PC5 communication site test method for vehicle-road cloud integrated system

Abstract

The invention discloses a PC5 communication site test method for a vehicle-road-cloud integrated system, and relates to the field of site test, and the method comprises the steps: a test preparation stage comprises the steps: providing an operation environment for the collection, comparison and analysis of test data, and completing the communication deployment and function initialization of a vehicle-road-cloud three-terminal test system; the communication performance test comprises the following steps: evaluating the link layer capability and the transmission quality in the process that the RSU broadcasts a message to a test vehicle through a PC5 direct connection communication interface; the message accuracy test comprises the following steps: receiving a message in real time through a vehicle-mounted device, and comparing and analyzing the message with truth value data acquired on site to realize error quantification and functional consistency verification of key information elements in the vehicle-road cloud system; the evaluation and judgment stage comprises the following steps: based on data obtained in the communication performance test and message accuracy test stage, carrying out quantitative analysis on the operation quality of the tested RSU and the whole vehicle-road cloud communication link, and constructing a unified performance evaluation system.

Description

Technical Field

[0001] This application relates to the field of field testing, and in particular to a field testing method for PC5 communication for vehicle-road-cloud integrated systems, a field testing device for PC5 communication for vehicle-road-cloud integrated systems, electronic equipment, storage media and testing platform. Background Technology

[0002] With the rapid development of Intelligent Connected Vehicles (ICVs) and next-generation Cooperative Vehicle Infrastructure Systems (CVIS), transportation systems are gradually evolving from a "vehicle-centric" model to a ubiquitous intelligent system that integrates vehicles, roads, and the cloud. Among these, C-V2X (Cellular Vehicle-to-Everything) technology, as a crucial communication foundation for intelligent transportation, utilizes the PC5 interface to enable low-latency, low-dependency direct communication between vehicles (V2V) and between vehicles and infrastructure (V2I), playing a key role in the integrated vehicle-road-cloud system.

[0003] The vehicle-road-cloud integrated system refers to a complex system that efficiently connects and coordinates traffic intelligent agents such as vehicle terminals, roadside units (RSUs), and a central cloud control platform through technologies such as information perception, communication interconnection, and edge computing. In this system, roadside RSUs periodically broadcast basic perception messages such as MAP (map information) and SPAT (traffic light information) through PC5 links, providing vehicles with local high-reliability environmental perception supplements and collaborative control support.

[0004] Currently, in the field of vehicle-road cooperative systems, there are some testing and verification schemes for the communication quality and functional accuracy of RSUs, but a unified and complete testing method has not yet been formed.

[0005] To meet the demands of intelligent connected vehicles for low-latency and high-reliability communication, C-V2X direct communication technology (PC5 interface) has been widely deployed in vehicle-road cooperative systems. Current typical testing schemes fall into two categories: The first is communication performance testing, which evaluates the physical communication capabilities and link stability of the RSU broadcasting messages via the PC5 interface. This covers core indicators such as maximum communication distance, coverage, packet loss rate, and end-to-end latency, and is verified in the field using a frequency sweeper and test vehicles. The second is message function accuracy testing, which focuses on the accuracy and consistency of the MAP and SPAT messages broadcast by the RSU. This includes the accuracy of map coordinates and road segment attributes, the accuracy of traffic light status timestamps, and message structure consistency. The testing process relies on ground truth acquisition equipment and high-precision positioning systems. Some studies have attempted to verify message quality through manual comparison, but this method is complex, inefficient, and lacks standardized evaluation criteria, making it difficult to support large-scale verification needs.

[0006] Although the two types of testing methods mentioned above have a certain technical foundation, they suffer from prominent problems in practical engineering applications, such as the separation of communication capability testing and functional verification, the fragmentation of indicator systems, and the lack of closed-loop verification processes. These issues make it difficult to comprehensively reflect the overall performance of the vehicle-road-cloud system's collaborative operation. Therefore, there is an urgent need for an integrated PC5 field testing method that combines communication capability and message accuracy, covers the system's collaborative process, and adapts to the deployment requirements of multiple scenarios, serving as a key supporting means for the deployment evaluation and standard setting of intelligent transportation systems.

[0007] Therefore, a solution for PC5 communication field testing of vehicle-road-cloud integrated systems is needed to solve the following core technical problems:

[0008] (1) To achieve collaborative testing and unified evaluation of communication performance indicators (such as maximum communication distance, packet loss rate, latency, etc.) and message accuracy indicators (such as MAP / SPAT message field consistency, time synchronization accuracy, etc.);

[0009] (2) Establish a full-link data path between RSU, vehicle terminal and cloud control platform to realize end-to-end spatiotemporal consistency verification and functional closed-loop verification;

[0010] (3) Improve the standardization and automation of the testing process, reduce manual intervention, and improve testing efficiency and result repeatability;

[0011] (4) Adapt to the consistency testing requirements of various test scenarios (such as closed test areas and open urban roads). Summary of the Invention

[0012] The purpose of this invention is to provide a PC5 communication field testing method, a PC5 communication field testing device, electronic equipment, storage medium, and testing platform for a vehicle-road-cloud integrated system. It addresses at least the following technical issues: adapting to consistency testing requirements across multiple testing scenarios; coordinating and uniformly evaluating communication performance indicators and message accuracy indicators; establishing a seamless data path between the RSU, vehicle terminal, and cloud control platform to achieve end-to-end spatiotemporal consistency verification and functional closed-loop verification; and improving the standardization and automation of the testing process, reducing manual intervention, and enhancing testing efficiency and result repeatability.

[0013] This invention provides the following solution:

[0014] According to a first aspect of the present invention, a PC5 communication field testing method for a vehicle-road-cloud integrated system is provided, the PC5 communication field testing method for a vehicle-road-cloud integrated system comprising:

[0015] The steps in the test preparation phase, the steps in the communication performance test, the steps in the message accuracy test, and the steps in the evaluation and judgment phase;

[0016] The steps in the test preparation phase include providing a runtime environment for the collection, comparison and analysis of test data, and completing the interconnection deployment and functional initialization of the vehicle, road and cloud test systems.

[0017] The steps of communication performance testing include: providing quantitative evidence for the overall system communication reliability; and evaluating the link layer capability and transmission quality of the RSU broadcasting messages to the test vehicle through the PC5 direct communication interface.

[0018] The steps for message accuracy testing include receiving messages in real time through in-vehicle equipment and comparing and analyzing them with the true data collected on site, so as to quantify the error of key information elements in the vehicle-road-cloud system and verify the functional consistency.

[0019] The evaluation and judgment phase includes the following steps: based on the data obtained from the communication performance test and message accuracy test phases, quantitative analysis is conducted on the operational quality of the tested RSU and the overall vehicle-road-cloud communication link, and a unified performance evaluation system is constructed.

[0020] Furthermore, the steps in the test preparation phase also include: the steps of test vehicle deployment and positioning synchronization, the steps of terminal perception and truth acquisition equipment configuration, and the steps of cloud data processing and collaborative platform construction.

[0021] Based on providing a runtime environment for the collection, comparison, and analysis of test data, the interconnection deployment and functional initialization of the vehicle, road, and cloud-based test systems were completed.

[0022] The steps for test vehicle deployment and location synchronization include:

[0023] Select representative road scenarios within the RSU coverage area being tested, and deploy test vehicles equipped with GNSS high-precision positioning systems.

[0024] The steps for configuring terminal sensing and truth acquisition devices include:

[0025] A C-V2X message acquisition terminal supporting the PC5 interface protocol stack was installed on the test vehicle, and a truth acquisition device independent of the system under test was configured, including a lidar, a high-definition camera and a traffic light status recognition module.

[0026] The steps involved in building a cloud-based data processing and collaboration platform include:

[0027] A test data processing platform is deployed on the cloud side, which is responsible for receiving data streams from vehicle-side data acquisition terminals and performing unified data parsing, error calculation, field comparison, and time series restoration analysis functions.

[0028] Furthermore, the communication performance testing steps also include: the maximum communication distance test, the effective coverage test, the packet loss rate and PRR test, and the end-to-end communication latency test.

[0029] Based on providing a quantitative basis for the overall system communication reliability, this study evaluates the link layer capability and transmission quality of the RSU broadcasting messages to the test vehicle via the PC5 direct communication interface.

[0030] The steps for testing the maximum communication distance include:

[0031] The test vehicle slowly drove away from the RSU under test from near to far, and with the support of the frequency sweeper and message acquisition terminal, the reception of RSU broadcast messages was recorded in real time.

[0032] The farthest straight-line distance from which a valid message can be identified is determined based on whether the message is completely interrupted or the reception quality falls below a threshold.

[0033] The steps for effective coverage testing include:

[0034] Within the standard communication radius set by the RSU, equally spaced sampling points were divided. The test vehicle slowly drove over the predetermined route and recorded the message reception and signal strength at each point.

[0035] The steps for packet loss rate and PRR testing include:

[0036] Sampling points are set with a fixed step size to collect continuous broadcast message data within that location. Missing frames are identified by analyzing the message sequence number field, and the PRR and packet loss rate are calculated.

[0037] The steps for end-to-end communication latency testing include:

[0038] Select the timestamped C-V2X message sent by the RSU, test the vehicle to parse the sending time, and calculate the difference between the sending time and the receiving time to obtain the end-to-end latency.

[0039] Furthermore, the message accuracy test steps also include: a step to verify the accuracy of MAP message fields and a step to verify the accuracy and synchronization of SPAT message fields;

[0040] By receiving messages in real time through onboard devices and comparing them with ground truth data collected on-site, the system achieves quantification of errors and verification of functional consistency for key information elements in the vehicle-road-cloud system.

[0041] The steps for verifying the accuracy of MAP message fields include:

[0042] Test the matching degree between various geospatial fields in the MAP message broadcast by RSU and real traffic scene data, and test the vehicle to traverse the target intersection in either coverage mode or fixed-point mode.

[0043] The steps for verifying the accuracy and synchronization of SPAT message fields include:

[0044] Verify that the SPAT message broadcast by the RSU is synchronized with the actual changes in the signal light status, and evaluate its timeliness and the correctness of the phase control logic.

[0045] Furthermore, the steps for verifying the accuracy of the MAP message fields also include: steps for checking the error between the reference coordinate system and the center point position, steps for checking the uniqueness of the node ID, steps for checking the accuracy of the road segment speed limit, width and centerline coordinates, and steps for checking the accuracy of the lane information structure.

[0046] Based on the matching degree between various geospatial fields in the MAP messages broadcast by the test RSU and real traffic scene data, the test vehicle traversed the target intersection in either coverage mode or fixed-point mode.

[0047] The steps to determine the positional error between the reference coordinate system and the center point include:

[0048] Calculate the distance between refPos in the MAP node and the intersection center position acquired via GNSS.

[0049] The steps to ensure node ID uniqueness include:

[0050] Parse the NodeID field of all nodes, count whether there are duplicate values, and verify the logical regularity of road segment division and the uniqueness within the region;

[0051] The steps for determining the speed limit, width, and centerline coordinate accuracy of a road segment include:

[0052] By combining on-site speed limit signs and data collected by laser rangefinders, and comparing the fields of speedLimits, linkWidth, and centerPoint, a threshold evaluation mechanism is used for evaluation.

[0053] The steps to ensure the accuracy of lane information structure include:

[0054] Check the uniqueness of LaneID, whether the number of lanes is consistent, the consistency of laneAttributes with the actual on-site signs, and collect laneWidth data for comparison with the actual lane width.

[0055] Furthermore, the steps for verifying the accuracy and synchronization of the SPAT message fields include:

[0056] Based on verifying whether the SPAT message broadcast by the RSU is synchronized with the actual changes in traffic light status, and evaluating its timeliness and the correctness of the phase control logic,

[0057] The steps involved in ensuring timestamp accuracy and delaying light color changes include:

[0058] Compare the SPAT.DSecond field with the traffic light change time detected by the vehicle truth device, and calculate the average delay and maximum error;

[0059] The steps for checking the consistency between the node ID and the MAP include:

[0060] Check whether the intersectionID in the SPAT message can be found in the corresponding MAP structure to verify whether the message matching and region binding logic is correct.

[0061] The steps for verifying phase ID consistency include:

[0062] Compare the phase definitions in SPAT and MAP to see if they exist and match, thus verifying the consistency of the control logic closed loop.

[0063] The steps for evaluating the accuracy of traffic light status fields include:

[0064] The vehicle detects the status of traffic lights using vision / sensors;

[0065] The steps for error assessment of the countdown field include:

[0066] Evaluate the synchronization between the countdown fields of likelyEndTime and nextStartTime and the actual signal change rhythm.

[0067] According to a second aspect of the present invention, a PC5 communication field testing device for a vehicle-road-cloud integrated system is provided, the PC5 communication field testing device for a vehicle-road-cloud integrated system comprising:

[0068] The test preparation phase module, communication performance test module, message accuracy test module, and evaluation and judgment phase module are included.

[0069] The test preparation phase module is used to provide a runtime environment for the collection, comparison and analysis of test data, and to complete the interconnection deployment and functional initialization of the vehicle, road and cloud test systems.

[0070] The communication performance testing module is used to provide quantitative evidence for the overall system communication reliability and to evaluate the link layer capability and transmission quality of the RSU broadcasting messages to the test vehicle through the PC5 direct communication interface.

[0071] The message accuracy testing module is used to receive messages in real time through the vehicle-mounted equipment and compare and analyze them with the true data collected on site, so as to realize the quantification of errors and the verification of functional consistency of key information elements in the vehicle-road-cloud system.

[0072] The evaluation and judgment phase module is used to quantitatively analyze the operational quality of the tested RSU and the overall vehicle-road-cloud communication link based on the data obtained from the communication performance test and message accuracy test phases, and to build a unified performance evaluation system.

[0073] According to a third aspect of the present invention, an electronic device is provided, comprising: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0074] The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the PC5 communication site testing method for the vehicle-road-cloud integrated system.

[0075] According to a fourth aspect of the present invention, a computer-readable storage medium is provided storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the PC5 communication site testing method for a vehicle-road-cloud integrated system.

[0076] According to a fifth aspect of the present invention, a testing platform is provided, comprising:

[0077] Electronic equipment for implementing the steps of the PC5 communication field testing method for the vehicle-road-cloud integrated system;

[0078] The processor runs a program, and when the program runs, it executes the steps of the PC5 communication field test method for the vehicle-road-cloud integrated system from the data output by the electronic device.

[0079] A storage medium for storing a program that, when running, executes the steps of the PC5 communication field test method for the vehicle-road-cloud integrated system based on data output from an electronic device.

[0080] The above solution achieves the following beneficial technical effects:

[0081] This application integrates communication performance testing (such as maximum communication distance, packet loss rate, latency, etc.) with message accuracy testing (such as MAP / SPAT message field consistency, time synchronization accuracy, etc.) into a unified testing process through the integrated design of testing methods, thereby realizing the collaborative verification of vehicle-road-cloud systems.

[0082] This application adopts an end-to-end closed-loop verification mechanism, which establishes a data pathway between the vehicle, road, and cloud by deploying test vehicles, roadside units (RSUs), and a cloud data processing platform, and achieves complete closed-loop verification from message sending, receiving, parsing to comparison.

[0083] This application achieves accurate comparison between message fields and real scene data by using high-precision ground truth acquisition and automatic comparison, utilizing ground truth acquisition equipment such as GNSS high-precision positioning system, lidar, and camera, combined with cloud-based automated analysis platform, thereby reducing manual intervention and improving testing efficiency and reliability.

[0084] This application adopts standardized and automated testing processes, designs standardized testing steps and evaluation indicators, supports automated testing in multiple scenarios (such as closed test areas and open roads), and ensures the repeatability and traceability of test results. Attached Figure Description

[0085] Figure 1 This is a flowchart of a PC5 communication field testing method for a vehicle-road-cloud integrated system provided by one or more embodiments of the present invention.

[0086] Figure 2 This is a structural diagram of a PC5 communication field test device for a vehicle-road-cloud integrated system provided by one or more embodiments of the present invention.

[0087] Figure 3 This is a schematic diagram of a PC5 field test framework for a vehicle-road-cloud integrated system provided in a specific embodiment of the present invention.

[0088] Figure 4 This is a block diagram of an electronic device structure for a PC5 communication field testing method for a vehicle-road-cloud integrated system, provided by one or more embodiments of the present invention. Detailed Implementation

[0089] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0090] Figure 1 This is a flowchart of a PC5 communication field testing method for a vehicle-road-cloud integrated system provided by one or more embodiments of the present invention.

[0091] like Figure 1 The PC5 communication field test method shown for the vehicle-road-cloud integrated system includes:

[0092] The steps are: A1 for the test preparation phase, A2 for the communication performance test, A3 for the message accuracy test, and A4 for the evaluation and judgment phase.

[0093] Step A1 in the test preparation phase includes providing a runtime environment for the collection, comparison and analysis of test data, and completing the interconnection deployment and functional initialization of the vehicle, road and cloud test systems.

[0094] Step A2 of the communication performance test includes providing a quantitative basis for the overall system communication reliability, evaluating the link layer capability and transmission quality of the RSU broadcasting messages to the test vehicle through the PC5 direct communication interface, including evaluation tests of communication range, stability, anti-interference capability and low latency characteristics.

[0095] Step A3 of the message accuracy test includes receiving messages in real time through the vehicle-mounted equipment and comparing and analyzing them with the true data collected on site. This enables the quantification of errors and verification of functional consistency of key information elements in the vehicle-road-cloud system, and is used to evaluate the functional performance of MAP and SPAT messages broadcast by the RSU through the PC5 interface in terms of structural integrity, field accuracy, and time synchronization.

[0096] Step A4 in the evaluation and judgment phase includes quantitatively analyzing the operational quality of the tested RSU and the overall vehicle-road-cloud communication link based on the data obtained from the communication performance test and message accuracy test phases, and constructing a unified performance evaluation system.

[0097] In this embodiment, the steps of the test preparation phase also include: the steps of test vehicle deployment and positioning synchronization, the steps of terminal perception and truth acquisition equipment configuration, and the steps of cloud data processing and collaborative platform construction.

[0098] Based on providing a runtime environment for the collection, comparison, and analysis of test data, the interconnection deployment and functional initialization of the vehicle, road, and cloud-based test systems were completed.

[0099] The steps for test vehicle deployment and location synchronization include:

[0100] Select representative road scenarios within the RSU coverage area being tested, and deploy test vehicles equipped with GNSS high-precision positioning systems.

[0101] The selected GNSS positioning system should have centimeter-level positioning accuracy and time synchronization capability, support RTK differential or PPP time synchronization mode, and ensure that the accuracy of subsequent message parsing and true time / location matching does not exceed ±1ms or ±10cm.

[0102] The steps for configuring terminal sensing and truth acquisition devices include:

[0103] A C-V2X message acquisition terminal supporting the PC5 interface protocol stack was installed on the test vehicle, and a truth acquisition device independent of the system under test was configured, including a lidar, a high-definition camera and a traffic light status recognition module.

[0104] This terminal supports decoding and timestamping of multiple message types and has GNSS time synchronization capabilities. Supported message types for decoding and timestamping include MAP, SPAT, BSM, and CAM. The ground truth device needs to be linked with the vehicle's driving status to collect reference physical information in real time, serving as the benchmark for subsequent functional field comparisons. Real-time collected reference physical information includes the timing of light color changes, lane boundaries, and speed.

[0105] The steps involved in building a cloud-based data processing and collaboration platform include:

[0106] A test data processing platform is deployed on the cloud side, which is responsible for receiving data streams from vehicle-side data acquisition terminals and performing unified data parsing, error calculation, field comparison, and time series restoration analysis functions.

[0107] The platform should support time alignment with GNSS base stations or cloud timing systems, possess multi-channel data synchronization and structured storage capabilities, and provide a graphical result output interface and test report generation tools. Based on the system's support for automatically assigning a unique identifier to each test task, data traceability and version control are achieved.

[0108] In this embodiment, the communication performance testing steps further include: the maximum communication distance test, the effective coverage test, the packet loss rate and PRR test, and the end-to-end communication latency test.

[0109] Based on providing a quantitative basis for the overall system communication reliability, this study evaluates the link layer capability and transmission quality of the RSU broadcasting messages to the test vehicle via the PC5 direct communication interface.

[0110] The steps for testing the maximum communication distance include:

[0111] The test vehicle slowly drove away from the RSU under test from near to far, and with the support of the frequency sweeper and message acquisition terminal, the reception of RSU broadcast messages was recorded in real time.

[0112] The farthest straight-line distance from which a valid message can be identified is determined based on whether the message is completely interrupted or the reception quality falls below a threshold. This threshold is used to measure the theoretical maximum power generation capacity and channel adaptability of the RSU in an unobstructed environment. The threshold includes RSRP < -108 dBm.

[0113] The steps for effective coverage testing include:

[0114] Within the standard communication radius set by the RSU, equally spaced sampling points are divided. The test vehicle slowly drives along a predetermined route, and the message reception and signal strength at each point are recorded. The standard communication radius includes 150 meters.

[0115] The effective coverage criterion is to use signal strength meeting a set threshold or message decoding success rate exceeding a threshold (e.g., PRR ≥ 90%). The percentage of valid coverage points is then calculated to determine the coverage rate. The set thresholds for signal strength meeting the threshold include RSRP ≥ -108dBm; the criteria for effective coverage include PRR ≥ 90%.

[0116] The steps for packet loss rate and PRR testing include:

[0117] Sampling points were set with a fixed step size. The test vehicle remained stationary at each sampling point for ≥100 seconds, and continuous broadcast message data was collected within that location. Missing frames were identified by analyzing the message sequence number field, and the PRR and packet loss rate were calculated. The fixed step size included 50m. Missing frames were identified by analyzing the message sequence number field, including MsgCount.

[0118] The steps for end-to-end communication latency testing include:

[0119] The test vehicle parses the transmission time of timestamped C-V2X messages sent by the selected RSU and calculates the difference between the transmission time and the reception time to obtain the end-to-end latency. Messages are continuously collected, and the average and maximum latency are calculated. The timestamped C-V2X messages sent by the selected RSU include the DSecond field; furthermore, when ≥100 messages are continuously collected, the average and maximum latency are calculated.

[0120] In this embodiment, the message accuracy test steps further include: a step of verifying the accuracy of MAP message fields and a step of verifying the accuracy and synchronization of SPAT message fields;

[0121] Based on real-time message reception via onboard equipment and comparative analysis with ground truth data collected on-site, the error quantification and functional consistency verification of key information elements in the vehicle-road-cloud system are achieved. This is used to evaluate the functional performance of MAP and SPAT messages broadcast by the RSU through the PC5 interface in terms of structural integrity, field accuracy, and time synchronization. The steps for verifying the accuracy of MAP message fields include:

[0122] The test focuses on the matching degree between various geospatial fields in the MAP messages broadcast by RSU and real traffic scene data. The test vehicle traverses the target intersection in either coverage mode or fixed-point mode.

[0123] The steps for verifying the accuracy and synchronization of SPAT message fields include:

[0124] The key focus is to verify whether the SPAT messages broadcast by the RSU are synchronized with the actual changes in the signal light status, and to evaluate their timeliness and the correctness of the phase control logic.

[0125] In this embodiment, the steps for verifying the accuracy of MAP message fields further include: steps for checking the error between the reference coordinate system and the center point position, steps for checking the uniqueness of the node ID, steps for checking the accuracy of the road segment speed limit, width and centerline coordinates, and steps for checking the accuracy of the lane information structure.

[0126] Based on the matching degree between various geospatial fields in the MAP messages broadcast by the test RSU and real traffic scene data, the test vehicle traversed the target intersection in either coverage mode or fixed-point mode.

[0127] The steps to determine the positional error between the reference coordinate system and the center point include:

[0128] The distance between the refPos (Position3D) in the MAP node and the intersection center position acquired via GNSS is calculated; an error ≤1m is considered acceptable. The GCJ-02 / WGS-84 coordinate transformation mechanism is used to support multi-source map comparison.

[0129] The steps to ensure node ID uniqueness include:

[0130] Parse the NodeID field of all nodes, count whether there are duplicate values, and verify the logical regularity of road segment division and the uniqueness within the region;

[0131] The steps for determining the speed limit, width, and centerline coordinate accuracy of a road segment include:

[0132] By combining on-site speed limit signs with data collected by laser rangefinders, and comparing the fields of speedLimits, linkWidth, and centerPoint, a threshold evaluation mechanism is used for assessment; for example, an error ≤10% or ≤50cm is considered qualified.

[0133] The steps to ensure the accuracy of lane information structure include:

[0134] Check the uniqueness of LaneID, whether the number of lanes is consistent, and the consistency between laneAttributes and the actual scene (e.g., the actual scene of left turn and straight ahead). Also, collect laneWidth and compare it with the actual lane width. The allowable error range is within ±0.5m.

[0135] This also includes a comparison of the consistency of lane turning / speed limit information:

[0136] Compare the maneuvers field with the actual markings / signs to confirm that the control logic matches; the speed limit field has an error of ≤5km / h compared with the on-site settings.

[0137] In this embodiment, the steps for verifying the accuracy and synchronization of SPAT message fields include:

[0138] Based on verifying whether the SPAT message broadcast by the RSU is synchronized with the actual traffic signal status change, and evaluating its timeliness and the correctness of the phase control logic,

[0139] The steps for verifying the accuracy of the timestamp and the delay of the traffic signal color change include:

[0140] Compare the SPAT.DSecond field with the traffic light change time detected by the in-vehicle truth device, and calculate the average delay and the maximum error; Target requirement: average error ≤ 300ms, maximum error ≤ 500ms.

[0141] The steps for checking the consistency between the node ID and the MAP include: <00002​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​The test preparation phase module, communication performance test module, message accuracy test module, and evaluation and judgment phase module are included.

[0152] The test preparation phase module is used to provide a runtime environment for the collection, comparison and analysis of test data, and to complete the interconnection deployment and functional initialization of the vehicle, road and cloud test systems.

[0153] The communication performance testing module is used to provide quantitative evidence for the overall system communication reliability and to evaluate the link layer capability and transmission quality of the RSU broadcasting messages to the test vehicle through the PC5 direct communication interface.

[0154] The message accuracy testing module is used to receive messages in real time through the vehicle-mounted equipment and compare and analyze them with the true data collected on site, so as to realize the quantification of errors and the verification of functional consistency of key information elements in the vehicle-road-cloud system.

[0155] The evaluation and judgment phase module is used to quantitatively analyze the operational quality of the tested RSU and the overall vehicle-road-cloud communication link based on the data obtained from the communication performance test and message accuracy test phases, and to build a unified performance evaluation system.

[0156] It is worth noting that although this system / device only discloses the test preparation phase module, communication performance test module, message accuracy test module, and evaluation and judgment phase module, it does not mean that this device is limited to the above-mentioned basic functional modules. On the contrary, what this invention intends to express is that, based on the above-mentioned basic functional modules, those skilled in the art can arbitrarily add one or more functional modules in combination with existing technology to form an infinite number of embodiments or technical solutions. That is to say, this system / device is open rather than closed. The fact that this embodiment only discloses a few basic functional modules should not be taken as a reason to believe that the scope of protection of the claims of this invention is limited to the above-disclosed basic functional modules.

[0157] In one specific embodiment, a PC5 field testing method for a vehicle-road-cloud integrated system is disclosed, addressing the following core technical issues:

[0158] (1) To achieve collaborative testing and unified evaluation of communication performance indicators (such as maximum communication distance, packet loss rate, latency, etc.) and message accuracy indicators (such as MAP / SPAT message field consistency, time synchronization accuracy, etc.);

[0159] (2) Establish a full-link data path between RSU, vehicle terminal and cloud control platform to realize end-to-end spatiotemporal consistency verification and functional closed-loop verification;

[0160] (3) Improve the standardization and automation of the testing process, reduce manual intervention, and improve testing efficiency and result repeatability;

[0161] (4) Adapt to the consistency testing requirements of various test scenarios (such as closed test areas and open urban roads).

[0162] Based on such Figure 3 The PC5 field testing framework for a vehicle-road-cloud integrated system shown in this embodiment includes the following steps:

[0163] S1: Test preparation phase (system setup), framework as follows Figure 1 As shown

[0164] The test preparation phase, as a fundamental step in the test method of this invention, aims to complete the connectivity deployment and functional initialization of the vehicle-road-cloud three-terminal test system, providing an accurate and efficient operating environment for subsequent test data collection, comparison, and analysis. This phase mainly includes the following key operations:

[0165] S11: Test vehicle deployment and location synchronization

[0166] Within the RSU coverage area under test, select representative road scenarios and deploy test vehicles equipped with GNSS high-precision positioning systems. The selected GNSS positioning system should have centimeter-level positioning accuracy and time synchronization capability, support RTK differential or PPP time synchronization, and ensure that the accuracy of subsequent message parsing and true time / location matching does not exceed ±1ms or ±10cm.

[0167] S12: Configuration of Terminal Sensing and Truth Acquisition Equipment

[0168] A C-V2X message acquisition terminal supporting the PC5 interface protocol stack was installed on the test vehicle, along with a truth acquisition device independent of the system under test, including but not limited to LiDAR, high-definition cameras, and traffic light status recognition modules. This terminal should support decoding and timestamp recording of multiple message types (such as MAP, SPAT, BSM, CAM, etc.) and have GNSS time synchronization capabilities. The truth acquisition device needs to be linked to the vehicle's driving status, collecting reference physical information in real time (such as the timing of light color changes, lane boundaries, speed, etc.) as a benchmark for subsequent functional field comparisons.

[0169] S13: Cloud Data Processing and Collaboration Platform Construction

[0170] A test data processing platform is deployed on the cloud side to receive data streams from vehicle-mounted acquisition terminals and perform unified analysis functions such as data parsing, error calculation, field comparison, and time series reconstruction. This platform should support time alignment with GNSS base stations or cloud timing systems, possess multi-channel data synchronization and structured storage capabilities, and provide a graphical result output interface and test report generation tools. The system should support automatically assigning a unique identifier to each test task to achieve data traceability and version control.

[0171] S2: Communication performance test (link capability verification)

[0172] The communication performance testing phase aims to evaluate the link layer capabilities and transmission quality of the RSU broadcasting messages to the test vehicle via the PC5 direct communication interface, providing a quantitative basis for the overall system communication reliability. The testing focuses on communication range, stability, anti-interference capabilities, and low-latency characteristics, and mainly includes the following sub-steps:

[0173] S21: Maximum Communication Distance Test

[0174] The test vehicle slowly moves away from the tested RSU from near to far, and with the support of a frequency sweeper and message acquisition terminal, the reception of RSU broadcast messages is recorded in real time. The farthest straight-line distance at which a valid message can be identified is determined, based on whether the message is completely interrupted or the reception quality drops below a threshold (e.g., RSRP < -108 dBm). This metric is used to measure the theoretical maximum power generation capacity and channel adaptability of the RSU in an unobstructed environment.

[0175] S22: Effective Coverage Test

[0176] Within the standard communication radius set by the RSU (e.g., 150 meters), equally spaced sampling points are divided. The test vehicle slowly drives along a predetermined route, recording the message reception and signal strength at each point. Effective coverage is determined by using a signal strength meeting a set threshold (e.g., RSRP ≥ -108 dBm) or a message decoding success rate exceeding a threshold (e.g., PRR ≥ 90%). The percentage of effective points is then calculated to determine the coverage rate.

[0177] S23: Packet Loss Rate and PRR Test

[0178] Sampling points are set at fixed step sizes (e.g., every 50m). The test vehicle remains stationary at each sampling point for ≥100 seconds, collecting continuous broadcast message data within that location. Missing frames are identified by analyzing the message sequence number field (e.g., MsgCount), and the message reception success rate (PRR) and packet loss rate are calculated per unit time.

[0179] S24: End-to-end communication latency test

[0180] Select timestamped C-V2X messages sent by the RSU (e.g., containing a DSecond field). Test the vehicle to parse the transmission time and calculate the difference between it and the reception time to obtain the end-to-end latency. Collect ≥100 messages continuously and calculate the average and maximum latency.

[0181] S3: Message Accuracy Test (Field Precision and Functional Consistency Verification)

[0182] This phase aims to systematically evaluate the performance of MAP (map information) and SPAT (traffic light information) messages broadcast by the RSU via the PC5 interface in terms of structural integrity, field accuracy, and time synchronization. Messages are received in real-time by onboard equipment and compared with high-precision "true value data" collected on-site to quantify errors and verify functional consistency of key information elements in the vehicle-road-cloud system. The test content is divided into the following sub-modules:

[0183] S31: Verification of the accuracy of MAP message fields

[0184] This module focuses on testing the matching degree between various geospatial fields in the MAP messages broadcast by the RSU and real traffic scene data. The test vehicle traverses the target intersection in either coverage mode or fixed-point mode.

[0185] S311: Error between reference coordinate system and center point position

[0186] The distance between the refPos (Position3D) in the MAP node and the intersection center position acquired via GNSS is calculated, and an error ≤1m is considered acceptable. The GCJ-02 / WGS-84 coordinate transformation mechanism is used to support multi-source map comparison.

[0187] S312: Node ID Uniqueness

[0188] Parse the NodeID field of all nodes, count whether there are duplicate values, and verify the logical regularity of road segment division and the uniqueness within the region.

[0189] S313: Speed ​​limits, width, and centerline coordinate accuracy of road sections

[0190] By combining on-site speed limit signs with data collected by laser rangefinders, and comparing fields such as speedLimits, linkWidth, and centerPoint, a threshold evaluation mechanism is adopted. An error of ≤10% or ≤50cm is considered as qualified.

[0191] S314: Accuracy of Lane Information Structure

[0192] Check the uniqueness of LaneID, whether the number of lanes is consistent, and the consistency of laneAttributes with the actual scene (such as left turn, straight) signs. Also, collect laneWidth data and compare it with the actual lane width. The allowable error range is within ±0.5m.

[0193] Consistency of lane turning / speed limit information

[0194] Compare the maneuvers field with the actual markings / signs to confirm that the control logic matches; the speed limit field has an error of ≤5km / h compared with the on-site settings.

[0195] S32: Verification of the accuracy and synchronization of SPAT message fields

[0196] This module focuses on verifying whether the SPAT messages broadcast by the RSU are synchronized with the actual changes in traffic light status, and evaluating their timeliness and the correctness of the phase control logic. Specific details are as follows:

[0197] S321: Timestamp accuracy and light color change delay

[0198] Compare the SPAT.DSecond field with the traffic light change times detected by the onboard ground truth device, and calculate the average delay and maximum error. Target requirements: average error ≤ 300ms, maximum error ≤ 500ms.

[0199] S322: Node ID and MAP Consistency Check

[0200] Check whether the intersectionID in the SPAT message can be found in the corresponding MAP structure to verify whether the message matching and region binding logic is correct.

[0201] S323: Phase ID Consistency Verification

[0202] Compare the phase definitions in SPAT and MAP to see if they exist and match, thus verifying the consistency of the control logic closed loop.

[0203] S324: Accuracy Assessment of Traffic Light Status Field

[0204] The vehicle detects the traffic light status via vision / sensors and compares it with the LightState field in SPAT within a 6-second time window. An accuracy rate of ≥95% is considered acceptable.

[0205] S325: Error Assessment for Countdown Field

[0206] Evaluate the synchronization between countdown fields such as likelyEndTime and nextStartTime and the actual rhythm of signal changes. Use linear interpolation for evaluation; a score of ≤300ms is considered perfect.

[0207] S4: Evaluation and Judgment Phase (Indicator Normalization and Performance Judgment)

[0208] This phase aims to quantitatively analyze the operational quality of the tested RSU and the overall vehicle-road-cloud communication link based on the data obtained from the communication performance test and message accuracy test phases, and to construct a unified performance evaluation system.

[0209] In another specific embodiment, in S21:

[0210] Key points for data acquisition: Continuously record RSSI / RSRP messages, location coordinates, and timestamps;

[0211] Evaluation criteria: Maximum communication distance should be ≥200m (adjustable according to the scenario);

[0212] Precautions: The test path should be unobstructed and free of reflections. The vehicle should travel at a constant speed of 20-30 km / h, and the gradual attenuation process should be recorded.

[0213] In another specific embodiment, in S22:

[0214] Formula: Coverage = (Number of valid points / Total number of sampling points) × 100%;

[0215] Target requirement: Coverage rate ≥ 99%;

[0216] Supporting mechanisms: The test vehicle should be equipped with an automatic point-marking mechanism that samples and records data every second, and calculates the spatial distribution map by combining it with GNSS coordinates.

[0217] In another specific embodiment, in S23:

[0218] Calculation method: Packet loss rate = Number of lost frames / Theoretical number of frames × 100%; PRR = 1 − Packet loss rate;

[0219] Target requirement: PRR ≥ 90%;

[0220] Clock alignment mechanism: GNSS timing is used for the accurate recording of message reception time to prevent timing deviations.

[0221] In another specific embodiment, in S24:

[0222] Time synchronization mechanism: Both the transmitting and receiving ends synchronize their time based on GNSS time;

[0223] Performance requirement: Average latency ≤ 30ms;

[0224] Anomaly handling mechanism: If a sudden change in frame delay of more than 100ms is detected, it will be automatically marked as an unstable link state.

[0225] Figure 4 This is a block diagram of an electronic device structure for a PC5 communication field testing method for a vehicle-road-cloud integrated system, provided by one or more embodiments of the present invention.

[0226] like Figure 4 As shown, this application provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0227] The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the PC5 communication field test method for the vehicle-road-cloud integrated system.

[0228] This application also provides a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of a PC5 communication field test method for a vehicle-road-cloud integrated system.

[0229] This application also provides a testing platform, including:

[0230] Electronic equipment, steps for implementing a PC5 communication field test method for a vehicle-road-cloud integrated system;

[0231] The processor runs a program that, when running, executes the steps of a PC5 communication field test method for a vehicle-road-cloud integrated system based on data output from electronic devices.

[0232] Storage medium for storing programs that, when running, execute steps of a PC5 communication field test method for a vehicle-road-cloud integrated system based on data output from electronic devices.

[0233] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0234] The electronic device comprises a hardware layer, an operating system layer running on top of the hardware layer, and an application layer running on the operating system. The hardware layer includes hardware such as a central processing unit (CPU), a memory management unit (MMU), and memory. The operating system can be any one or more computer operating systems that control the electronic device through processes, such as Linux, Unix, Android, iOS, or Windows. Furthermore, in this embodiment of the invention, the electronic device can be a smartphone, tablet computer, or other handheld device, or a desktop computer, portable computer, or other electronic device; there is no particular limitation in this embodiment.

[0235] In this embodiment of the invention, the executing entity for electronic device control can be an electronic device itself, or a functional module within an electronic device capable of calling and executing a program. The electronic device can obtain the firmware corresponding to the storage medium. This firmware is provided by the supplier, and different storage media may have the same or different firmware; no limitation is made here. After obtaining the firmware corresponding to the storage medium, the electronic device can write this firmware into the storage medium; specifically, it burns the firmware corresponding to the storage medium into the storage medium. The process of burning the firmware into the storage medium can be implemented using existing technology, and will not be elaborated upon in this embodiment of the invention.

[0236] Electronic devices can also obtain reset commands corresponding to the storage media. The reset commands corresponding to the storage media are provided by the supplier. The reset commands corresponding to different storage media can be the same or different, and no restrictions are imposed here.

[0237] At this time, the storage medium of the electronic device is a storage medium on which the corresponding firmware has been written. The electronic device can respond to the reset command corresponding to the storage medium on which the corresponding firmware has been written, thereby resetting the storage medium on which the corresponding firmware has been written according to the reset command. The process of resetting the storage medium according to the reset command can be implemented by existing technology and will not be described in detail in this embodiment of the invention.

[0238] For ease of description, the above devices are described separately by function as various units and modules. Of course, in implementing this application, the functions of each unit and module can be implemented in one or more software and / or hardware.

[0239] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined.

[0240] For the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0241] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0242] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A PC5 communication field testing method for a vehicle-road-cloud integrated system, characterized in that, The PC5 communication field testing method for the vehicle-road-cloud integrated system includes: The steps in the test preparation phase, the steps in the communication performance test, the steps in the message accuracy test, and the steps in the evaluation and judgment phase; The steps in the test preparation phase include providing a runtime environment for the collection, comparison and analysis of test data, and completing the interconnection deployment and functional initialization of the vehicle, road and cloud test systems. The steps of communication performance testing include: providing quantitative evidence for the overall system communication reliability; and evaluating the link layer capability and transmission quality of the RSU broadcasting messages to the test vehicle through the PC5 direct communication interface. The steps for message accuracy testing include receiving messages in real time through in-vehicle equipment and comparing and analyzing them with the true data collected on site, so as to quantify the error of key information elements in the vehicle-road-cloud system and verify the functional consistency. The evaluation and judgment phase includes the following steps: based on the data obtained from the communication performance test and message accuracy test phases, quantitative analysis is conducted on the operational quality of the tested RSU and the overall vehicle-road-cloud communication link, and a unified performance evaluation system is constructed.

2. The PC5 communication field testing method for a vehicle-road-cloud integrated system according to claim 1, characterized in that, The steps in the test preparation phase also include: the steps of test vehicle deployment and positioning synchronization, the steps of terminal perception and truth acquisition equipment configuration, and the steps of cloud data processing and collaborative platform construction. Based on providing an operating environment for the collection, comparison, and analysis of test data, the interconnection deployment and functional initialization of the vehicle, road, and cloud-based test systems were completed. The steps for test vehicle deployment and location synchronization include: Select representative road scenarios within the RSU coverage area being tested, and deploy test vehicles equipped with GNSS high-precision positioning systems. The steps for configuring terminal sensing and truth acquisition devices include: A C-V2X message acquisition terminal supporting the PC5 interface protocol stack was installed on the test vehicle, and a truth acquisition device independent of the system under test was configured, including a lidar, a high-definition camera and a traffic light status recognition module. The steps involved in building a cloud-based data processing and collaboration platform include: A test data processing platform is deployed on the cloud side, which is responsible for receiving data streams from vehicle-side data acquisition terminals and performing unified data parsing, error calculation, field comparison, and time series restoration analysis functions.

3. The PC5 communication field testing method for a vehicle-road-cloud integrated system according to claim 2, characterized in that, The steps of communication performance testing also include: the maximum communication distance test, the effective coverage test, the packet loss rate and PRR test, and the end-to-end communication latency test. Based on providing a quantitative basis for the overall system communication reliability, this study evaluates the link layer capability and transmission quality of the RSU broadcasting messages to the test vehicle via the PC5 direct communication interface. The steps for testing the maximum communication distance include: The test vehicle slowly drove away from the RSU under test from near to far, and with the support of the frequency sweeper and message acquisition terminal, the reception of RSU broadcast messages was recorded in real time. The farthest straight-line distance from which a valid message can be identified is determined based on whether the message is completely interrupted or the reception quality falls below a threshold. The steps for effective coverage testing include: Within the standard communication radius set by the RSU, equally spaced sampling points were divided. The test vehicle slowly drove over the predetermined route and recorded the message reception and signal strength at each point. The steps for packet loss rate and PRR testing include: Sampling points are set with a fixed step size to collect continuous broadcast message data within that location. Missing frames are identified by analyzing the message sequence number field, and the PRR and packet loss rate are calculated. The steps for end-to-end communication latency testing include: Select the timestamped C-V2X message sent by the RSU, test the vehicle to parse the sending time, and calculate the difference between the sending time and the receiving time to obtain the end-to-end latency.

4. The PC5 communication field testing method for a vehicle-road-cloud integrated system according to claim 3, characterized in that, The message accuracy test steps also include: steps for verifying the accuracy of MAP message fields and steps for verifying the accuracy and synchronization of SPAT message fields; By receiving messages in real time through onboard equipment and comparing them with ground truth data collected on-site, the error quantification and functional consistency verification of key information elements in the vehicle-road-cloud system can be achieved. The steps for verifying the accuracy of MAP message fields include: Test the matching degree between various geospatial fields in the MAP message broadcast by RSU and real traffic scene data, and test the vehicle to traverse the target intersection in either coverage mode or fixed-point mode. The steps for verifying the accuracy and synchronization of SPAT message fields include: Verify that the SPAT message broadcast by the RSU is synchronized with the actual changes in the signal light status, and evaluate its timeliness and the correctness of the phase control logic.

5. The PC5 communication field testing method for a vehicle-road-cloud integrated system according to claim 4, characterized in that, The steps for verifying the accuracy of the MAP message fields also include: steps for the reference coordinate system and center point position error, steps for the uniqueness of node ID, steps for the accuracy of road segment speed limit, width and center line coordinates, and steps for the accuracy of lane information structure. Based on the matching degree between various geospatial fields in the MAP messages broadcast by the test RSU and real traffic scene data, the test vehicle traversed the target intersection in either coverage mode or fixed-point mode. The steps to determine the positional error between the reference coordinate system and the center point include: Calculate the distance between refPos in the MAP node and the intersection center position acquired via GNSS. The steps to ensure node ID uniqueness include: Parse the NodeID field of all nodes, count whether there are duplicate values, and verify the logical regularity of road segment division and the uniqueness within the region; The steps for determining the speed limit, width, and centerline coordinate accuracy of a road segment include: By combining on-site speed limit signs and data collected by laser rangefinders, and comparing the fields of speedLimits, linkWidth, and centerPoint, a threshold evaluation mechanism is used for evaluation. The steps to ensure the accuracy of lane information structure include: Check the uniqueness of LaneID, whether the number of lanes is consistent, and the consistency between laneAttributes and the actual on-site signs. Also, collect laneWidth data and compare it with the actual lane width. The allowable error range is within the preset range.

6. The PC5 communication field test method for a vehicle-road-cloud integrated system according to claim 3 or 4, characterized in that, The steps for verifying the accuracy and synchronization of the SPAT message fields include: Based on verifying whether the SPAT message broadcast by the RSU is synchronized with the actual changes in traffic light status, and evaluating its timeliness and the correctness of the phase control logic, The steps involved in ensuring timestamp accuracy and delaying light color changes include: Compare the SPAT.DSecond field with the traffic light change time detected by the vehicle truth device, and calculate the average delay and maximum error; The steps for checking the consistency between node ID and MAP include: Check whether the intersectionID in the SPAT message can be found in the corresponding MAP structure to verify whether the message matching and region binding logic is correct. The steps for verifying phase ID consistency include: Compare the phase definitions in SPAT and MAP to see if they exist and match, and verify the consistency of the control logic closed loop. The steps for evaluating the accuracy of traffic light status fields include: The vehicle detects the status of traffic lights using vision / sensors; The steps for error assessment of the countdown field include: Evaluate the synchronization between the countdown fields of likelyEndTime and nextStartTime and the actual signal change rhythm.

7. A PC5 communication field testing device for a vehicle-road-cloud integrated system, characterized in that, The PC5 communication field test device for the vehicle-road-cloud integrated system includes: The test preparation phase module, communication performance test module, message accuracy test module, and evaluation and judgment phase module are included. The test preparation phase module is used to provide a runtime environment for the collection, comparison and analysis of test data, and to complete the interconnection deployment and functional initialization of the vehicle, road and cloud test systems. The communication performance testing module is used to provide quantitative evidence for the overall system communication reliability and to evaluate the link layer capability and transmission quality of the RSU broadcasting messages to the test vehicle through the PC5 direct communication interface. The message accuracy testing module is used to receive messages in real time through the vehicle-mounted equipment and compare and analyze them with the true data collected on site, so as to realize the quantification of errors and the verification of functional consistency of key information elements in the vehicle-road-cloud system. The evaluation and judgment phase module is used to quantitatively analyze the operational quality of the tested RSU and the overall vehicle-road-cloud communication link based on the data obtained from the communication performance test and message accuracy test phases, and to build a unified performance evaluation system.

8. An electronic device, characterized in that, include: The processor, communication interface, memory, and communication bus are connected, with the processor, communication interface, and memory communicating with each other via the communication bus. The memory stores a computer program that, when executed by a processor, causes the processor to perform the steps of the PC5 communication site testing method for a vehicle-road-cloud integrated system as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The device stores a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the PC5 communication field test method for a vehicle-road-cloud integrated system as described in any one of claims 1 to 6.

10. A testing platform, characterized in that, include: An electronic device for implementing the steps of the PC5 communication field testing method for a vehicle-road-cloud integrated system as described in any one of claims 1 to 6; The processor runs a program that, when the program is running, executes the steps of the PC5 communication field test method for a vehicle-road-cloud integrated system as described in any one of claims 1 to 6 from data output by the electronic device. A storage medium for storing a program that, when running, performs the steps of the PC5 communication field test method for a vehicle-road-cloud integrated system as described in any one of claims 1 to 6 on data output from an electronic device.

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