V2X-based traffic situation early warning method, system and device

Abstract

The invention provides a V2X-based traffic situation early warning method, system and device, and the method comprises the steps: obtaining traffic data collected by a plurality of data sources, and carrying out the preprocessing of the received traffic data; corresponding traffic indexes are determined according to the preprocessed traffic data, and the traffic indexes at least comprise the vehicle pedestrian flow, the vehicle average speed and the lane traffic situation; wherein the lane traffic situation at least comprises a corresponding grade representing a road congestion condition in a preset time period, and the corresponding grade at least comprises one of unblocked, mild congestion, moderate congestion and serious congestion; and evaluating a corresponding traffic situation condition according to the traffic index, and if the traffic situation condition is abnormal, outputting corresponding risk early warning information. Through the real-time data monitoring technology, the urban traffic management efficiency is improved, the traffic jam problem is relieved, and the comprehensiveness and accuracy of information are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of real-time analysis and early warning of urban traffic flow, and in particular to a V2X-based traffic situation early warning method, system and device. Background Art

[0002] In response to the challenge of rapid growth of urban traffic data, the construction of vehicle-road-cloud integration faces the following major technical problems: Data processing and storage challenges: With the surge in the amount of urban traffic data, traditional data processing and storage methods are difficult to meet the needs of real-time and high efficiency. This requires that the construction of vehicle-road-cloud integration must adopt more advanced data processing technologies, such as cloud computing and edge computing, as well as more efficient data storage solutions to achieve rapid data processing and analysis. Data quality and timeliness: The differences and uncertainties of different data sources may affect the accuracy and practicality of data. The integration of vehicle-road-cloud needs to ensure the comprehensiveness and accuracy of data, which involves the optimization and coordination of multiple links such as data collection, transmission, and processing. Computing resource and storage space consumption: Big data processing and analysis require a large amount of computing resources and storage space. The construction of vehicle-road-cloud integration must consider how to efficiently use computing resources and how to expand storage space to adapt to the growing amount of data. Low latency and high reliability requirements: The vehicle-road-cloud integration system needs to realize real-time data interaction between vehicles, roadside infrastructure, and cloud platforms, which requires the system to have the characteristics of low latency and high reliability. For example, the deterministic low latency characteristics of the 5G-A network support latency of less than 20ms on all road sections, meeting the data transmission requirements of high-level autonomous driving technology.

[0003] Traditional traffic flow prediction methods are mainly based on mathematical statistics and time series analysis, including linear regression, exponential smoothing, grey model, etc. These methods usually rely on historical data and assumptions of basic laws. Although they can predict traffic flow to a certain extent, they are limited by data volume and feature extraction. Summary of the invention

[0004] The purpose of the present invention is to propose a V2X-based traffic situation warning method, system and device to solve the technical problem of how to achieve real-time analysis and warning of urban traffic flow.

[0005] On the one hand, a V2X-based traffic situation warning method is provided, comprising:

[0006] Acquire traffic data collected from multiple data sources and pre-process the received traffic data; wherein the traffic data at least includes traffic flow, vehicle speed and pedestrian flow;

[0007] Determine corresponding traffic indicators according to the preprocessed traffic data, wherein the traffic indicators at least include vehicle and pedestrian flow, average vehicle speed, and lane traffic situation; wherein the lane traffic situation at least includes a corresponding level indicating road congestion within a preset time period, and the corresponding level includes at least one of unblocked, lightly congested, moderately congested, and severely congested;

[0008] The corresponding traffic situation is evaluated according to the traffic indicators, and if the traffic situation is abnormal, the corresponding risk warning information is output.

[0009] Preferably, the data source includes at least one or more of a road test sensing device, a vehicle-mounted terminal, a GPS device, and a mobile application.

[0010] Preferably, the preprocessing of the received traffic data includes:

[0011] Identify the perception data output by the drive test perception device, and determine the data speed when the perception data is collected, the corresponding perception object in the perception data, and the acceleration of the perception object in the time series;

[0012] If the data speed of a piece of perception data during collection exceeds a preset speed limit threshold, the speed of the perception data is determined to be abnormal; wherein the data speed is the speed at which the traffic data was collected;

[0013] If the difference between the acceleration of the same perceived object at a certain moment and the three most recent accelerations at that moment exceeds a preset acceleration threshold, the perceived data is judged to be abnormal.

[0014] Preferably, it also includes:

[0015] When the sensed data is determined to be abnormal, the longitude and latitude position of the sensed object at the abnormal moment and the longitude and latitude position at the moment before the abnormal moment are identified and the distance between the two moments is determined;

[0016] The corresponding average speed is calculated according to the distance between the two moments, and the acceleration at the abnormal moment is replaced by the average speed.

[0017] Preferably, determining the corresponding traffic index according to the preprocessed traffic data includes:

[0018] Counting the number of vehicles and pedestrians at the corresponding traffic intersection within a preset time period, and outputting the number of vehicles and pedestrians as vehicle and pedestrian flow;

[0019] Extract the speed information of all vehicles within a preset time period and calculate the average speed of the corresponding vehicles.

[0020] Preferably, determining the corresponding traffic index according to the preprocessed traffic data further includes:

[0021] Determine the number of vehicles per unit length in the lane according to the real-time vehicle and pedestrian flow;

[0022] The lane traffic situation in the lane is determined based on the number of vehicles per unit length in the lane and the average speed of the vehicles.

[0023] Preferably, determining the lane traffic situation in the lane includes:

[0024] When the number of vehicles per unit length in the lane is less than a preset first number threshold and the average speed of the vehicles is greater than a preset first speed threshold, it is determined that the lane traffic situation in the lane is unblocked;

[0025] When the number of vehicles per unit length in the lane is greater than or equal to a preset first number threshold and less than a preset second number threshold, and the average speed of the vehicles is less than or equal to a preset first speed threshold and greater than a preset second speed threshold, it is determined that the lane traffic situation in the lane is slightly congested;

[0026] When the number of vehicles per unit length in the lane is greater than or equal to a preset second number threshold and less than a preset third number threshold and the average speed of the vehicles is less than a preset second speed threshold, it is determined that the lane traffic situation in the lane is slightly congested;

[0027] When the number of vehicles per unit length in the lane is greater than or equal to a preset third number threshold and the average speed of the vehicles is less than a preset third speed threshold, it is determined that the lane traffic situation in the lane is slightly congested.

[0028] Preferably, the evaluating the corresponding traffic situation according to the traffic index includes:

[0029] Determine the corresponding traffic situation according to the traffic indicators within the preset first time period threshold;

[0030] If the lane traffic situation of all lanes is not in a serious congestion state or the lane traffic situation of a lane changes from a serious congestion state to a non-severe congestion state within the first time period threshold, it is determined that the corresponding traffic situation is normal;

[0031] If the traffic situation of a lane has been in a serious congestion state within the first time period threshold, it is determined that the traffic situation is abnormal.

[0032] On the other hand, a V2X-based traffic situation warning system is also provided to implement the V2X-based traffic situation warning method, comprising:

[0033] A data acquisition module, used to acquire traffic data collected from multiple data sources and pre-process the received traffic data; wherein the traffic data at least includes traffic flow, vehicle speed and pedestrian flow;

[0034] A data processing module, used to determine corresponding traffic indicators according to the pre-processed traffic data, wherein the traffic indicators at least include vehicle and pedestrian flow, average vehicle speed and lane traffic situation; wherein the lane traffic situation at least includes a corresponding level indicating road congestion within a preset time period, and the corresponding level includes at least one of unblocked, lightly congested, moderately congested and severely congested;

[0035] It is also used to evaluate the corresponding traffic situation according to the traffic indicators, and if the traffic situation is abnormal, output corresponding risk warning information.

[0036] On the other hand, a device is also provided for performing risk warning through the V2X-based traffic situation warning method.

[0037] In summary, the implementation of the embodiments of the present invention has the following beneficial effects:

[0038] The V2X-based traffic situation warning method, system and device provided by the present invention improves the efficiency of urban traffic management and alleviates traffic congestion through real-time data monitoring technology. It relies on multi-source data collection and uses multiple devices such as road test sensing equipment, vehicle terminals, GPS devices and mobile applications to collect important data such as traffic flow, vehicle speed, pedestrian flow, etc. in real time to ensure the comprehensiveness and accuracy of the information. It also conducts real-time traffic flow analysis based on the collected data to improve traffic management efficiency and reduce congestion and accident rates. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, without paying creative labor, other drawings obtained based on these drawings still belong to the scope of the present invention.

[0040] Figure 1 Schematic diagram of the main process of a V2X-based traffic situation warning method in an embodiment of the present invention.

[0041] Figure 2 It is a logical schematic diagram of a V2X-based traffic situation warning method in an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below with reference to the accompanying drawings.

[0043] like Figure 1 and Figure 2 FIG. 1 is a schematic diagram of an embodiment of a V2X-based traffic situation warning method provided by the present invention. In this embodiment, the method includes the following steps:

[0044] Step S1, obtain traffic data collected by multiple data sources, and pre-process the received traffic data; wherein the traffic data at least includes traffic flow, vehicle speed and pedestrian flow; the data source at least includes one or more of road test sensing equipment, vehicle-mounted terminals, GPS devices and mobile applications. It is understandable that in the data collection and pre-processing stages, diversified data sources, including road test monitoring equipment, vehicle-mounted terminals, etc., are used to collect traffic data in real time. After these data are collected and accessed by the equipment, they are reported to Apache Kafka (hereinafter referred to as Kafka) in real time, and Apache Flink (hereinafter referred to as Flink) subscribes to the traffic data topic of kafka to obtain traffic data for real-time processing. In this embodiment, V2X, vehicle to everything, that is, the exchange of information between the vehicle and the outside world, is a commonly used abbreviation in this field and will not be repeated here.

[0045] In one embodiment, the preprocessing of the received traffic data includes identifying the perception data output by the road test perception device, and determining the data speed when the perception data is collected and the corresponding perception object in the perception data and the acceleration of the perception object in the time series; if the data speed when a certain perception data is collected exceeds the preset speed limit threshold, the speed of the perception data is determined to be abnormal; wherein the data speed is the time speed of the traffic data when it is collected; if the difference between the acceleration of the same perception object at a certain moment and the three most recent accelerations at that moment exceeds the preset acceleration threshold, the perception data is determined to be abnormal. It is understandable that Flink will perform data cleaning operations when processing reported data, mainly including abnormal data and duplicate data. In actual situations, the data perceived by the road test equipment is not 100% accurate, and there may be data with some recognition errors, such as abnormal speed recognition, abnormal latitude and longitude recognition, etc. When processing data, Flink identifies anomalies in the data perceived by the road test equipment (hereinafter referred to as perceived data). On the one hand, it configures a speed limit threshold. If the speed of the collected data exceeds the speed limit, the data is considered to have an abnormal speed. On the other hand, it performs speed change analysis and configures an acceleration threshold. When the difference between the acceleration collected by the same sensor and the acceleration perceived three times in the past exceeds the acceleration threshold, the data is also considered to have an abnormal speed.

[0046] It also includes, when it is determined that the perception data is abnormal, identifying the latitude and longitude position of the perception object at the abnormal moment and the latitude and longitude position of the previous moment of the abnormal moment and determining the distance between the two moments; calculating the corresponding average speed according to the distance between the two moments, and replacing the acceleration at the abnormal moment with the average speed. That is, for the perception data judged as abnormal speed, the distance is calculated according to the latitude and longitude position of the perception data and the latitude and longitude position of the previous perception data of the perception object, and the time is calculated according to the time difference between the two perception data, so as to calculate the average speed, and replace the abnormal speed with the average speed.

[0047] In addition, in some scenarios, people are more concerned about changes in some data, such as map data and event data. For example, the map data of some intersections needs to be reported continuously for business reasons, but the map data does not change frequently, and a large amount of duplicate map data will be generated. These duplicate map data will occupy the computing resources of the downstream map change processing tasks and need to be filtered. Flink will monitor the changes in the data content of this part of the data, and perform hash value and length verification calculations on the data content. When the hash value or length changes, it is considered that the data content has changed and the downstream processing tasks need to be notified, otherwise the data will be filtered out.

[0048] Step S2, determine the corresponding traffic indicators based on the preprocessed traffic data, wherein the traffic indicators at least include vehicle and pedestrian flow, average vehicle speed and lane traffic situation; wherein the lane traffic situation at least includes a corresponding level representing the road congestion situation within a preset time period, and the corresponding level includes at least one of smooth, light congestion, moderate congestion and severe congestion; it is understandable that after filtering and cleaning abnormal and duplicate data, Flink will calculate various traffic indicators in real time. This part mainly includes some traffic indicator data analysis at intersections and lane levels, including vehicle and pedestrian flow, average vehicle speed and vehicle traffic situation. Flink configures a series of traffic indicator calculation tasks.

[0049] In one embodiment, the determination of the corresponding traffic index according to the pre-processed traffic data includes counting the number of vehicles and pedestrians at the corresponding traffic intersection within a preset time period, and outputting the number of vehicles and pedestrians as vehicle and pedestrian flow; it is understandable that the calculation of vehicle and pedestrian flow is mainly based on the data of vehicles and pedestrians passing through a specific intersection or lane in the perception data. In Flink, the number of vehicles and pedestrians passing through a certain monitoring point, i.e., the corresponding traffic intersection, within a certain time window (every 5 minutes) is counted. The vehicles passing through an intersection include various types, such as trucks, cars, tricycles, taxis, etc. When the road test perception device detects the perception object, it analyzes the type of the perception object by identifying the shape and size of the perception object, whether it is a vehicle type or a pedestrian, and reports the identification information at the same time. Flink groups the perception objects according to the type of perception object identified by the road test perception device, and classifies and counts them according to the type of vehicles and pedestrians. The flow is equal to the total number of vehicles and pedestrians detected within the time window, and the unit is "vehicle / person-time". In fact, the passage of vehicles or pedestrians through an intersection is a continuous process. During this process, the perception data of vehicles and pedestrians will be continuously reported. In this process, it is also necessary to accurately and uniquely identify different perception objects in order to accurately calculate the flow rate. In the process of identifying perception objects, the road test perception equipment will extract the characteristic information of the perception objects, establish a perception object feature library, convert the characteristic information identified by the perception objects into a unique feature ID, and report the feature ID at the same time. Flink calculates the flow rate based on the feature ID, and repeated feature IDs are not included in the flow statistics.

[0050] Extract the speed information of all vehicles within a preset time period and calculate the average speed of the corresponding vehicles. It is understandable that the calculation of the average speed of the vehicle is done by counting the speeds of all vehicles passing through the monitoring point within a specific time window, with 5 minutes as a time statistical window. Extract the speed information of all vehicles within the time window and perform validity checks to ensure the accuracy of the data. The road test perception equipment collects speed data through the combination of millimeter-wave radar and visual perception technology. Millimeter-wave radar can emit and receive electromagnetic waves, and calculate the distance and speed of objects by analyzing the reflected signals, while the visual sensor uses image processing technology to identify and track vehicles, capture their movement trajectories, and calculate the speed by comparing continuous frame images, and report the calculated speed data.

[0051] Among them, at the end of the window, the average speed of the vehicle is calculated. After a vehicle or pedestrian passes by, the road test perception device calculates the instantaneous speed of the perceived object through the radar-vision fusion technology. After Flink obtains this speed data, it performs frame extraction and sampling to ensure that the speed samples obtained for each perceived object within the same time unit are consistent, avoiding the amplification of the weight of some speed data in the calculation of the average speed due to different frame rates. After sampling, the average speed is calculated using the following formula:

[0052]

[0053] The determination of the corresponding traffic indicators based on the preprocessed traffic data further includes determining the number of vehicles per unit length of the lane according to the real-time vehicle and pedestrian flow; determining the traffic situation of the lane based on the number of vehicles per unit length of the lane and the average speed of the vehicles. It can be understood that the traffic situation of the lane refers to the comprehensive traffic conditions within a certain lane, reflecting the congestion status of the road.

[0054] Flink will perform calculations and analyses in the following way: Based on the real-time flow and average speed data, it uses indicators such as traffic density (number of vehicles / km) and speed difference to evaluate the congestion level of the lane. Traffic density ((D)) is an important indicator for evaluating the traffic flow situation, representing the number of vehicles per unit length of the lane. D = N / L, where N represents the number of vehicles in the lane and L represents the length of the lane. The average speed ((V)) is calculated by the calculation method in Section 2.2.2 above. In the situation assessment, the road congestion is divided into four levels as follows:

[0055] Uncongested: D < Dlow and V > Viigh

[0056] Slightly congested: Dlow ≤ D < Dmediu m and Vhigh ≤ V < Vmedium

[0057] Moderately congested: Dmedium ≤ D < Dhigh and V < Vmedium

[0058] Severely congested: D ≥ Dhigh and V < Vlow.

[0060] Wherein, the determining of the lane traffic situation in the lane includes: when the number of vehicles on a lane per unit length in the lane is less than a preset first number threshold and the average speed of the vehicles is greater than the preset first speed threshold, determining that the lane traffic situation in the lane is unblocked; when the number of vehicles on a lane per unit length in the lane is greater than or equal to the preset first number threshold and less than the preset second number threshold, and the average speed of the vehicles is less than or equal to the preset first speed threshold and greater than the preset second speed threshold, determining that the lane traffic situation in the lane is slightly congested; when the number of vehicles on a lane per unit length in the lane is greater than or equal to the preset second number threshold and less than the preset third number threshold and the average speed of the vehicles is less than the preset second speed threshold, determining that the lane traffic situation in the lane is slightly congested; when the number of vehicles on a lane per unit length in the lane is greater than or equal to the preset third number threshold and the average speed of the vehicles is less than the preset third speed threshold, determining that the lane traffic situation in the lane is slightly congested. It is understandable that different roads have different speed limits. Here, corresponding speed limit thresholds are set according to different lanes. When Flink obtains the perception data reported by the road test equipment, it obtains lane information through the lane corresponding to the perception data. The lane information contains the speed limit threshold of the lane. With the speed limit threshold, the situation level can be evaluated according to the traffic situation and average speed.

[0061] Step S3, evaluate the corresponding traffic situation according to the traffic indicators, and if the traffic situation is abnormal, output the corresponding risk warning information. It can be understood that by collecting road test perception data to analyze the flow situation and traffic congestion situation of the corresponding lane, these traffic indicators Flink will be written into the database in real time after calculation, supporting the upper-level application to display data and perform warning processing.

[0062] In one embodiment, the traffic situation condition corresponding to the traffic indicator evaluation includes determining the corresponding traffic situation condition according to the traffic indicator within the preset first time period threshold; if the lane traffic situation of all lanes is not in a serious congestion state or the lane traffic situation of a lane changes from a serious congestion state to a non-serious congestion state within the first time period threshold, the corresponding traffic situation condition is determined to be normal; if the lane traffic situation of a lane is always in a serious congestion state within the first time period threshold, the traffic situation condition is determined to be abnormal. Understandably, the analyzed traffic situation congestion condition is also used to implement risk warning. Under normal circumstances, vehicles will pass through the traffic intersection in an orderly manner, and the flow density and average speed will remain within a normal range. Even when waiting for a red light, the congestion of vehicles will deepen for a short time, but if the observation time is extended, these traffic indicators will be within a normal range again. Therefore, if it is observed that the traffic situation of the lane is evaluated as serious congestion within a long time range, a risk warning will be triggered, and the risk warning can be notified to the traffic management personnel through SMS push, so that they can quickly take countermeasures.

[0063] An embodiment of the present invention further provides a V2X-based traffic situation warning system for implementing the V2X-based traffic situation warning method, comprising:

[0064] A data acquisition module, used to acquire traffic data collected from multiple data sources and pre-process the received traffic data; wherein the traffic data at least includes traffic flow, vehicle speed and pedestrian flow;

[0065] A data processing module, used to determine corresponding traffic indicators according to the pre-processed traffic data, wherein the traffic indicators at least include vehicle and pedestrian flow, average vehicle speed and lane traffic situation; wherein the lane traffic situation at least includes a corresponding level indicating road congestion within a preset time period, and the corresponding level includes at least one of unblocked, lightly congested, moderately congested and severely congested;

[0066] It is also used to evaluate the corresponding traffic situation according to the traffic indicators, and if the traffic situation is abnormal, output corresponding risk warning information.

[0067] An embodiment of the present invention further provides a device for performing risk warning through the V2X-based traffic situation warning method.

[0068] It should be noted that the system described in the above embodiment corresponds to the method described in the above embodiment. Therefore, the undetailed parts of the system described in the above embodiment can be obtained by referring to the contents of the method described in the above embodiment, and will not be repeated here.

[0069] In summary, the implementation of the embodiments of the present invention has the following beneficial effects:

[0070] The V2X-based traffic situation warning method, system and device provided by the present invention improves the efficiency of urban traffic management and alleviates traffic congestion through real-time data monitoring technology. It relies on multi-source data collection and uses multiple devices such as road test sensing equipment, vehicle terminals, GPS devices and mobile applications to collect important data such as traffic flow, vehicle speed, pedestrian flow, etc. in real time to ensure the comprehensiveness and accuracy of the information. It also conducts real-time traffic flow analysis based on the collected data to improve traffic management efficiency and reduce congestion and accident rates.

[0071] The above disclosure is only the preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A traffic situation warning method based on V2X, characterized in that: include: Acquire traffic data collected from multiple data sources and pre-process the received traffic data; wherein the traffic data at least includes traffic flow, vehicle speed and pedestrian flow; Determine corresponding traffic indicators according to the preprocessed traffic data, wherein the traffic indicators at least include vehicle and pedestrian flow, average vehicle speed, and lane traffic situation; wherein the lane traffic situation at least includes a corresponding level indicating road congestion within a preset time period, and the corresponding level includes at least one of unblocked, lightly congested, moderately congested, and severely congested; The corresponding traffic situation is evaluated according to the traffic indicators, and if the traffic situation is abnormal, the corresponding risk warning information is output.

2. The method according to claim 1, characterized in that The data source includes at least one or more of a road test sensing device, a vehicle-mounted terminal, a GPS device, and a mobile application.

3. The method according to claim 2, characterized in that The preprocessing of the received traffic data includes: Identify the perception data output by the drive test perception device, and determine the data speed when the perception data is collected, the corresponding perception object in the perception data, and the acceleration of the perception object in the time series; If the data speed of a piece of perception data during collection exceeds a preset speed limit threshold, the speed of the perception data is determined to be abnormal; wherein the data speed is the speed at which the traffic data was collected; If the difference between the acceleration of the same perceived object at a certain moment and the three most recent accelerations at that moment exceeds a preset acceleration threshold, the perceived data is judged to be abnormal.

4. The method according to claim 3, characterized in that Also includes, When the sensed data is determined to be abnormal, the longitude and latitude position of the sensed object at the abnormal moment and the longitude and latitude position at the moment before the abnormal moment are identified and the distance between the two moments is determined; The corresponding average speed is calculated according to the distance between the two moments, and the acceleration at the abnormal moment is replaced by the average speed.

5. The method according to claim 4, characterized in that Determining the corresponding traffic index according to the pre-processed traffic data includes: Counting the number of vehicles and pedestrians at the corresponding traffic intersection within a preset time period, and outputting the number of vehicles and pedestrians as vehicle and pedestrian flow; Extract the speed information of all vehicles within a preset time period and calculate the average speed of the corresponding vehicles.

6. The method according to claim 5, characterized in that The determining of the corresponding traffic index according to the pre-processed traffic data also includes: Determine the number of vehicles per unit length in the lane according to the real-time vehicle and pedestrian flow; The lane traffic situation in the lane is determined based on the number of vehicles per unit length in the lane and the average speed of the vehicles.

7. The method according to claim 6, characterized in that Determining the lane traffic situation in the lane includes: When the number of vehicles per unit length in the lane is less than a preset first number threshold and the average speed of the vehicles is greater than a preset first speed threshold, it is determined that the lane traffic situation in the lane is unblocked; When the number of vehicles per unit length in the lane is greater than or equal to a preset first number threshold and less than a preset second number threshold, and the average speed of the vehicles is less than or equal to a preset first speed threshold and greater than a preset second speed threshold, it is determined that the lane traffic situation in the lane is slightly congested; When the number of vehicles per unit length in the lane is greater than or equal to a preset second number threshold and less than a preset third number threshold and the average speed of the vehicles is less than a preset second speed threshold, it is determined that the lane traffic situation in the lane is slightly congested; When the number of vehicles per unit length in the lane is greater than or equal to a preset third number threshold and the average speed of the vehicles is less than a preset third speed threshold, it is determined that the lane traffic situation in the lane is slightly congested.

8. The method according to claim 7, characterized in that The traffic situation status corresponding to the traffic indicator evaluation includes: Determine the corresponding traffic situation according to the traffic indicators within the preset first time period threshold; If the lane traffic situation of all lanes is not in a serious congestion state or the lane traffic situation of a lane changes from a serious congestion state to a non-severe congestion state within the first time period threshold, it is determined that the corresponding traffic situation is normal; If the traffic situation of a lane has been in a serious congestion state within the first time period threshold, it is determined that the traffic situation is abnormal.

9. A V2X-based traffic situation warning system, used to implement the method according to any one of claims 1 to 8, characterized in that: include, A data acquisition module, used to acquire traffic data collected from multiple data sources and pre-process the received traffic data; wherein the traffic data at least includes traffic flow, vehicle speed and pedestrian flow; A data processing module, used to determine corresponding traffic indicators according to the pre-processed traffic data, wherein the traffic indicators at least include vehicle and pedestrian flow, average vehicle speed and lane traffic situation; wherein the lane traffic situation at least includes a corresponding level indicating road congestion within a preset time period, and the corresponding level includes at least one of unblocked, lightly congested, moderately congested and severely congested; It is also used to evaluate the corresponding traffic situation according to the traffic indicators, and if the traffic situation is abnormal, output corresponding risk warning information.

10. A device, characterized in that: Risk warning is performed by using the V2X-based traffic situation warning method as described in any one of claims 1 to 8.

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