A highway traffic safety intelligent detection system and method

Abstract

The present invention relates to an intelligent highway traffic safety detection system and method, and relates to the technical field of traffic safety detection. The method comprises: determining multiple first-level highway traffic safety detection points and second-level highway traffic safety detection points, and traffic safety associated information of the first-level highway traffic safety detection points according to historical highway traffic data of a target area; regulating multiple second image acquisition units according to traffic safety related information corresponding to each first-level highway traffic safety detection point; generating highway traffic safety early warning information according to traffic safety related information corresponding to each first-level highway traffic safety detection point and traffic safety associated information of multiple first-level highway traffic safety detection points in the target area through multiple edge computing units, and performing safety detection according to highway images collected by multiple first image acquisition units and multiple second image acquisition units, which has the advantages of realizing automatic detection of highway traffic safety and improving the real-time performance of safety prompts.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic safety detection, and in particular to a highway traffic safety intelligent detection system and method. Background Art

[0002] The development of expressways has promoted the high-speed operation of passenger flow, logistics and information flow, greatly improved transportation efficiency, and brought significant social and economic benefits. However, expressways also have traffic safety risks. In order to effectively prevent and reduce traffic accidents on expressways, it is necessary to monitor and analyze the road conditions of expressways in real time and provide traffic safety warning information to drivers or traffic management personnel in a timely manner.

[0003] Existing highway lane line detection and warning devices mainly use intelligent equipment on the highway for auxiliary monitoring. They are unable to accurately and effectively monitor the real-time situation of driving vehicles, and cannot meet the needs of effective monitoring and early warning of real-time safe driving of driving vehicles, resulting in frequent safety accidents.

[0004] Therefore, it is necessary to provide a highway traffic safety intelligent detection system and method for realizing automated detection of highway traffic safety and improving the real-time performance of highway traffic safety prompts. Summary of the invention

[0005] The present invention provides an intelligent highway traffic safety detection system, comprising: a detection layout module, used to obtain historical highway traffic data of a target area, and determine a plurality of first-level highway traffic safety detection points and a plurality of second-level highway traffic safety detection points in the target area according to the historical highway traffic data of the target area; a detection association module, used to determine traffic safety association information of a plurality of first-level highway traffic safety detection points in the target area according to the historical highway traffic data of the target area; a data acquisition module, including a data acquisition unit corresponding to each first-level highway traffic safety detection point, wherein the data acquisition unit is used to acquire traffic safety related information corresponding to the corresponding first-level highway traffic safety detection point, and the traffic safety related information at least includes vehicle flow and meteorological information; an image acquisition module, used to include an acquisition control unit; element, a plurality of first image acquisition units set at a plurality of first-level highway traffic safety detection points and a plurality of second image acquisition units set at a plurality of second-level highway traffic safety detection points, wherein the acquisition and control unit is used to control the plurality of second image acquisition units according to the traffic safety-related information corresponding to the first-level highway traffic safety detection points obtained by each data acquisition unit; a safety analysis module, including a plurality of edge computing units, the plurality of edge computing units are used to generate highway traffic safety warning information according to the traffic safety-related information corresponding to the first-level highway traffic safety detection points obtained by each data acquisition unit and the traffic safety association information of the plurality of first-level highway traffic safety detection points in the target area, and are also used to perform safety detection according to the highway images acquired by the plurality of first image acquisition units and the plurality of second image acquisition units.

[0006] Furthermore, the detection layout module determines multiple first-level highway traffic safety detection points and multiple second-level highway traffic safety detection points in the target area based on the historical highway traffic data of the target area, including: determining multiple accident points based on the historical highway traffic data of the target area; clustering the multiple accident points according to the highway distance between any two accident points through a clustering algorithm to determine multiple accident point clusters, and determining multiple first-level highway traffic safety detection points based on the multiple accident point clusters; determining multiple second-level highway traffic safety detection points based on the highway connectivity relationship of the multiple first-level highway traffic safety detection points. Furthermore, the detection layout module determines multiple second-level highway traffic safety detection points based on the highway connectivity relationship of the multiple first-level highway traffic safety detection points, including: determining multiple first-level highway traffic safety detection point groups based on the highway connectivity relationship of the multiple first-level highway traffic safety detection points, wherein the first-level highway traffic safety detection point group includes two adjacent first-level highway traffic safety detection points that are connected by a highway;

[0007] For each first-level highway traffic safety detection point group, the density of the second-level highway traffic safety detection points of the first-level highway traffic safety detection point group is determined according to the accident point clusters corresponding to each first-level highway traffic safety detection point included in the first-level highway traffic safety detection point group, and according to the density of the second-level highway traffic safety detection points of the first-level highway traffic safety detection point group, at least one second-level highway traffic safety detection point is set between two first-level highway traffic safety detection points included in the first-level highway traffic safety detection point group.

[0008] Furthermore, the detection association module determines traffic safety association information of multiple first-level highway traffic safety detection points in the target area based on historical highway traffic data of the target area, including: for any two first-level highway traffic safety detection points in the target area, determining accident co-occurrence parameters of the two first-level highway traffic safety detection points based on historical highway traffic data of the target area; determining associated first-level highway traffic safety detection points of each first-level highway traffic safety detection point based on the accident co-occurrence parameters of any two first-level highway traffic safety detection points, wherein the traffic safety association information of multiple first-level highway traffic safety detection points in the target area includes the associated first-level highway traffic safety detection points of each first-level highway traffic safety detection point.

[0009] Furthermore, the data acquisition module sets a data acquisition unit corresponding to each first-level highway traffic safety detection point, including: for each first-level highway traffic safety detection point, determining the safety impact weight of each meteorological factor corresponding to the first-level highway traffic safety detection point based on the historical highway traffic data of the target area, determining the key meteorological factors corresponding to the first-level highway traffic safety detection point based on the safety impact weight of each meteorological factor corresponding to the first-level highway traffic safety detection point, and determining a meteorological information collection component based on the key meteorological factors corresponding to the first-level highway traffic safety detection point, wherein the meteorological information collection component is used to collect meteorological information corresponding to the first-level highway traffic safety detection point.

[0010] Furthermore, the acquisition and control unit controls the multiple second image acquisition units according to the traffic safety-related information corresponding to the first-level highway traffic safety detection point acquired by each data acquisition unit, including: for each first-level highway traffic safety detection point, calculating the safety risk value of the first-level highway traffic safety detection point according to the traffic safety-related information corresponding to the first-level highway traffic safety detection point; for each first-level highway traffic safety detection point group, judging whether to turn on the second image acquisition unit corresponding to the first-level highway traffic safety detection point group according to the safety risk value of each first-level highway traffic safety detection point included in the first-level highway traffic safety detection point group.

[0011] Furthermore, the multiple edge computing units generate highway traffic safety warning information based on the traffic safety-related information corresponding to the first-level highway traffic safety detection point acquired by each data collection unit and the traffic safety association information of multiple first-level highway traffic safety detection points in the target area, including: determining the risky highways in the target area based on the safety risk values ​​of the first-level highway traffic safety detection points and the associated first-level highway traffic safety detection points of each first-level highway traffic safety detection point; generating the highway traffic safety warning information based on the risky highways in the target area.

[0012] Furthermore, the multiple edge computing units perform safety detection based on the highway images collected by the multiple first image acquisition units and the multiple second image acquisition units, including: determining the first image acquisition unit and the second image acquisition unit corresponding to each edge computing unit based on the status information of the multiple edge computing units and the control results of the multiple second image acquisition units; for each edge computing unit, the edge computing unit performs safety detection based on the highway images collected by the corresponding first image acquisition unit and the second image acquisition unit.

[0013] Furthermore, the edge computing unit performs safety detection based on the highway images collected by the corresponding first image acquisition unit and the second image acquisition unit, including: performing safety detection based on the highway images collected by the corresponding first image acquisition unit and the second image acquisition unit through a safety detection model.

[0014] The present invention provides a method for intelligent detection of highway traffic safety, which is applied to the above-mentioned intelligent detection system of highway traffic safety, including: obtaining historical highway traffic data of a target area; determining multiple first-level highway traffic safety detection points and multiple second-level highway traffic safety detection points in the target area according to the historical highway traffic data of the target area; determining traffic safety association information of multiple first-level highway traffic safety detection points in the target area according to the historical highway traffic data of the target area; obtaining traffic safety related information corresponding to each first-level highway traffic safety detection point, wherein the traffic safety related information at least includes vehicle flow and meteorological information; regulating the multiple second image acquisition units according to the traffic safety related information corresponding to each first-level highway traffic safety detection point; generating highway traffic safety warning information according to the traffic safety related information corresponding to each first-level highway traffic safety detection point and the traffic safety association information of multiple first-level highway traffic safety detection points in the target area through multiple edge computing units; performing safety detection according to highway images collected by multiple first image acquisition units and multiple second image acquisition units through multiple edge computing units.

[0015] Compared with the prior art, the highway traffic safety intelligent detection system provided in this specification has at least the following beneficial effects:

[0016] By setting up primary and secondary highway traffic safety detection points, the system can fully cover the traffic conditions in the target area, monitor and warn potential safety hazards in real time. The safety analysis module uses the edge computing unit to quickly process traffic safety related information and generate warning information, which helps to take safety measures in time and reduce the occurrence of traffic accidents. The detection layout module intelligently determines the location of the detection point based on historical highway traffic data, so that the detection resources are reasonably allocated and the detection efficiency is improved. The data acquisition module and the image acquisition module can automatically collect and process data, reduce manual intervention, and realize intelligent management. It can perform accurate safety analysis based on real-time collected traffic data (such as traffic flow, meteorological information, etc.) and image information, and provide timely warning information. Through the analysis of related information, the system can identify high-risk areas or time periods and provide targeted safety suggestions and countermeasures for traffic management departments. The acquisition and control unit controls the image acquisition unit of the secondary detection point based on the data of the primary highway traffic safety detection point, avoiding waste of resources and improving acquisition efficiency. The application of edge computing units makes data processing more efficient, reduces data transmission delays, and improves the real-time performance of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0018] Figure 1 is a module diagram of a highway traffic safety intelligent detection system shown in an embodiment of the present application;

[0019] Figure 2 It is a flow chart of a method for intelligent detection of highway traffic safety shown in one embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following briefly introduces the drawings required for describing the embodiments.

[0021] Figure 1 is a module diagram of a highway traffic safety intelligent detection system shown in an embodiment of the present application, such as Figure 1 As shown, a highway traffic safety intelligent detection system may include a detection layout module, a detection association module, a data acquisition module, an image acquisition module and a safety analysis module.

[0022] The detection layout module can be used to obtain historical highway traffic data of the target area, and determine multiple primary highway traffic safety detection points and multiple secondary highway traffic safety detection points in the target area based on the historical highway traffic data of the target area.

[0023] Specifically include:

[0024] Based on the historical highway traffic data of the target area, multiple accident points are identified;

[0025] By using a clustering algorithm (e.g., a K-means clustering algorithm), a plurality of accident points are clustered according to the road distance between any two accident points to determine a plurality of accident point clusters, and a plurality of first-class highway traffic safety detection points are determined according to the plurality of accident point clusters;

[0026] According to the highway connectivity relationship among multiple first-level highway traffic safety inspection points, multiple second-level highway traffic safety inspection points are determined.

[0027] Specifically, based on the historical highway traffic data of the target area, the location points where traffic accidents are prone to occur can be determined as accident points.

[0028] The road distance between two accident points may be the length of the road connecting the two accident points.

[0029] Based on the following process, multiple first-level highway traffic safety detection points can be determined according to multiple accident point clusters, including:

[0030] For each accident point cluster, according to the highway distance between any two accident points included in the accident point cluster, the first-level highway traffic safety detection point corresponding to the accident point cluster is calculated;

[0031] S11, calculating a discrete value of the highway distance corresponding to the accident point cluster according to the highway distance between any two accident points included in the accident point cluster;

[0032] S12, determining the number of first-class highway traffic safety detection points corresponding to the accident point cluster according to the highway distance discrete value corresponding to the accident point cluster;

[0033] S13, based on the number of first-class highway traffic safety detection points corresponding to the accident point cluster, clustering the accident points included in the accident point cluster according to the highway distance between any two accident points included in the accident point cluster by a clustering algorithm (e.g., a K-means clustering algorithm), and determining a plurality of accident point groups corresponding to the accident point cluster, wherein the number of accident point groups is consistent with the number of first-class highway traffic safety detection points corresponding to the accident point cluster;

[0034] S14. For each accident point group, determine the coordinates of the first-class highway traffic safety detection point corresponding to the accident point group according to the coordinates of each accident point included in the accident point group, wherein one accident point group corresponds to one first-class highway traffic safety detection point.

[0035] For example, the discrete value of the road distance corresponding to the accident point cluster can be calculated according to the following formula:

[0036] ;

[0037] in, is the discrete value of the highway distance corresponding to the kth accident point cluster, is the highway distance between the nth accident point included in the kth accident point cluster and the cluster center of the kth accident point cluster, is the total number of accident points included in the kth accident point cluster.

[0038] The number of first-level highway traffic safety detection points corresponding to the accident point cluster can be calculated according to the following formula:

[0039] ;

[0040] in, is the number of first-level highway traffic safety detection points corresponding to the k-th accident point cluster, is the preset road distance discrete value, The number of preset first-level highway traffic safety inspection points.

[0041] The coordinates of the first-level highway traffic safety detection points corresponding to the accident point group can be determined according to the following formula:

[0042] ;

[0043] in, is the coordinate of the first-level highway traffic safety detection point corresponding to the i-th accident point group, is the coordinate of the mth accident point included in the ith accident point group, is the total number of accident points included in the i-th accident point group.

[0044] In some embodiments, the detection layout module determines a plurality of secondary highway traffic safety detection points according to the highway connectivity relationship of the plurality of primary highway traffic safety detection points, including:

[0045] Determine a plurality of first-class highway traffic safety detection point groups according to the highway connectivity relationship of the plurality of first-class highway traffic safety detection points, wherein the first-class highway traffic safety detection point group includes two first-class highway traffic safety detection points that are adjacent and connected by a highway;

[0046] For each first-level highway traffic safety detection point group, the density of second-level highway traffic safety detection points of the first-level highway traffic safety detection point group is determined according to the accident point clusters corresponding to each first-level highway traffic safety detection point included in the first-level highway traffic safety detection point group; based on the density of second-level highway traffic safety detection points of the first-level highway traffic safety detection point group, at least one second-level highway traffic safety detection point is set between two first-level highway traffic safety detection points included in the first-level highway traffic safety detection point group.

[0047] Specifically, the density of the secondary highway traffic safety detection point group of the primary highway traffic safety detection point group can be determined according to the following formula:

[0048] ;

[0049] in, is the density of the secondary highway traffic safety detection points between the first-level highway traffic safety detection point and the j-th first-level highway traffic safety detection point in the first-level highway traffic safety detection point group, is the accident risk value of the nth accident point included in the accident point cluster corresponding to the i-th first-class highway traffic safety detection point, is the total number of accident points included in the accident point cluster corresponding to the i-th first-class highway traffic safety detection point, is the accident risk value of the nth accident point included in the accident point cluster corresponding to the jth first-class highway traffic safety detection point, The first-class highway traffic safety detection point group includes the total number of accident points included in the accident point cluster corresponding to the j-th first-class highway traffic safety detection point.

[0050] The accident risk value of the accident point included in the accident point cluster can be determined by a risk determination model based on historical highway traffic data corresponding to the accident points included in the accident point cluster, wherein the risk determination model can be a convolutional neural network model.

[0051] The number of secondary highway traffic safety inspection points to be set up between two primary highway traffic safety inspection points included in the primary highway traffic safety inspection point group can be determined according to the density of secondary highway traffic safety inspection points in the primary highway traffic safety inspection point group. The greater the density of secondary highway traffic safety inspection points, the greater the number of secondary highway traffic safety inspection points.

[0052] The detection association module can be used to determine the traffic safety association information of multiple first-level highway traffic safety detection points in the target area based on the historical highway traffic data of the target area.

[0053] Specifically include:

[0054] For any two first-class highway traffic safety detection points in the target area, the accident co-occurrence parameters of the two first-class highway traffic safety detection points are determined based on the historical highway traffic data of the target area;

[0055] According to the accident co-occurrence parameters of any two first-level highway traffic safety detection points, the associated first-level highway traffic safety detection points of each first-level highway traffic safety detection point are determined, wherein the traffic safety association information of multiple first-level highway traffic safety detection points in the target area includes the associated first-level highway traffic safety detection points of each first-level highway traffic safety detection point.

[0056] For example, the accident co-occurrence parameters of two first-level highway traffic safety detection points can be calculated according to the following formula:

[0057] ;

[0058] in, is the accident co-occurrence parameter of the i-th first-class highway traffic safety detection point and the j-th first-class highway traffic safety detection point, is the total number of accidents that occurred in the tth historical time period at the accident points included in the cluster corresponding to the i-th first-level highway traffic safety detection point, is the total number of accidents that occurred in the tth historical time period at the accident points included in the cluster corresponding to the jth first-level highway traffic safety detection point, is the total number of historical time periods sampled.

[0059] The data acquisition module may include a data acquisition unit corresponding to each first-level highway traffic safety detection point, wherein the data acquisition unit is used to obtain traffic safety related information corresponding to the corresponding first-level highway traffic safety detection point, and the traffic safety related information at least includes vehicle flow and meteorological information.

[0060] In some embodiments, the data collection module sets a data collection unit corresponding to each first-level highway traffic safety detection point, including:

[0061] For each first-class highway traffic safety checkpoint, the safety impact weight of each meteorological factor (for example, precipitation, visibility, wind speed, temperature, etc.) corresponding to the first-class highway traffic safety checkpoint is determined based on the historical highway traffic data of the target area. Based on the safety impact weight of each meteorological factor corresponding to the first-class highway traffic safety checkpoint, the key meteorological factors corresponding to the first-class highway traffic safety checkpoint are determined. Based on the key meteorological factors corresponding to the first-class highway traffic safety checkpoint, a meteorological information collection component is determined, wherein the meteorological information collection component is used to collect meteorological information corresponding to the first-class highway traffic safety checkpoint. For example, if the key meteorological factors include temperature and humidity, the meteorological information collection component includes temperature and humidity sensors.

[0062] Specifically, a hierarchical model can be established: decompose the problem into a target layer, a criterion layer, and a solution layer. The target layer is the traffic safety of the first-class highway, the criterion layer is the various meteorological factors, and the solution layer is the different safety detection points. Construct a judgment matrix: Based on expert experience or historical data, compare each meteorological factor in pairs to construct a judgment matrix. Calculate weights: Use the judgment matrix to calculate the weights of each meteorological factor. The meteorological factors whose safety impact weights are greater than the safety impact weight threshold are regarded as the key meteorological factors corresponding to the first-class highway traffic safety detection points.

[0063] The image acquisition module can be used to include an acquisition and control unit, multiple first image acquisition units set at multiple first-level highway traffic safety detection points, and multiple second image acquisition units set at multiple second-level highway traffic safety detection points, wherein the acquisition and control unit is used to control the multiple second image acquisition units according to the traffic safety-related information corresponding to the first-level highway traffic safety detection point obtained by each data acquisition unit.

[0064] In some embodiments, the acquisition and control unit controls the plurality of second image acquisition units according to the traffic safety related information corresponding to the first-level highway traffic safety detection point acquired by each data acquisition unit, including:

[0065] For each first-class highway traffic safety detection point, the safety risk value of the first-class highway traffic safety detection point is calculated based on the traffic safety related information corresponding to the first-class highway traffic safety detection point;

[0066] For each first-level highway traffic safety detection point group, it is determined whether to open the second image acquisition unit corresponding to the first-level highway traffic safety detection point group according to the safety risk value of each first-level highway traffic safety detection point included in the first-level highway traffic safety detection point group.

[0067] Specifically, the safety risk value of the first-class highway traffic safety detection point can be calculated according to the traffic safety related information corresponding to the first-class highway traffic safety detection point through the risk prediction model, wherein the risk prediction model can be a long short-term memory network model.

[0068] When the mean value of the safety risk value of each first-level highway traffic safety detection point included in the first-level highway traffic safety detection point group is greater than the first mean value threshold, the second image acquisition unit corresponding to the first-level highway traffic safety detection point group is turned on.

[0069] The safety analysis module may include multiple edge computing units, which are used to generate highway traffic safety warning information based on the traffic safety-related information corresponding to the first-level highway traffic safety detection point obtained by each data acquisition unit and the traffic safety association information of multiple first-level highway traffic safety detection points in the target area, and are also used to perform safety detection based on highway images collected by multiple first image acquisition units and multiple second image acquisition units.

[0070] In some embodiments, multiple edge computing units generate highway traffic safety warning information based on traffic safety related information corresponding to the primary highway traffic safety detection point acquired by each data collection unit and traffic safety association information of multiple primary highway traffic safety detection points in the target area, including:

[0071] Determine the risk highways within the target area based on the safety risk values ​​of the first-level highway traffic safety detection points and the associated first-level highway traffic safety detection points of each first-level highway traffic safety detection point;

[0072] Generate highway traffic safety warning information based on risky highways in the target area.

[0073] Specifically, the safety risk value of the first-level highway traffic safety checkpoint and the average of the safety risk values ​​of the associated first-level highway traffic safety checkpoints of each first-level highway traffic safety checkpoint can be calculated. If the average is greater than the second average threshold, the highway where the first-level highway traffic safety checkpoint is located will be regarded as a risk highway in the target area.

[0074] In some embodiments, the plurality of edge computing units perform safety detection based on the highway images collected by the plurality of first image collection units and the plurality of second image collection units, including:

[0075] Determine the first image acquisition unit and the second image acquisition unit corresponding to each edge computing unit according to the status information of the plurality of edge computing units and the control results of the plurality of second image acquisition units;

[0076] For each edge computing unit, the edge computing unit performs safety detection based on the highway images collected by the corresponding first image acquisition unit and the second image acquisition unit.

[0077] Specifically, the status information of each edge computing unit is obtained in real time, including processing power, load status, network connection status, etc. According to the status information and control strategy of the edge computing unit, the first image acquisition unit and the second image acquisition unit corresponding to each edge computing unit are dynamically adjusted. For example, when the load of an edge computing unit is high, the number of its corresponding image acquisition units can be reduced; when the processing power of an edge computing unit is strong and the load is low, the number of its corresponding image acquisition units can be increased. Through this dynamic adjustment, it is ensured that each edge computing unit can process the corresponding image data efficiently and accurately.

[0078] In some embodiments, the edge computing unit performs safety detection based on the highway images collected by the corresponding first image collection unit and the second image collection unit, including:

[0079] Safety detection is performed based on the highway images acquired by the corresponding first image acquisition unit and the second image acquisition unit through the safety detection model, wherein the safety detection model may be a convolutional neural network model.

[0080] Specifically, the safety detection model detects information such as vehicle type, color, license plate number, as well as obstacles, pedestrians, vehicle speed, distance, direction and other abnormal conditions on the road to identify potential traffic safety hazards. When a safety hazard is detected, the edge computing unit immediately triggers the early warning mechanism and sends early warning information to the traffic management center, including the type, location, severity and other information of the safety hazard.

[0081] Figure 2 is a flow chart of a method for intelligent detection of highway traffic safety shown in one embodiment of the present application. Figure 2 As shown, a road traffic safety intelligent detection method may include the following steps:

[0082] Obtain historical highway traffic data for the target area;

[0083] Determine multiple first-level highway traffic safety detection points and multiple second-level highway traffic safety detection points in the target area based on historical highway traffic data of the target area;

[0084] Determine the traffic safety related information of multiple first-class highway traffic safety detection points in the target area based on the historical highway traffic data of the target area;

[0085] Obtaining traffic safety related information corresponding to each first-level highway traffic safety detection point, wherein the traffic safety related information at least includes traffic flow and weather information;

[0086] According to the traffic safety related information corresponding to each first-level highway traffic safety detection point, the plurality of second image acquisition units are controlled;

[0087] Generate highway traffic safety warning information through multiple edge computing units based on the traffic safety related information corresponding to each first-level highway traffic safety detection point and the traffic safety association information of multiple first-level highway traffic safety detection points in the target area;

[0088] Safety detection is performed by multiple edge computing units based on highway images collected by multiple first image acquisition units and multiple second image acquisition units.

[0089] A highway traffic safety intelligent detection method can be applied to a highway traffic safety intelligent detection system. For more descriptions of a highway traffic safety intelligent detection method, please refer to the relevant descriptions of a highway traffic safety intelligent detection system, which will not be repeated here.

[0090] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A highway traffic safety intelligent detection system, characterized in that: include: The detection layout module is used to obtain the historical highway traffic data of the target area, and determine multiple first-level highway traffic safety detection points and multiple second-level highway traffic safety detection points in the target area according to the historical highway traffic data of the target area, including: determining multiple accident points according to the historical highway traffic data of the target area; clustering the multiple accident points according to the highway distance between any two accident points through a clustering algorithm to determine multiple accident point clusters, and determining multiple first-level highway traffic safety detection points according to the multiple accident point clusters; determining multiple first-level highway traffic safety detection point groups according to the highway connectivity relationship of the multiple first-level highway traffic safety detection points, wherein the first-level highway traffic safety detection point group includes two adjacent first-level highway traffic safety detection points connected by the highway; for each first-level highway traffic safety detection point group, determining the second-level highway traffic safety detection point density of the first-level highway traffic safety detection point group according to the accident point cluster corresponding to each first-level highway traffic safety detection point included in the first-level highway traffic safety detection point group, and setting at least one second-level highway traffic safety detection point between two first-level highway traffic safety detection points included in the first-level highway traffic safety detection point group according to the second-level highway traffic safety detection point density of the first-level highway traffic safety detection point group; A detection association module, used to determine traffic safety association information of multiple first-level highway traffic safety detection points in the target area based on historical highway traffic data of the target area; The data collection module includes a data collection unit corresponding to each first-level highway traffic safety detection point, wherein the data collection unit is used to obtain traffic safety related information corresponding to the corresponding first-level highway traffic safety detection point, and the traffic safety related information at least includes vehicle flow and meteorological information; An image acquisition module is used to include an acquisition control unit, a plurality of first image acquisition units set at a plurality of first-level highway traffic safety detection points, and a plurality of second image acquisition units set at a plurality of second-level highway traffic safety detection points, wherein the acquisition control unit is used to control the plurality of second image acquisition units according to the traffic safety related information corresponding to the first-level highway traffic safety detection point acquired by each data acquisition unit, specifically including: for each first-level highway traffic safety detection point, calculating the safety risk value of the first-level highway traffic safety detection point according to the traffic safety related information corresponding to the first-level highway traffic safety detection point; for each first-level highway traffic safety detection point group, judging whether to start the second image acquisition unit corresponding to the first-level highway traffic safety detection point group according to the safety risk value of each first-level highway traffic safety detection point included in the first-level highway traffic safety detection point group; The safety analysis module includes multiple edge computing units, which are used to generate highway traffic safety warning information based on the traffic safety-related information corresponding to the first-level highway traffic safety detection point obtained by each data acquisition unit and the traffic safety association information of multiple first-level highway traffic safety detection points in the target area, and are also used to perform safety detection based on highway images collected by multiple first image acquisition units and multiple second image acquisition units.

2. A highway traffic safety intelligent detection system according to claim 1, characterized in that: The detection association module determines the traffic safety association information of multiple first-level highway traffic safety detection points in the target area according to the historical highway traffic data of the target area, including: For any two first-class highway traffic safety detection points in the target area, the accident co-occurrence parameters of the two first-class highway traffic safety detection points are determined based on the historical highway traffic data of the target area; According to the accident co-occurrence parameters of any two first-level highway traffic safety detection points, the associated first-level highway traffic safety detection points of each first-level highway traffic safety detection point are determined, wherein the traffic safety association information of the multiple first-level highway traffic safety detection points in the target area includes the associated first-level highway traffic safety detection points of each first-level highway traffic safety detection point.

3. A highway traffic safety intelligent detection system according to claim 2, characterized in that: The data acquisition module is provided with a data acquisition unit corresponding to each first-class highway traffic safety detection point, including: For each first-class highway traffic safety checkpoint, the safety impact weight of each meteorological factor corresponding to the first-class highway traffic safety checkpoint is determined based on the historical highway traffic data of the target area. The key meteorological factors corresponding to the first-class highway traffic safety checkpoint are determined based on the safety impact weight of each meteorological factor corresponding to the first-class highway traffic safety checkpoint. Based on the key meteorological factors corresponding to the first-class highway traffic safety checkpoint, a meteorological information collection component is determined, wherein the meteorological information collection component is used to collect meteorological information corresponding to the first-class highway traffic safety checkpoint.

4. A highway traffic safety intelligent detection system according to claim 3, characterized in that: The plurality of edge computing units generate highway traffic safety warning information according to the traffic safety related information corresponding to the primary highway traffic safety detection point acquired by each data collection unit and the traffic safety association information of the plurality of primary highway traffic safety detection points in the target area, including: Determine risk roads within the target area based on the safety risk values ​​of the first-level highway traffic safety detection points and the associated first-level highway traffic safety detection points of each first-level highway traffic safety detection point; The highway traffic safety warning information is generated according to the risky highways in the target area.

5. A highway traffic safety intelligent detection system according to any one of claims 1 to 4, characterized in that: The plurality of edge computing units perform safety detection according to the highway images collected by the plurality of first image collection units and the plurality of second image collection units, including: Determine the first image acquisition unit and the second image acquisition unit corresponding to each edge computing unit according to the status information of the plurality of edge computing units and the control results of the plurality of second image acquisition units; For each edge computing unit, the edge computing unit performs safety detection based on the highway images collected by the corresponding first image acquisition unit and the second image acquisition unit.

6. A highway traffic safety intelligent detection system according to claim 5, characterized in that: The edge computing unit performs safety detection according to the highway image acquired by the corresponding first image acquisition unit and the second image acquisition unit, including: Safety detection is performed using the safety detection model based on the highway images captured by the corresponding first image capture unit and the second image capture unit.

7. A road traffic safety intelligent detection method, characterized in that: A highway traffic safety intelligent detection system applied to any one of claims 1 to 6, comprising: Obtain historical highway traffic data for the target area; Determine a plurality of first-level highway traffic safety detection points and a plurality of second-level highway traffic safety detection points within the target area based on historical highway traffic data of the target area; Determining traffic safety related information of a plurality of first-class highway traffic safety detection points within the target area based on historical highway traffic data of the target area; Obtaining traffic safety related information corresponding to each first-level highway traffic safety detection point, wherein the traffic safety related information at least includes traffic flow and weather information; regulating the plurality of second image acquisition units according to the traffic safety related information corresponding to each first-level highway traffic safety detection point; Generate highway traffic safety warning information through multiple edge computing units according to traffic safety related information corresponding to each first-level highway traffic safety detection point and traffic safety association information of multiple first-level highway traffic safety detection points in the target area; Safety detection is performed by multiple edge computing units based on highway images collected by multiple first image acquisition units and multiple second image acquisition units.

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