Traffic control method and device based on vehicle networking DDS cross-domain communication system

Abstract

The application provides a traffic control method and device based on a vehicle networking DDS cross-domain communication system, and is applied to a cloud server. The method comprises the following steps: acquiring standardized data of each vehicle on a target road section by using the vehicle networking DDS cross-domain communication system; analyzing traffic flow on the target road section based on the standardized data of each vehicle to obtain a road condition evaluation result, and formulating a traffic control strategy based on the road condition evaluation result; encoding the traffic control strategy to obtain a traffic control instruction; and sending the traffic control instruction to a roadside device, so that the roadside device adjusts a signal light timing scheme according to the traffic control instruction to obtain traffic signal adjustment data. The application realizes efficient management and application of real-time state data of vehicles through the vehicle networking DDS cross-domain communication system, and enhances the real-time performance and accuracy of traffic control.

Description

Technical Field

[0001] This application relates to the field of traffic control technology, and in particular to traffic control methods and devices based on vehicle-to-everything (V2X) DDS cross-domain communication systems. Background Technology

[0002] Existing systems have limitations in cross-domain communication and data management. Vehicle-to-everything (V2X) systems exhibit poor interoperability between different manufacturers and devices, limiting the efficiency and coverage of information sharing. When faced with real-time, large-scale data, these systems typically lack sufficient response speed and processing capacity, potentially leading to data delays or incompleteness, thus affecting the timely formulation and implementation of traffic management strategies. In emergency situations, technological limitations make it difficult for systems to adjust traffic lights or update road condition information in a timely manner, resulting in congested traffic, reduced vehicle safety, and further exacerbating the likelihood of traffic jams and accidents. Summary of the Invention

[0003] In view of this, this application provides a traffic control method and apparatus based on a vehicle-to-everything (V2X) DDS cross-domain communication system to solve the above-mentioned technical problems.

[0004] In a first aspect, embodiments of this application provide a traffic control method based on a vehicle-to-everything (V2X) DDS cross-domain communication system, applied to a cloud server, comprising: The DDS cross-domain communication system for vehicle-to-everything (V2X) is used to acquire standardized data of each vehicle on the target road segment. Based on standardized data from each vehicle, traffic flow on the target road segment is analyzed to obtain road condition assessment results, and traffic control strategies are formulated based on the road condition assessment results. The traffic control strategy is encoded to obtain traffic control instructions; The traffic control command is sent to the roadside equipment so that the roadside equipment can adjust the traffic light timing scheme according to the traffic control command and obtain traffic signal adjustment data.

[0005] Secondly, embodiments of this application provide a traffic control device based on a vehicle-to-everything (V2X) DDS cross-domain communication system, applied to a cloud server, comprising: The acquisition unit is used to acquire standardized data of each vehicle on the target road segment using the vehicle-to-everything (V2X) DDS cross-domain communication system. The processing unit is used to analyze the traffic flow of the target road segment based on the standardized data of each vehicle to obtain the road condition assessment results, and to formulate traffic control strategies based on the road condition assessment results. The encoding unit is used to encode the traffic control strategy to obtain traffic control instructions; The control unit is used to send the traffic control command to the roadside equipment so that the roadside equipment can adjust the traffic light timing scheme according to the traffic control command and obtain traffic signal adjustment data.

[0006] Thirdly, embodiments of this application provide an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method of embodiments of this application.

[0007] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the methods of embodiments of this application.

[0008] Fifthly, embodiments of this application provide a computer program product, including a computer program / instructions, which, when executed by a processor, implement the method of embodiments of this application.

[0009] This application utilizes a vehicle-to-everything (V2X) DDS cross-domain communication system to achieve efficient management and application of real-time vehicle status data, thereby enhancing the real-time performance and accuracy of traffic control. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0011] Figure 1 A flowchart illustrating a traffic control method based on a vehicle-to-everything (V2X) DDS cross-domain communication system provided in this application embodiment; Figure 2 A functional structure diagram of a traffic control device based on a vehicle-to-everything (V2X) DDS cross-domain communication system provided in this application embodiment; Figure 3 This is a structural diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0013] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0014] The technical solutions provided in the embodiments of this application will be described below.

[0015] like Figure 1 As shown, this embodiment proposes a traffic control method based on a vehicle-to-everything (V2X) DDS cross-domain communication system, applied to a cloud server, including: Step 101: Use the vehicle-to-everything (V2X) DDS (Data Distribution Service) cross-domain communication system to obtain standardized data of each vehicle on the target road segment; Step 102: Based on the standardized data of each vehicle, analyze the traffic flow of the target road segment to obtain the road condition assessment results, and formulate traffic control strategies based on the road condition assessment results; Step 103: Encode the traffic control strategy to obtain traffic control instructions; Step 104: Send traffic control instructions to the roadside equipment so that the roadside equipment can adjust the traffic light timing scheme according to the traffic control instructions and obtain traffic signal adjustment data.

[0016] For example, roadside equipment includes traffic light controllers and information display panels. A suitable wireless communication technology, such as cellular network, DSRC, or Wi-Fi, is selected to establish a communication connection between the cloud server and the target roadside equipment.

[0017] This embodiment utilizes a vehicle-to-everything (V2X) DDS cross-domain communication system to achieve efficient management and application of real-time vehicle status data, enhancing the real-time performance and accuracy of traffic control. In terms of traffic flow analysis and road condition assessment, traffic control strategies are formulated based on the latest data, instructions are quickly issued, and signal configurations of roadside equipment are adjusted. By continuously monitoring and providing feedback on signal adjustment results, traffic management measures are evaluated and optimized in real time, making strategies more flexible and responsive, thereby reducing traffic congestion and improving road safety.

[0018] The method in this embodiment can be applied to: Urban traffic management: Applicable to scenarios such as urban traffic signal control, traffic flow monitoring, and emergency response, improving urban traffic efficiency.

[0019] Highway monitoring: On highways, the system can be used to monitor traffic flow in real time, predict and mitigate congestion, and improve driving safety.

[0020] Connected vehicle service providers: Provide technical support to connected vehicle service providers to enhance their service competitiveness.

[0021] In some embodiments, the standardized data includes vehicle speed, location, and fuel consumption formatted according to the DDS protocol; the method further includes data acquisition via onboard sensors: Receives encrypted, standardized data sent by each vehicle through the DDS cross-domain communication system of the vehicle network; Decrypt the encrypted standardized data to obtain the standardized data for each vehicle; The standardized data of each vehicle is verified for data integrity to obtain the verified standardized data; Validated standardized data is stored in a cloud database.

[0022] Specifically, multiple copies of the data are created to ensure data recoverability in the event of any hardware failure. At the same time, backup technology is used to regularly back up the database content to ensure long-term secure data storage. The combined effect of data storage and protection measures optimizes secure data storage and provides the system with continuous and reliable data services. After data storage is completed, cloud-based confirmation data is generated to facilitate system tracking and auditing.

[0023] In this embodiment, vehicle speed, location, and fuel consumption information are collected in real time, converted into standardized data, and centrally processed in the cloud to ensure timely updates and comprehensive analysis. The implementation of cross-domain communication significantly enhances interoperability between different manufacturers and devices, providing drivers and road network managers with more comprehensive and accurate information, which helps optimize traffic flow and improve road safety.

[0024] In some embodiments, the step of generating the standardized data includes: Based on the real-time acquisition of vehicle speed, GPS location and fuel consumption data by on-board sensors, the data is transmitted to the processing module through multi-channel input. The processing module integrates data filtering algorithms, uses frequency domain analysis to remove high-frequency noise in the signal, and then uses a low-pass filter to retain low-frequency effective data. During this process, the clock synchronization function of the sensor ensures the consistency of data acquisition time, optimizes the accuracy of data, and obtains vehicle dynamic information. Based on vehicle dynamic information, the analog signal of vehicle speed is input into the analog-to-digital converter. The converter samples the signal according to the preset sampling frequency and converts the analog signal into a digital signal through a quantization step. The GPS coordinate information is formatted and the latitude and longitude data is converted into a standard digital encoding format using an encoding algorithm. The process ensures lossless signal conversion and data consistency. Through conversion and processing steps, digital signal data is obtained. Based on digital signal data, key parameters such as vehicle speed, location and fuel consumption information are extracted from the digital signals. For fuel consumption data, real-time computing technology is used to calculate the instantaneous fuel consumption rate and cumulative consumption of the vehicle through real-time analysis of the fuel consumption signal. The process involves real-time updating and storage of data to ensure the timeliness and accuracy of the data. After integrating the data, the vehicle status is recorded and updated to obtain the real-time status data of the vehicle. Based on real-time vehicle status data, checksums and compliance assessments of data formats are performed on data packets. Algorithms compare the consistency and integrity of data within each part of the data packet to identify any possible data corruption or incorrect format issues. All detected data that does not conform to preset standards is discarded or marked to ensure that only data that conforms to the predetermined format and standards can be further processed. Data that passes verification is then timestamped and marked with a verification pass identifier for reference in subsequent processes, thus obtaining verified data. Based on the verified data, data compression and encryption are performed. The data is compressed using a preset compression algorithm. The compressed data flows to the encryption unit, where encryption technology is used to ensure the security of data transmission in any network environment. The encryption algorithm includes, but is not limited to, symmetric and asymmetric encryption technologies to ensure that only authorized recipients can decrypt and access the data. After processing, the generated data packet is marked as compressed and encrypted data, ready for network transmission. Based on compressed and encrypted data, data encapsulation processing is performed. An automated protocol encapsulation process is used to add DDS protocol header information to ensure that the data packets conform to the data distribution service standard. Then, the data packets are fully formatted, including serializing the data structure and encapsulating it according to the preset communication protocol standard. During the encapsulation process, the compatibility of the data structure and protocol is ensured. The generated data packets fully comply with the standards for subsequent system reception and processing, resulting in standardized vehicle data. Based on standardized vehicle data, and utilizing the built-in security features of the HTTPS protocol, such as Transport Layer Security (TLS) and Secure Sockets Layer (SSL), end-to-end encryption of data packets is performed. This process includes the generation and exchange of public and private keys, ensuring that the data is encrypted before being sent. The data is then uploaded to a cloud server through a secure network channel, typically an authenticated VPN or a direct SSL connection, enhancing the security and privacy of data transmission over the internet and resulting in encrypted uploaded data.

[0025] In this embodiment, key data such as vehicle speed, location, and fuel consumption can be collected in real time and processed rapidly to provide immediate decision support for traffic management. The DDS protocol is used to achieve efficient data transmission between different manufacturers and devices.

[0026] Cloud databases can store large amounts of data, improving data processing efficiency and accuracy.

[0027] In some embodiments, traffic flow on a target road segment is analyzed based on standardized data from each vehicle to obtain a road condition assessment result; including: The standardized data of each vehicle is matched with historical traffic condition data to obtain the traffic density and average speed of the target road segment. Traffic flow is obtained by processing standardized data of each vehicle using a traffic flow model; Correlation analysis is performed on the traffic density, traffic flow, and average vehicle speed of the target road segment to obtain road condition assessment results.

[0028] In some embodiments, the traffic control strategy is encoded to obtain traffic control instructions; including: Traffic control strategies are decomposed based on roadside equipment to generate a set of instructions to be executed in stages, including: the time allocation ratio of traffic lights and the content update text of information boards; The execution of the instruction set is tested by simulating the environment of roadside equipment to verify the correctness and completeness of the instruction set. The instruction set that passes the verification is determined as the traffic control instruction. The traffic control instruction is the intersection traffic signal adjustment instruction, emergency road condition response instruction, or traffic information update instruction.

[0029] In some embodiments, the roadside equipment adjusts the traffic light timing scheme according to traffic control instructions to obtain traffic signal adjustment data, including: The roadside equipment parses the traffic light timing information in the traffic control instructions, extracts the parameters of each traffic light, including: green light duration, red light duration, and yellow light switching time; calls the timing control program to transmit the traffic light parameters to the timer of the traffic light control unit, forming a new traffic signal timing and generating traffic signal adjustment data.

[0030] In some embodiments, the method further includes: The control system updates roadside traffic signs based on traffic signal adjustment data, including changing turn arrow indicators and speed limit signs, to obtain updated roadside facility data.

[0031] In some embodiments, the method further includes: Based on roadside facility update data, determine the response time of roadside equipment; The efficiency of roadside equipment in executing traffic control commands is calculated based on the time difference between the arrival of traffic control commands at roadside equipment and the status update of roadside equipment. Adjust the monitoring interval of the roadside equipment based on its response time and efficiency in executing traffic control commands; Based on the monitoring intervals of roadside equipment, the traffic light adjustment results are obtained; the traffic light adjustment results include traffic light timing adjustment information, traffic flow guidance effect, and real-time traffic feedback information.

[0032] In some embodiments, the method further includes: After the traffic lights are adjusted, the DDS cross-domain communication system of the vehicle network is used to receive data packets uploaded by vehicles from various traffic nodes in order to obtain vehicle information from multiple traffic nodes. Statistical analysis of vehicle information at multiple traffic nodes yields traffic flow change data; Based on traffic flow change data, the effectiveness of traffic control strategies is evaluated, and an evaluation score is obtained.

[0033] Specifically, each traffic node receives data packets uploaded by vehicles, including specific information such as the speed, location, and waiting time of each vehicle. The data from each node is grouped and processed using a unique identifier. The contents of each data packet are parsed one by one to extract vehicle identifiers, timestamps, and relevant performance data. A time synchronization mechanism is used to calibrate the time dimension of all node data to ensure that all data can be compared and integrated on the same timeline. The integrated data is categorized by node and stored in a multi-node vehicle information database to obtain multi-node vehicle information.

[0034] In some embodiments, statistical analysis is performed on vehicle information from multiple traffic nodes to obtain traffic flow change data; including: Data sets from various traffic nodes are retrieved from the cloud database. Based on time periods, vehicle speed, location, and waiting time are statistically processed to calculate the average traffic flow and its changing trends. By comparing traffic flow between traffic nodes, specific areas of traffic increase or decrease can be identified, and congestion points and their occurrence times can be extracted from the datasets of each traffic node. By statistically analyzing the frequency distribution of congestion points and related time periods, statistical results are generated that include traffic flow increases and decreases as well as congestion point conditions, thus obtaining traffic flow analysis data.

[0035] In some embodiments, the effectiveness of traffic control strategies is evaluated based on traffic flow change data to obtain an evaluation score, including: Execution assessment score The calculation formula is:

[0036] in, The average vehicle speed before the implementation of traffic control strategies. Vehicle count before implementing traffic control strategies, To count vehicles after implementing traffic control strategies, The percentage decrease in average vehicle speed after implementing traffic control strategies. This refers to the adjusted traffic light cycle time. For traffic flow at the intersection, , , and All are weighting coefficients.

[0037] Parameter details and acquisition methods: Average vehicle speed before the strategy was implemented: calculated from speed data collected at control points and provided by the vehicle-to-everything (V2X) network.

[0038] Vehicle count before strategy implementation: This is obtained from the number of vehicles counted by traffic cameras or traffic flow sensors within the same time window, or provided by the Internet of Vehicles, reflecting the total number of vehicles passing through the intersection within a specific time period.

[0039] Vehicle count after strategy implementation: As above, data is collected in the same time window after strategy implementation to assess the direct impact of the strategy.

[0040] Percentage decrease in average vehicle speed after implementing the strategy: by comparison and average vehicle speed after implementation According to the formula The calculation yielded the result.

[0041] Adjusted traffic light cycle times: Signal adjustment parameters are based on optimized calculations of intersection traffic flow and waiting time by traffic engineers.

[0042] Intersection traffic flow: and and Similarly, but focusing on specific areas at intersections, which are usually the traffic nodes most affected by the strategy.

[0043] Weighting coefficient , , and The coefficients are determined based on historical data analysis and expert system optimization output, and are used to adjust the influence of various parameters in the congestion index calculation. The setting of these coefficients typically involves multiple iterations and feedback adjustments to ensure the model's adaptability and accuracy. The impact of adjusting average vehicle speed on the congestion index Adjusting the impact of changes in vehicle count on the congestion index. Adjust the weighting of the percentage change in average vehicle speed. The impact of adjusting traffic flow at intersections on signal cycle adjustment.

[0044] Calculation example: Set the following parameters: km / h (average vehicle speed before the strategy was implemented). Vehicles (vehicle count before strategy implementation). Vehicles (count of vehicles after the strategy is implemented). km / h (average vehicle speed after the strategy is implemented) Seconds (adjusted traffic light cycle) Vehicles (traffic flow at intersections) , , , .

[0045] calculate :

[0046] calculate :

[0047]

[0048] Calculation results A low value indicates that traffic flow management strategies have not effectively reduced congestion. This index can help traffic management departments assess and adjust traffic control strategies to optimize road utilization.

[0049] Based on the same inventive concept, this application provides a traffic control device based on a vehicle-to-everything (V2X) DDS cross-domain communication system, applied to a cloud server, see reference. Figure 2 As shown, the traffic control device 200 based on the vehicle-to-everything (V2X) DDS cross-domain communication system provided in this application embodiment includes at least: The acquisition unit 201 is used to acquire standardized data of each vehicle in the target road segment using the vehicle-to-everything (V2X) DDS cross-domain communication system. The processing unit 202 is used to analyze the traffic flow of the target road segment based on the standardized data of each vehicle to obtain the road condition assessment results, and to formulate traffic control strategies based on the road condition assessment results. Encoding unit 203 is used to encode the traffic control strategy to obtain traffic control instructions; The control unit 204 is used to send the traffic control command to the roadside equipment so that the roadside equipment can adjust the traffic light timing scheme according to the traffic control command and obtain traffic signal adjustment data.

[0050] It should be noted that the principle of the traffic control device 200 based on the vehicle-to-everything (V2X) DDS cross-domain communication system provided in this application embodiment to solve the technical problem is similar to the method provided in this application embodiment. Therefore, the implementation of the traffic control device 200 based on the V2X DDS cross-domain communication system provided in this application embodiment can refer to the implementation of the method provided in this application embodiment, and the repeated parts will not be described again.

[0051] Based on the same inventive concept, embodiments of this application also provide an electronic device, such as... Figure 3 As shown, it includes a memory and a processor. The memory stores an executable program, and the processor executes the executable program to implement the steps of the traffic control method based on the vehicle-to-everything (V2X) DDS cross-domain communication system provided in the above embodiments.

[0052] The aforementioned processor can be a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The aforementioned PLD can be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0053] Since the electronic device described in this application embodiment is an electronic device equipped with a memory for implementing the traffic control method based on the vehicle-to-everything (V2X) DDS cross-domain communication system disclosed in this application embodiment, those skilled in the art can understand the structure and variations of the electronic device described in this application embodiment based on the traffic control method based on the vehicle-to-everything (V2X) DDS cross-domain communication system disclosed in this application embodiment, and therefore will not be described again here.

[0054] This application also provides a computer-readable storage medium storing a computer program thereon. When the computer program is run by a processor, it implements the steps of the traffic control method based on the vehicle-to-everything (V2X) DDS cross-domain communication system provided in the above embodiments.

[0055] The storage medium in this embodiment may be included in an electronic device; or it may exist independently and not be assembled into an electronic device. The storage medium carries one or more computer programs, which, when executed, implement the steps of the traffic control method based on the vehicle-to-everything (V2X) DDS cross-domain communication system provided in the above embodiment.

[0056] It should be understood that the various solutions in this embodiment have the same technical effects as those in the above method embodiments, and will not be repeated here.

[0057] According to embodiments of this application, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. Optionally, specific examples in this embodiment can refer to the examples described in any embodiment of this application, which will not be repeated here. Obviously, those skilled in the art should understand that the various modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular hardware and software combination.

[0058] This application also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the traffic control method based on the vehicle-to-everything (V2X) DDS cross-domain communication system provided in the above embodiments.

[0059] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions targeted in the blocks may occur in a different order than those targeted in the drawings. For example, two consecutively represented blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0060] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. Multitasking and parallel processing may be advantageous in certain environments. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this application. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

Claims

1. A traffic control method based on a vehicle-to-everything (V2X) DDS cross-domain communication system, applied to a cloud server, characterized in that: include: The DDS cross-domain communication system for vehicle-to-everything (V2X) is used to acquire standardized data of each vehicle on the target road segment. Based on standardized data from each vehicle, traffic flow on the target road segment is analyzed to obtain road condition assessment results, and traffic control strategies are formulated based on the road condition assessment results. The traffic control strategy is encoded to obtain traffic control instructions; The traffic control command is sent to the roadside equipment so that the roadside equipment can adjust the traffic light timing scheme according to the traffic control command and obtain traffic signal adjustment data.

2. The method according to claim 1, characterized in that, The standardized data includes vehicle speed, location, and fuel consumption formatted according to the DDS protocol; the method further includes: Receives encrypted, standardized data sent by each vehicle through the DDS cross-domain communication system of the vehicle network; Decrypt the encrypted standardized data to obtain the standardized data for each vehicle; The standardized data of each vehicle is verified for data integrity to obtain the verified standardized data; Validated standardized data is stored in a cloud database.

3. The method according to claim 1, characterized in that, Based on standardized data from each vehicle, traffic flow on the target road segment is analyzed to obtain road condition assessment results, including: The standardized data of each vehicle is matched with historical traffic condition data to obtain the traffic density and average speed of the target road segment. Traffic flow is obtained by processing standardized data of each vehicle using a traffic flow model; Correlation analysis is performed on the traffic density, traffic flow, and average vehicle speed of the target road segment to obtain road condition assessment results.

4. The method according to claim 3, characterized in that, The traffic control strategy is encoded to obtain traffic control instructions; including: Traffic control strategies are decomposed based on roadside equipment to generate a set of instructions to be executed in stages, including: the time allocation ratio of traffic lights and the content update text of information boards; The execution of the instruction set is tested by simulating the environment of roadside equipment to verify the correctness and completeness of the instruction set. The instruction set that passes the verification is determined as the traffic control instruction. The traffic control instruction is the intersection traffic signal adjustment instruction, emergency road condition response instruction, or traffic information update instruction.

5. The method according to claim 1, characterized in that, Roadside equipment adjusts traffic light timing schemes according to traffic control instructions, obtaining traffic signal adjustment data, including: The roadside equipment parses the traffic light timing information in the traffic control instructions, extracts the parameters of each traffic light, including: green light duration, red light duration, and yellow light switching time; calls the timing control program to transmit the traffic light parameters to the timer of the traffic light control unit, forming a new traffic signal timing and generating traffic signal adjustment data.

6. The method according to claim 5, characterized in that, The method further includes: The control system updates roadside traffic signs based on traffic signal adjustment data, including changing turn arrow indicators and speed limit signs, to obtain updated roadside facility data.

7. The method according to claim 6, characterized in that, The method further includes: Based on roadside facility update data, determine the response time of roadside equipment; The efficiency of roadside equipment in executing traffic control commands is calculated based on the time difference between the arrival of traffic control commands at roadside equipment and the status update of roadside equipment. Adjust the monitoring interval of the roadside equipment based on its response time and efficiency in executing traffic control commands; Based on the monitoring intervals of roadside equipment, the traffic light adjustment results are obtained; the traffic light adjustment results include traffic light timing adjustment information, traffic flow guidance effect, and real-time traffic feedback information.

8. The method according to claim 1, characterized in that, The method further includes: After the traffic lights are adjusted, the DDS cross-domain communication system of the vehicle network is used to receive data packets uploaded by vehicles from various traffic nodes in order to obtain vehicle information from multiple traffic nodes. Statistical analysis of vehicle information at multiple traffic nodes yields traffic flow change data; Based on traffic flow change data, the effectiveness of traffic control strategies is evaluated, and an evaluation score is obtained.

9. The method according to claim 8, characterized in that, Statistical analysis of vehicle information from multiple traffic nodes yields traffic flow change data, including: Data sets from various traffic nodes are retrieved from the cloud database. Based on time periods, vehicle speed, location, and waiting time are statistically processed to calculate the average traffic flow and its changing trends. By comparing traffic flow between traffic nodes, specific areas of traffic increase or decrease can be identified, and congestion points and their occurrence times can be extracted from the datasets of each traffic node. By statistically analyzing the frequency distribution of congestion points and related time periods, statistical results are generated that include traffic flow increases and decreases as well as congestion point conditions, thus obtaining traffic flow analysis data.

10. The method according to claim 8, characterized in that, Based on traffic flow change data, the effectiveness of traffic control strategies is evaluated, resulting in an evaluation score, including: Execution assessment score The calculation formula is: in, The average vehicle speed before the implementation of traffic control strategies. Vehicle count before implementing traffic control strategies, To count vehicles after implementing traffic control strategies, The percentage decrease in average vehicle speed after implementing traffic control strategies. This refers to the adjusted traffic light cycle time. For traffic flow at the intersection, , , and All are weighting coefficients.

11. A traffic control device based on a vehicle-to-everything (V2X) DDS cross-domain communication system, applied to a cloud server, characterized in that, include: The acquisition unit is used to acquire standardized data of each vehicle on the target road segment using the vehicle-to-everything (V2X) DDS cross-domain communication system. The processing unit is used to analyze the traffic flow of the target road segment based on the standardized data of each vehicle to obtain the road condition assessment results, and to formulate traffic control strategies based on the road condition assessment results. The encoding unit is used to encode the traffic control strategy to obtain traffic control instructions; The control unit is used to send the traffic control command to the roadside equipment so that the roadside equipment can adjust the traffic light timing scheme according to the traffic control command and obtain traffic signal adjustment data.

12. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method as claimed in any one of claims 1-10.

13. A computer-readable storage medium, characterized in that, A computer-readable storage medium stores computer instructions that, when executed by a processor, implement the methods of the embodiments of this application.

14. A computer program product, characterized in that, Includes a computer program / instruction that, when executed by a processor, implements the methods of the embodiments of this application.

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