V2X message full link detection method and system

Abstract

The invention relates to the technical field of automatic driving, and discloses a V2X message full-link detection method. S100, signal quality detection is carried out on V2X messages broadcasted by RSUs of network intersections in a detection area, and a signal quality detection network intersection sample is constructed; s200, acquiring V2X information of each intersection in the signal quality detection network connection intersection sample; s300, performing message quality detection on the acquired V2X messages of the intersections according to a message quality detection standard; s400, performing intersection secondary sampling from network intersections of which the message quality meets the message quality detection standard to form a data quality verification intersection sample; and S500, performing data quality verification on the SPAT message and the MAP message of each intersection of the data quality verification intersection sample according to a data quality verification standard. According to the invention, a set of full-link message service detection method is provided based on a dependent link of a message, so that signal, message and data quality integrated full-link detection is realized, all network intersections in a detection area can be rapidly detected, and a fault intersection can be positioned.

Description

Technical Field

[0001] The present invention relates to the technical field of autonomous driving, and particularly to a method and system for full-link detection of V2X messages. Background Art

[0002] The distrust of autonomous vehicles in roadside V2X messages is mainly reflected in aspects such as data authenticity, integrity, source credibility, consistency, security threats, technical compatibility, information obsolescence, system reliability, and user behavior, which has become one of the main bottlenecks in the development of the vehicle-road collaborative industry. By taking effective technical measures and management strategies, the trust of vehicles in roadside V2X messages can be improved, thereby better supporting the development and application of autonomous driving technology. Therefore, in the construction of intelligent connected roads, the reliability detection of V2X messages is a key link.

[0003] Conventional V2X message detection includes signal quality detection, protocol consistency detection, message quality detection, and message data content verification, which are carried out in an independent manner for each type of detection. However, the problems existing in this method at present are as follows: In the early stage, the scale of intelligent connected road construction was small, mainly focusing on the intelligent connected construction of independent roads. Due to the small number of connected intersections and the single structure of the road environment, problem tracing was simple, and the detection methods of each detection type being independent and isolated could fully meet the actual needs in the early stage. However, as the intelligent connected construction began to develop towards the regional and urban levels, the number of connected intersections increased rapidly, the road environment became diversified, and problem tracing became more complex. Isolated detection methods could no longer meet the actual needs. Coupled with the fact that each detection was independently completed by different equipment or software, the detection time was long, seriously affecting the detection efficiency and increasing the detection cost.

[0004] Therefore, there is an urgent need for a new method that can quickly complete the reliability detection of V2X messages to adapt to the development trend of intelligent connected construction towards the regional and urban levels. Summary of the Invention

[0005] The present invention aims to provide a method and system for full-link detection of V2X messages to solve the technical problem of low efficiency of the existing V2X message detection method.

[0006] The basic solution provided by the present invention is: A method for full-link detection of V2X messages, the method comprising:

[0007] S100, performing signal quality detection on the V2X messages broadcast by each RSU at connected intersections in the detection area, and constructing a sample of connected intersections for signal quality detection;

[0008] S200, collecting the V2X messages broadcast by each RSU at the connected intersections in the sample of connected intersections for signal quality detection, including SPAT messages, MAP messages, RSI messages, and RSM messages;

[0009] S300, according to the message quality detection standard, perform message quality detection on the V2X messages broadcast by the RSU at each intersection collected;

[0010] S400, perform secondary sampling of intersections from the networked intersections whose message quality meets the message quality detection standard to form a data quality verification intersection sample;

[0011] S500, according to the data quality verification standard, perform data quality verification on the SPAT messages and MAP messages at each intersection of the data quality verification intersection sample.

[0012] Furthermore, the steps of S100 include: S101, measure the spectrum data of the V2X message coverage section in the detection area in a preset manner, and draw a signal strength road-level distribution map based on the spectrum data;

[0013] S102, taking the signal strength of the V2X message as the division basis, divide the intelligent networked road into normally covered intersections and weakly covered intersections; perform sampling on the normally covered intersections and weakly covered intersections in a preset proportion manner to construct a signal quality detection networked intersection sample.

[0014] Furthermore, in S102, the intersection with signal strength RSRP > -117dBm is a normally covered intersection, and the intersection with RSRP < -117dBm is a weakly covered intersection; the preset proportion manner is that the sampling proportion of normally covered intersections is 20 - 30%, and the sampling proportion of weakly covered intersections is 70 - 80%.

[0015] Furthermore, in S200, starting from the first distance from the RSU installation position, gradually shorten the distance in a preset step size, and sequentially select message collection points, and collect the RSU broadcast messages at each message collection point.

[0016] Furthermore, in S200, use an RSU broadcast message collection array to collect RSU broadcast messages, aggregate the messages collected by each unit of the array, divide them into 4 message subsets according to the message type, and perform deduplication according to the message count field and send timestamp field of the message frame.

[0017] Furthermore, in S400, the secondary sampling of intersections is to perform sampling on crossroads, T-shaped intersections and other types of intersections respectively in a preset proportion.

[0018] Furthermore, the data quality verification in S500 includes the verification of the signal light state change delay of the SPAT message, and the steps are as follows:

[0019] Collect the video of the signal light state change, and use an image recognition algorithm to retrieve the moment T0 when the signal light state changes in the video of the signal light state change, compare it with the data frame timestamp T1 of the signal light phase change in the SPAT message, calculate the delay time difference of the SPAT message, and verify the data quality of the SPAT message with the delay time difference between T0 and T1.

[0020] Furthermore, the data quality verification in S500 includes the lane center line accuracy verification of the MAP message. The steps are as follows:

[0021] Collect the lane center line reference line, sample the GPS position data of the sampling points from the MAP message, calculate the distance of the sampling points relative to the lane center line reference line, as well as the maximum distance and average distance, and verify the data quality of the MAP message.

[0022] The present invention is based on a V2X message full-link detection method, and also provides a V2X message full-link detection system to solve the technical problem of low efficiency of the existing V2X message detection method.

[0023] The system includes a detection vehicle and a host computer that are communicatively connected; the detection vehicle is equipped with detection devices, and the detection devices include a spectrum analyzer, a message acquisition device, a positioning device, and an image acquisition device; the host computer includes a database, a road-level distribution unit, and an analysis unit;

[0024] The spectrum analyzer is used to measure the spectrum data of the V2X message coverage section broadcast by the RSU at each networked intersection in the detection area and transmit it to the database;

[0025] The message acquisition device is used to collect the V2X messages broadcast by the RSU at each intersection in the signal quality detection networked intersection samples, including SPAT messages, MAP messages, RSI messages, and RSM messages, and transmit them to the database;

[0026] The positioning device is used to collect the center reference line of the lane where the detection vehicle is traveling and transmit it to the database;

[0027] The image acquisition device is used to collect the video of the signal light state change and transmit it to the database;

[0028] The road-level distribution unit is used to draw a signal strength road-level distribution map based on the spectrum data;

[0029] The analysis unit is configured to select a number of connected intersections in a preset manner on the signal strength road-level distribution map to construct a sample of connected intersections for signal quality detection; it is also configured to perform message quality detection on the V2X messages broadcast by the RSU at each intersection according to the message quality detection standard, and perform secondary sampling of the connected intersections from the connected intersections whose message quality meets the message quality detection standard to form a sample of intersections for data quality verification; it is further configured to perform data quality verification on the SPAT messages and MAP messages at each intersection in the sample of intersections for data quality verification according to the data quality verification standard.

[0030] Furthermore, the detection device further includes cameras installed on both sides of the detection vehicle, which are configured to collect image data of the lane lines on both sides and send it to the database; the analysis unit is further configured to calculate the distances between the left and right sides of the vehicle and the lane lines based on the image data of the lane lines on both sides to assist in keeping the vehicle driving in the middle of the lane.

[0031] The working principle and advantages of the present invention are as follows:

[0032] Conventional existing detection methods can meet the verification requirements in the early stage of intelligent network connection construction when the roads are simple and the number of intersections is small. Usually, after obtaining the corresponding data of each detection type through independent devices, the data is uniformly processed by the backend. Therefore, in the whole detection process, the detection processes of each detection type are independent of each other. The independent data acquisition process of each detection type only needs to start from the detection requirements of each detection type and does not need to consider the detection requirements of other detection types. However, with the development of intelligent network connection construction, the detection difficulty increases, the amount of data is large, and the data relationship is more complex. It is necessary to improve the conventional independent detection method. Since there are many parameters and limiting conditions involved in the detection processes of each detection type, the integration of each detection type is technically difficult.

[0033] In response to the challenges faced by those skilled in the art in the reliability detection of V2X messages at present, this solution deeply explores the internal correlation logic of V2X messages themselves and proposes a set of full-link message service detection methods. The entire detection process is no longer restricted by the continuous expansion of the scale of intelligent network connection roads and the continuous increase in the number of connected intersections. It can quickly complete the detection during the dynamic development process of intelligent network connection roads, which well conforms to the development trend of intelligent network connection construction towards the regional and urban levels.

[0034] Compared with the prior art, through comparative analysis, it is found in this solution that the signal quality of V2X messages affects the message quality, and reliable message quality is a prerequisite for data quality detection. Therefore, by ingeniously relying on the message dependency link, through designing a reasonable verification sequence and verification path, and connecting in series at intersections, an integrated full-link detection of signal quality, message quality, and data quality is achieved. At the same time, based on intersections, a non-balanced sampling method is adopted. The correlation between intersections and message quality problems is stronger, and the data value is higher, which can more accurately find problem intersections, achieve fault location, cooperate with the fault inspection form, clarify the fault type, quickly conduct troubleshooting, and improve the efficiency of inspection work. In addition, the system equipment of this solution can be obtained through a general equipment combination, which will significantly reduce equipment and operation and maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a flowchart showing a method for full-link detection of V2X messages provided by an embodiment of the present invention Figure 1 ;

[0036] Figure 2 is a flowchart showing a method for full-link detection of V2X messages provided by an embodiment of the present invention Figure 2 ;

[0037] Figure 3 is a road-level distribution diagram of V2X signal strength of a V2X message full-link detection system provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0038] The following is a more detailed description through specific embodiments:

[0039] The embodiment is basically as shown in the attached Figure 1 and Figure 2 : A V2X message full-link detection system that can implement a method for full-link detection of V2X messages.

[0040] The system includes a detection vehicle and a host computer that are communicatively connected; the detection vehicle is equipped with detection equipment, and the detection equipment includes a spectrum analyzer, a message acquisition device, a positioning device, and an image acquisition device; the host computer includes a database, a road-level distribution unit, and an analysis unit; the data collected by the detection equipment is transmitted to the database, and the road-level distribution unit and the analysis unit retrieve the corresponding data in the database for processing.

[0041] The spectrum analyzer is used to measure the spectrum data of the V2X message coverage section and transmit it to the database. The working frequency band of the spectrum analyzer covers 5905 - 5925 MHz, and the antenna is installed directly above the working vehicle, keeping the working vehicle driving in the middle of the lane. The road-level distribution unit is used to draw a road-level distribution map of signal strength based on the spectrum data. The analysis unit is used to select a number of connected intersections in a preset manner on the road-level distribution map of signal strength to construct a sample of connected intersections for signal quality detection.

[0042] The message acquisition device (in-vehicle OBU) is installed conventionally. The OBU antenna (PC5 signal receiving antenna) is installed directly above the vehicle, keeping the main direction of the antenna consistent with the driving direction of the vehicle and facing the RSU of the test intersection. It is used to collect the RSU broadcast messages of each intersection in the sample of connected intersections for signal quality detection and transmit them to the database. Among them, the intersection RSU broadcast messages include SPAT messages, MAP messages, RSI messages, and RSM messages, four message types. The analysis unit is also used to perform message quality detection on the RSU broadcast messages of each intersection according to the message quality detection standard, and conduct secondary sampling of connected intersections from the connected intersections whose message quality meets the message quality detection standard to form a sample of connected intersections for data quality verification.

[0043] The image acquisition device is used to record the video of the signal light state change and transmit it to the database. A high-speed camera can be used, with a frame rate greater than 100 frames per second. It is installed directly in front of the roof to ensure that the camera's field of view has no obstacles and can record the clear process of signal light state switching. In addition, cameras are installed on both sides of the detection vehicle to collect the image data of the lane lines on both sides and transmit it to the database.

[0044] The positioning device is used to collect the reference line of the center line of the driving lane and transmit it to the database. An RTK high-precision positioning device can be used, and the satellite antenna is installed at the geometric center point of the vehicle.

[0045] The analysis unit is also used to perform data quality verification on the SPAT messages and MAP messages of each intersection in the sample of connected intersections for data quality verification according to the data quality verification standard. It is also used to calculate the distances between the left and right sides of the vehicle and the lane lines based on the image data of the lane lines on both sides to assist in keeping the vehicle driving in the middle of the lane, that is, during the vehicle driving process, the distances between the left and right sides of the vehicle relative to the lane lines on both sides are calculated in real time to keep the distances from both sides of the lane lines equal.

[0046] The data quality verification is specifically as follows:

[0047] Use an image recognition algorithm to retrieve the moment T0 when the signal state changes in the video of the signal light state change, compare it with the moment T1 when the signal state changes in the SPAT message, calculate the delay time difference of the SPAT message, and verify the data quality of the SPAT message with the delay time difference between moment T0 and T1.

[0048] Retrieve the sampling point closest to the lane center reference line from the MAP message as the target sampling point, calculate the distance deviation of the target sampling point relative to the lane center reference line, and statistically calculate the average deviation value and the maximum deviation value. Comprehensively identify the accuracy of the map data with the average deviation value and the maximum deviation value, so as to verify the data quality of the MAP message.

[0049] The use of the above system implements a full-link detection method for V2X messages. The method includes the following steps:

[0050] S100, perform signal quality detection on the V2X messages broadcast by each RSU at the networked intersections in the detection area, and construct a sample of networked intersections for signal quality detection;

[0051] Specifically, S101, measure the spectrum data of the road section covered by the V2X message in the detection area in a preset manner, and draw a road-level distribution map of the signal strength based on the spectrum data, as Figure 3 shown.

[0052] The preset manner includes surveying the construction design drawings of the networked road project and the RSU installation intersections (networked intersections) in the intelligent networked area, formulating a detection route that covers all networked intersections.

[0053] The detection vehicle drives slowly along the formulated detection route, passing each road section more than three times, and the driving path covers each lane of the intersection. At the same time, turn on the spectrum detection function of the spectrum analyzer and the RTK high-precision positioning function of the positioning device, and the data update frequency is 10HZ. The upper computer synchronizes and aggregates the spectrum detection data and the high-precision positioning data based on the time stamp to form the spectrum data of each sampling point. The detection frequency band is 5905MHz to 5925MHz, the frequency band is reasonable, and the acquired data meets the quantity and quality requirements.

[0054] Perform grid processing on the networked roads in the detection area. The scale of each grid can be preferably 5 meters. Statistically calculate the signal strength of each grid, retrieve all the sampling points within the grid, calculate the signal strength of the sampling point using the spectrum data of each sampling point, and take the average value of the signal strengths of all the sampling points in the grid to obtain the signal strength of the grid. Calculate the signal strengths of all grids and obtain the road-level distribution map of the signal strength according to the existing mapping technology, as Figure 3 shown, where the shade of the gray color represents the strength of the signal. The area within the obvious circle has a very strong signal strength, and the specific value can be viewed by selecting in the background.

[0055] S102, divide the intelligent connected roads into normally covered intersections and weakly covered intersections based on the signal strength of V2X messages; sample the normally covered intersections and weakly covered intersections in a preset proportion manner to construct a sample of connected intersections for signal quality detection.

[0056] Among them, 150M is the minimum effective communication distance of the RSU broadcast message required by the standard. Along each incoming road of the intersection, retrieve the grid at a distance of 150M ± 5M from the RSU installation location, calculate the average signal strength of each incoming road grid area, and select the road with the minimum average value as the alternative detection section. Divide the alternative detection section into normally covered intersections and weakly covered intersections according to the coverage signal strength. The division can be made by selecting the signal strength RSRP of -117dBm. Intersections with RSRP > -117dBm are normally covered intersections, and intersections with RSRP < -117dBm are weakly covered intersections. Statistically analyze the grids of each intersection. If the signal strength of 50% of the intersections is lower than -117dBm, it is regarded as a weakly signal covered intersection, and it is necessary to check whether there are obstacles near the RSU blocking the signal propagation. If there are, after removing the obstacles, re-acquire to obtain valid intersection data.

[0057] The preset proportion method is that the sampling proportion of normally covered intersections is 20 - 30%, and the sampling proportion of weakly covered intersections is 70 - 80%. Preferably, the sampling proportion of normally covered intersections is 20%, and the sampling proportion of weakly covered intersections is 80%. Using an unbalanced sampling method can more accurately find problem intersections and improve the inspection work efficiency.

[0058] S200, collect the V2X messages broadcast by the RSU at each intersection in the sample of connected intersections for signal quality detection, including SPAT messages, MAP messages, RSI messages, and RSM messages.

[0059] Specifically, the detection vehicle drives slowly along the specified detection route, and the driving direction is the same as the traffic flow direction. Each lane is passed through more than three times, and the driving path covers each lane of the intersection. Through the message collection device (in-vehicle OBU) carried, collect the RSU broadcast messages at different distances from the RSU. It can be selected to start from the first distance from the RSU installation location and gradually shorten the distance at a preset step length, and sequentially select the message collection points. The first distance can be selected as 300m, and the preset step length can be selected as 10m. With such data selection, an appropriate number of message collection points can be obtained.

[0060] To minimize the unreliability of the message quality detection results caused by the detection equipment, an RSU broadcast message acquisition array is used to collect RSU broadcast messages, avoiding the loss of messages by a single collector, which may lead to inaccurate detection results; the messages collected by each unit of the aggregation array are divided into 4 message subsets according to the message type, and duplicate messages are removed according to the message count field and the transmission timestamp field of the message frame, avoiding duplicate counting of messages.

[0061] S300, according to the message quality detection standard, perform message quality detection on the V2X messages broadcast by each intersection RSU collected;

[0062] Detect the quality of each intersection V2X message (including 4 types of messages: SPAT, MAP, RSI, RSM) in the detection signal quality detection networked intersection sample. The detection indicators for each message quality are shown in Table 1.

[0063] Table 1 Message Quality Detection Indicators

[0064] Message type Detection index SPAT message Broadcast frequency, effective communication distance MAP message Broadcast frequency, effective communication distance RSI message Broadcast frequency, effective communication distance, packet loss rate RSM message Broadcast frequency, effective communication distance, packet loss rate

[0065] To detect whether various indicators of the message meet the standard requirements, collect RSU broadcast messages at the message collection point, and calculate the broadcast frequency and packet loss rate indicators. Among the sampling points where both the packet loss rate and the broadcast frequency meet the standard requirements, select the sampling point with the maximum distance from the RSU. This distance is the maximum communication distance of the detected message. If all message quality detection indicators meet the requirements, the message quality is considered qualified. The indicator standard requirements for the 4 types of messages are shown in Table 2:

[0066] Table 2 Corresponding Standard Values of Message Quality Detection Indicators

[0067] Message type Broadcast frequency Packet loss rate Effective communication distance SPAT >2HZ None >150M MAP >1HZ None >150M RSI >1HZ <10％ >150M RSM >10HZ <10％ >150M

[0068] S400, perform secondary sampling of intersections from the networked intersections whose message quality meets the message quality detection standard to form a data quality verification intersection sample; specifically, the secondary sampling of intersections is to sample 20% from each of the crossroads, T-shaped intersections, and other types of intersections to ensure the diversity of intersection types and avoid a single intersection, so as to ensure the accuracy of the detection results.

[0069] S500, according to the data quality verification standard, perform data quality verification on the SPAT messages and MAP messages of each intersection in the data quality verification intersection sample. Only perform data quality verification on the SPAT messages and MAP messages to meet the data quality verification requirements of the networked signal control messages. The data items for verifying each type of message are shown in Table 3.

[0070] Table 3 Message Data Quality Detection Indicators

[0071]

[0072] Data quality verification includes:

[0073] S501. The verification steps for the signal light state change delay of the SPAT message are as follows: Collect the video of the signal light state change, and use an image recognition algorithm to retrieve the moment T0 when the signal light state changes in the video of the signal light state change. Compare it with the timestamp T1 of the data frame when the signal light phase changes in the SPAT message, and calculate the delay time difference of the SPAT message. Verify the data quality of the SPAT message with the delay time difference between moment T0 and T1.

[0074] S502. Verification of the lane center line accuracy of the MAP message. The vehicle is detected to pass through each section of the intersection in sequence, and it keeps driving in the middle of the lane. For the automatic detection of map data, collect the reference line of the lane center line, retrieve the sampling point closest to the lane center reference line from the MAP message as the target sampling point, analyze the GPS position data of the target sampling point, calculate its distance from the lane center reference line, and statistically calculate the average distance and the maximum distance to measure the accuracy of the map data, thereby verifying the data quality of the MAP message.

[0075] Analysis of the detection results: After all detections are completed, check the problematic intersections as shown in Table 4, which can achieve problem traceability and positioning, quickly check whether there are common problems, and uniformly process them to improve the problem handling efficiency. At the same time, it can also give play to the utilization value of the data in the detection process and provide strong support for all-round problem analysis.

[0076] Table 4 Detection result reference table

[0077]

[0078] A V2X message full-link detection method and system provided in this embodiment propose a set of full-link message service detection methods by utilizing the inherent correlation logic of V2X messages themselves to adapt to the development of intelligent network connection construction. Through comparative analysis, it is found that the signal quality of V2X messages affects the message quality, and reliable message quality is a prerequisite for data quality detection. Therefore, based on the dependency link of messages, the internal relationship is deeply explored, and by designing a reasonable verification sequence and verification path, and adopting a scientific sampling method at intersections, full-link detection covering the signal layer, message layer, and data layer is achieved, accurately positioning the reasons for unreliable V2X message services. The one-stop measurement of V2X messages greatly improves the detection efficiency of the test work. The entire detection process is no longer restricted by the continuous expansion of the scale of intelligent network-connected roads and the increasing number of network-connected intersections, and can be quickly completed during the dynamic development of intelligent network-connected roads, well fitting the development trend of intelligent network connection construction towards the regional and urban levels. At the same time, the sampling method based on the quality of intersections is more likely to discover problematic intersections, enabling fault location, and cooperating with the formulation of corresponding defect cause investigation tables and solutions, facilitating the rapid positioning of the main reasons for RSU message service defects at intersections and proposing corresponding improvement measures. The fault types are clear, the correlation between intersections and message quality problems is stronger, and the data value is higher. In addition, the system equipment of this solution can be obtained through a general equipment combination, which will significantly reduce equipment and operation and maintenance costs.

[0079] The above are only embodiments of the present invention. Specific structures and common knowledge such as characteristics well known in the art are not described in detail here. Those of ordinary skill in the art know all the common technical knowledge in the technical field to which the invention belongs before the application date or priority date, can know all the existing technologies in this field, and have the ability to apply conventional experimental means before this date. Those of ordinary skill in the art can, under the inspiration given in this application, complete and implement this solution in combination with their own abilities. Some typical well-known structures or well-known methods should not become obstacles for those of ordinary skill in the art to implement this application. It should be noted that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can still be made, and these should also be regarded as the protection scope of the present invention, and these will not affect the implementation effect of the present invention and the practicality of the patent.

Claims

1. A V2X message full-link detection method, characterized in that: The method comprises: S100, performing signal quality detection on the V2X messages broadcast by the RSU at each networked intersection in the detection area, and constructing a signal quality detection networked intersection sample; S200, collecting V2X messages broadcast by RSU at each intersection in the signal quality detection network intersection sample, including SPAT messages, MAP messages, RSI messages and RSM messages; S300, performing message quality detection on the V2X messages of the RSU broadcast messages collected at each intersection according to the message quality detection standard; S400, performing secondary sampling of intersections from the networked intersections where the message quality meets the message quality detection standard, to form a data quality verification intersection sample; S500: Perform data quality verification on the SPAT message and the MAP message of each intersection of the data quality verification intersection sample according to the data quality verification standard.

2. A V2X message full-link detection method according to claim 1, characterized in that: The steps of S100 include: S101, measuring spectrum data of a road section covered by a V2X message in a detection area in a preset manner, and drawing a road-level distribution map of signal strength based on the spectrum data; S102, dividing the intelligent connected roads into normal coverage intersections and weak coverage intersections based on the signal strength of the V2X message; sampling the normal coverage intersections and the weak coverage intersections according to a preset ratio to construct a signal quality detection network intersection sample.

3. A V2X message full-link detection method according to claim 2, characterized in that: In S102, the intersection with signal strength RSRP>-117dBm is a normal coverage intersection, and the intersection with RSRP<-117dBm is a weak coverage intersection; The preset ratio method is that the sampling ratio of normal coverage intersections is 20-30%, and the sampling ratio of weak coverage intersections is 70-80%.

4. A V2X message full-link detection method according to claim 1, characterized in that: In S200, starting from a first distance from the RSU installation position, the distance is gradually shortened with a preset step length, message collection points are selected in sequence, and RSU broadcast messages are collected at each message collection point.

5. A V2X message full-link detection method according to claim 1, characterized in that: In S200, the RSU broadcast message collection array is used to collect the V2X messages broadcast by the RSU, and the messages collected by each unit of the aggregation array are divided into 4 message subsets according to the message type, and deduplication is performed according to the message count field and the sending timestamp field of the message frame.

6. A V2X message full link detection method according to claim 1, characterized in that: In S400, the secondary sampling of intersections is to sample crossroads, T-junctions and other types of intersections respectively at a preset ratio.

7. A V2X message full-link detection method according to claim 1, characterized in that: The data quality verification in S500 includes the signal light state change delay verification of the SPAT message, and the steps are as follows: Collect the video of the traffic light state change, and use the image recognition algorithm to retrieve the time T0 when the light state changes in the traffic light state change video, compare it with the data frame timestamp T1 when the traffic light phase changes in the SPAT message, calculate the delay time difference of the SPAT message, and verify the data quality of the SPAT message with the delay time difference between T0 and T1.

8. A V2X message full-link detection method according to claim 1, characterized in that: The data quality verification in S500 includes the lane centerline accuracy verification of the MAP message, and the steps are as follows: Collect the lane centerline reference line, calculate the distance of the sampling point relative to the lane centerline reference line, as well as the maximum distance and average distance from the GPS position data of the sampling point in the MAP message, and verify the data quality of the MAP message.

9. A V2X message full-link detection system, characterized in that: A V2X message full-link detection method according to any one of claims 1 to 8 is applied; the system comprises a detection vehicle and a host computer in communication connection; the detection vehicle is equipped with a detection device, the detection device comprises a frequency sweeper, a message collection device, a positioning device and an image collection device; the host computer comprises a database, a road-level distribution unit and an analysis unit; The frequency scanner is used to measure the spectrum data of the road section covered by the V2X message broadcast by the RSU at each networked intersection in the detection area, and transmit it to the database; The message collection device is used to collect V2X messages broadcast by RSU at each intersection in the signal quality detection network intersection sample, including SPAT messages, MAP messages, RSI messages and RSM messages, and transmit them to the database; The positioning device is used to collect and detect the center reference line of the vehicle's driving lane and transmit it to the database; The image acquisition device is used to collect the video of the light state change of the signal light and transmit it to the database; The road level distribution unit is used to draw a signal strength road level distribution map based on the spectrum data; The analysis unit is used to select a number of networked intersections in a preset manner on the signal strength road-level distribution map to construct a signal quality detection networked intersection sample; it is also used to perform message quality detection on the V2X messages broadcast by the RSU at each intersection according to the message quality detection standard, and perform secondary sampling of networked intersections from the networked intersections whose message quality meets the message quality detection standard to form a data quality verification intersection sample; It is also used to perform data quality verification on the SPAT message and MAP message at each intersection of the data quality verification intersection sample according to the data quality verification standard.

10. A V2X message full-link detection system according to claim 9, characterized in that: The detection equipment also includes cameras installed on both sides of the detection vehicle, which are used to collect lane line image data on both sides and send them to the database; the analysis unit is also used to calculate the distance between the left and right sides of the vehicle and the lane lines based on the lane line image data on both sides, so as to assist in keeping the vehicle in the middle of the lane.

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