together to adjust the control strategy of traffic lights based on the optimization schemes fed back by the cloud module, so as to ensure smooth and safe road traffic.

[0073] S2. Based on TCP / IP or UDP / IP communication protocols, construct communication modules between vehicles and infrastructure, vehicles and cloud, and vehicles and vehicles to complete information transmission and interaction between vehicle-infrastructure-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 vehicle 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] The vehicle-mounted terminal module includes communication modules for various sensors. These modules integrate and compress data collected from the cloud, roadside facilities, and other vehicles, and receive this data via a communication receiving module. This data then enters a message distribution module, which distributes it to the appropriate data processing modules based on priority and data type. The data processing modules parse and process the received information, and then send the processed information to the main vehicle module or other vehicles via TCP / IP or UDP / IP protocols through a message sending module. This ensures efficient processing and transmission of multi-source information in concurrent scenarios. In the cloud module, the received data is processed, and optimized control commands and information packets are sent to the main vehicle module via the same communication module. The cloud module also includes a self-organizing network module for managing dynamic vehicle communication. When a vehicle leaves, the self-organizing network module reclaims the corresponding communication port; when a vehicle enters, the module assigns it a unique port number, 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 host vehicle's IP address and collect its performance data. First, JMeter needs to be configured to access the IP addresses of both the vehicle and cloud endpoints. By setting JMeter's HTTP request sampler (or TCP / UDP request sampler) to specify the IP addresses and corresponding port numbers of the vehicle and cloud endpoints, network requests can be sent. Through JMeter's performance monitoring plugin, real-time performance data from both the host vehicle and cloud endpoints can be collected, including key metrics such as CPU utilization, memory usage, and network throughput, allowing for the monitoring of system performance bottlenecks under high load. For example, when information is simultaneously being sent to the host vehicle from the neighboring vehicle, the cloud, and the road network, the consumption of the host vehicle's CPU or memory resources and changes in throughput can be monitored to identify potential performance bottlenecks in the host vehicle's onboard system for subsequent optimization.

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

[0080] The communication performance monitoring module deploys Wireshark within the local area network environment of the IVCPS system. By configuring a listening interface, it captures all incoming and outgoing network traffic from the main vehicle. Filters are set to specifically capture TCP / IP or UDP / IP packets between the main vehicle and neighboring vehicles / the cloud, analyzing key network performance indicators such as data transmission latency, packet loss rate, and retransmission count. Through detailed monitoring and analysis of communication between the main vehicle and neighboring vehicles / the cloud, Wireshark provides accurate network traffic information and protocol analysis results. For example, simultaneous communication by a large number of vehicles, roadside facilities, and cloud devices can lead to network congestion, increasing latency and packet loss rate. By capturing and analyzing data streams in these concurrent scenarios using Wireshark, increased retransmission counts due to network congestion or decreased efficiency of specific protocols under high concurrency can be detected. This bottleneck information can be used to further optimize communication protocols and network configurations to improve the overall performance and reliability of the system under high concurrency conditions.

[0081] Example 1

[0082] In the example, a scenario of an IVCPS urban intersection was constructed to simulate the communication and control process between the main vehicle and ten adjacent vehicles as they approach or enter the intersection. The data transmission link diagram is shown below. Figure 3 As shown, the key features of the in-vehicle system are message sending, message listening, message orchestration and distribution, and message processing functions. The overall architecture diagram is as follows. Figure 4 As shown.

[0083] Here are the key points for each step:

[0084] Step 1: Setting up the traffic scenario

[0085] A two-way, four-lane traffic scenario was constructed using PreScan, with each lane 3.5 meters wide, an intersection length of 100 meters, and a maximum speed of 50 km / h. This scenario simulates the traffic behavior of the main vehicle and ten adjacent vehicles at a crossroads. Figure 5 As shown.

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

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

[0088] Table 1 Vehicle Speed ​​Parameters

[0089]

[0090] Step 3: Configuration of main vehicle, side vehicles and cloud platform

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

[0092] Master vehicle: IP address: 192.168.1.2, Transmitting port: 5001, Receiving port: 6001

[0093] Side vehicle 1: IP address: 192.168.1.3, sending port: 5002, receiving port: 6002

[0094] Side vehicle 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 vehicle sends real-time vehicle status information (such as speed, location, etc.) to the cloud through the configured communication module.

[0098] Message orchestration and distribution: During message orchestration and distribution, the cloud not only integrates and processes the received vehicle status information, but also performs protocol and format conversion on the information. After processing, the cloud concurrently sends the results to the master vehicle, ensuring that the master 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 (e.g.) Figure 6 (As shown) is responsible for receiving and organizing information from the cloud. To ensure that the main vehicle can accurately receive and process information from the cloud and other vehicles during high-speed movement, the system is set with a sampling interval of 0.05 seconds and a simulation step size of 0.5 seconds. With this configuration, the main vehicle can guarantee high temporal resolution of data and reduce latency and errors in complex dynamic traffic environments.

[0100] After receiving the information, the message processing module of the main vehicle (such as...) Figure 2 (As shown) Decoding is performed first. This module has powerful concurrent processing capabilities, enabling it to orchestrate messages from the cloud and other vehicles based on data importance and timestamps, prioritizing critical data. Subsequently, a balanced allocation function is used to rationally allocate computing resources, avoiding system overload and ensuring processing efficiency. Through an intelligent concurrent scheduling algorithm, the communication module dynamically allocates processing tasks to multiple threads or processor cores, further improving the system's response speed and processing capacity.

[0101] During the simulation, the main vehicle can display the received speed information of the adjacent vehicles in real time (such as...). Figure 7 As shown in the figure, the simulation results were verified to confirm whether they met expectations. This process verified the processing performance of the main vehicle communication module under high concurrency conditions, ensuring that the main vehicle can make accurate driving control decisions quickly after receiving multi-source information.

[0102] Step 4: JMeter Performance Monitoring

[0103] Using JMeter to monitor the system performance of the host vehicle: Configure JMeter to sample requests from the host vehicle's IP address to monitor the performance of the in-vehicle system. First, configure an HTTP request sampler or a TCP / UDP request sampler in JMeter to specify the host vehicle's IP address and corresponding port number, thereby enabling network requests to be sent to the host vehicle. Specific steps include adding a sampler to the test plan and setting the host vehicle's IP address and port number within the sampler. With these configurations, JMeter can send network requests and communicate with the host vehicle. Next, using JMeter's performance monitoring plugin, collect key performance data of the host vehicle in real time, such as CPU utilization, memory usage, and network throughput. During actual testing, performance metrics changes under different scenarios can be monitored and recorded, such as... Figure 8 As shown, the trends of CPU, memory, and throughput of the host vehicle under different concurrent vehicle numbers are crucial for evaluating the host vehicle's performance 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 listening and filtering: Capture specific communication data packets between the master vehicle and the neighboring vehicle by configuring the listening interface and filters.

[0107] Message Analysis: Analyzing these data packets assesses the system's network performance metrics, including transmission latency, packet loss rate, and retransmission count. When five neighboring vehicles simultaneously send data to the master vehicle, Wireshark monitoring results show a 0% packet loss rate, indicating that under this concurrency scenario, the master vehicle can reliably receive all communication data packets from the neighboring vehicles without any data loss, demonstrating good network communication performance. However, when the number of concurrent vehicles increases to ten, Wireshark analysis shows that the packet loss rate rises to 0.46%. This means that as the number of concurrent vehicles increases, communication between the master vehicle and the neighboring vehicles begins to be affected by network bandwidth or other factors, leading to slight packet loss. Although the packet loss rate is low, this result indicates that the system's communication stability decreases 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 intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An IVCPS vehicle terminal concurrent simulation test method, characterized in that, Comprise the following steps: S1. Use software to simulate the traffic environment, according to IVCPS scene, build car end module, cloud module, roadside facilities module and car end information processing module; S1.1 create a simulation environment that meets the actual road conditions using PreScan; 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 on each vehicle; The sensor module is used to simulate the real perception ability, 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 the traffic signal and the road sign to simulate the actual traffic flow and traffic rules; The dynamic behavior parameters of the vehicle include speed, acceleration and braking distance; S1.4 build car end module, cloud module, roadside facilities module and car end information processing module; Car end module: collect the environmental information around the vehicle and the state information of the vehicle through the sensor module installed on the vehicle, and the car end module is connected with the cloud module and the roadside facilities module through the communication module; Cloud module: calculate and decide by receiving data information from multiple car end modules and roadside facilities modules; The cloud module can optimize the scheduling strategy of the global traffic signal according to the received traffic flow information, or provide the optimal path planning for the car end module according to the real-time road conditions, and the processing result is sent back to the car end module and the roadside facilities module through the cloud module, guiding the driving behavior of the vehicle and the control strategy of the roadside facilities; Roadside facilities module: real-time monitoring of road environment, collection of traffic flow and pedestrian dynamic information, and broadcasting of traffic prompt information to car end module through RSU; Car end information processing module: real-time receiving and processing of cloud, car end, road and self-perception data; In addition, the roadside facilities module and the cloud module work together, and can adjust the control strategy of the traffic signal according to the optimization scheme fed back by the cloud module, to ensure the smoothness and safety of road traffic; S2. Based on TCP / IP or UDP / IP communication protocol, build communication module between car, road and cloud, and between cars, complete information transmission and interaction between car, road and cloud modules in real local area network environment; 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 car end module, the cloud module and the roadside facilities module; S2.2 message sending; In the vehicle terminal module, configure various sensors, integrate and compress the data information collected by multiple vehicles through the communication module, and send it to the cloud module; S2.3 message arrangement and distribution; In the message arrangement and distribution process, the cloud module can not only integrate and process the received vehicle state information according to the priority and data type, but also can perform protocol conversion and format conversion, and send the result to the car end after processing; S2.4 message processing; The vehicle end receives real-time data from the cloud, the road end, other vehicles and its own sensor perception data through the communication module, and completes concurrent processing of the messages through the vehicle end information processing module; S3. Building a vehicle end performance monitoring module; The specific steps of the step S3 of building a vehicle end performance monitoring module are: First, configure JMeter to access the IP address of the host vehicle, set the HTTP request sampler or TCP / UDP request sampler of JMeter, specify the IP address and corresponding port number of the host vehicle, and send network requests to the host vehicle, collect the performance data of the host vehicle in real time through the performance monitoring plug-in of JMeter, including CPU usage, memory occupation and network throughput, and monitor the bottleneck of system performance under high load; S4. Building a vehicle end communication performance monitoring module; The specific steps of the step S4 of building a vehicle end communication performance monitoring module are: Deploy Wireshark in the local network environment where the IVCPS system is located, capture all network traffic in and out of the host vehicle by configuring the listening interface, capture TCP / IP or UDP / IP data packets between the host vehicle, the side vehicle, the road end and the cloud by setting the filter, analyze the delay, packet loss rate and retransmission number of data transmission, and provide accurate network traffic information and protocol analysis results.

2. The method of claim 1, wherein the method further comprises: In the step S1.4, the information collected by the vehicle end module includes vehicle speed, acceleration, vehicle position and road conditions ahead.

3. The method of claim 2, wherein the method further comprises: In the step S1.4, the traffic prompt information broadcasted by the road side facility module includes congestion ahead, accident warning and speed limit reminder.

4. The method of claim 3, wherein the method further comprises: In the step S2.3, the cloud module further includes a self-organizing network module for managing dynamic communication of vehicles, when a vehicle drives out, the self-organizing network module recycles the corresponding communication port; when a vehicle drives in, the self-organizing network module allocates a unique port number for the vehicle, so as to ensure smooth and efficient communication between the vehicle and other vehicles, road side facilities and the cloud.

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