CN117854284A

CN117854284A - Vehicle-road cooperative monitoring method and vehicle detector device for complex road environment

Info

Publication number: CN117854284A
Application number: CN202410256737.3A
Authority: CN
Inventors: 陈文倩; 黄卫民; 何玉容; 韩磊; 彭锦庆
Original assignee: Guangzhou Mainchance Communication Technology Co ltd
Current assignee: Guangzhou Mainchance Communication Technology Co ltd
Priority date: 2024-03-07
Filing date: 2024-03-07
Publication date: 2024-04-09
Anticipated expiration: 2044-03-07
Also published as: CN117854284B

Abstract

The invention discloses a vehicle-road collaborative monitoring method and a vehicle detector device for a complex road environment, wherein the method comprises the following steps: acquiring vehicle-mounted information of a target vehicle, and acquiring positioning, running speed, video data and sensing data of the target vehicle according to the vehicle-mounted information; obtaining a corresponding first road condition according to the positioning of the target vehicle; acquiring and obtaining first environmental data of the target vehicle in a positioning preset radius according to the first road condition, the first traffic condition and the first traffic scene; obtaining second environment data according to the video data and the sensing data of the target vehicle; and then, correcting the first environment data through the second environment data so as to obtain the actual environment data of the target vehicle; and transmitting the actual environment data and the vehicle-mounted data of the target vehicle to a cloud server in real time, so that the cooperative monitoring of the vehicle and the road of the target vehicle in the complex road environment is realized.

Description

Vehicle-road cooperative monitoring method and vehicle detector device for complex road environment

Technical Field

The invention relates to the technical field of intelligent traffic, in particular to a vehicle-road collaborative monitoring method and a vehicle detector device for a complex road environment.

Background

The vehicle-road cooperative monitoring adopts advanced wireless communication, new generation internet and other technologies, implements dynamic real-time information interaction among vehicles, roads and vehicles and people in all directions, and develops active safety control and road cooperative management of the vehicles on the basis of full-time empty dynamic traffic information acquisition and fusion, thereby fully realizing effective cooperation of the vehicles and the vehicles, ensuring traffic safety and improving traffic efficiency, and further forming a safe, efficient and environment-friendly road traffic system.

At present, the existing vehicle-road collaborative monitoring can only be used for marks such as highways and city express ways and road sections with clear road standards, but the vehicle-road collaborative monitoring cannot be accurately and efficiently realized for urban roads, multi-bifurcation road sections, mountain road sections, road sections of traffic environments consisting of motor vehicles, non-motor vehicles and pedestrians and the like, and meanwhile, the existing vehicle-road collaborative monitoring depends on road infrastructure due to the fact that the city road conditions have more uncontrollable factors compared with the highways, the city express ways and the like, so that the cost of the vehicle-road collaborative monitoring of complex road environments is high and the monitoring effect is poor.

Disclosure of Invention

The invention provides a vehicle-road collaborative monitoring method and a vehicle detector device for a complex road environment, which are used for solving the technical problems of low accuracy, low monitoring efficiency and high implementation cost of vehicle-road collaborative monitoring for the complex road environment in the prior art.

In order to solve the above technical problems, an embodiment of the present invention provides a vehicle-road collaborative monitoring method for a complex road environment, including:

acquiring vehicle-mounted information of a target vehicle, and acquiring positioning, running speed, video data and sensing data of the target vehicle according to the vehicle-mounted information;

according to the positioning of the target vehicle, obtaining a traffic block where the target vehicle is located, and obtaining a corresponding first road condition according to the traffic block; the traffic blocks are a plurality of, and each traffic block comprises road topology data and first road conditions thereof within a preset range in map navigation data;

acquiring vehicle-mounted information of all vehicles in a preset radius of the traffic zone of the target vehicle, so as to obtain a first traffic condition of the traffic zone of the target vehicle through the vehicle-mounted information of all vehicles; wherein the first traffic condition includes traffic flow information, vehicle type, and travel speed;

obtaining a first traffic scene of the target vehicle under the current positioning according to the road topology data of the traffic block, so as to obtain first environment data of the target vehicle within a positioning preset radius according to the first road condition, the first traffic condition and the first traffic scene;

Analyzing lane identification information and surrounding vehicle identification information of the target vehicle within a preset radius according to the video data of the target vehicle, obtaining road quality, light condition and weather condition of the target vehicle within the preset radius according to the sensing data of the target vehicle, obtaining the second road condition and the second traffic scene according to the lane identification information and the road quality, and obtaining the second traffic condition according to the surrounding vehicle identification information;

obtaining second environment data of the target vehicle in a positioning preset radius according to the second road condition, a second traffic scene and a second traffic condition, and correcting the second environment data and the first environment data through the second environment data so as to obtain actual environment data of the target vehicle;

and transmitting the actual environment data and the vehicle-mounted data of the target vehicle to a cloud server in real time, so that the cooperative monitoring of the vehicle and the road of the target vehicle in the complex road environment is realized.

As a preferred solution, the acquiring vehicle-mounted information of the target vehicle, and obtaining positioning, running speed, video data and sensing data of the target vehicle according to the vehicle-mounted information specifically includes:

Responding to the starting of the target vehicle, and acquiring the identity information of the target vehicle in real time;

the identity of the target vehicle is verified according to the identity information, and after the identity verification is passed, a vehicle-mounted information acquisition request is generated and sent to the target vehicle, so that the target vehicle acquires the vehicle-mounted information acquisition request and feeds back the vehicle-mounted information of the target vehicle, and the vehicle-mounted information of the target vehicle is acquired; the vehicle-mounted information comprises identity information, positioning, running speed, video data and sensing data corresponding to the vehicle.

As a preferred solution, the obtaining a traffic block in which the target vehicle is located according to the positioning of the target vehicle, and obtaining a corresponding first road condition according to the traffic block specifically includes:

according to the positioning of the target vehicle, acquiring a traffic block of the target vehicle in map navigation data, and obtaining corresponding road topology data according to the traffic block;

marking the road topology data according to the road data information stored in a preset road database, so as to obtain a first road condition of the traffic block according to the marked road data information; the road data information comprises road surface quality, road surface width, number of lanes, traffic lights and lane line types.

As a preferred solution, the acquiring the vehicle-mounted information of all vehicles within the preset radius of the target vehicle in the traffic zone, so as to obtain the first traffic condition of the traffic zone where the target vehicle is located through the vehicle-mounted information of all vehicles, specifically includes:

generating a communication request, and sending the communication request to all vehicles of the target vehicle within a preset radius, so that a communication link is established with each vehicle of the target vehicle within the preset radius in sequence;

the method comprises the steps of sequentially obtaining identity information of each vehicle in a preset radius through a communication link, and carrying out identity verification of the vehicle type on each vehicle according to the identity information;

reading information of the vehicles after the identity verification is successful, so as to obtain vehicle-mounted information of all vehicles of the target vehicle in a preset radius in the traffic block;

according to the positioning and running speeds of the target vehicle and all vehicles in a preset radius, calculating traffic flow information in the preset radius of the target vehicle, and according to the traffic flow information, the vehicle type and the running speed, obtaining the first traffic condition; wherein the first traffic condition includes traffic flow information, vehicle type, and travel speed.

As a preferred solution, the obtaining a first traffic scene of the target vehicle under the current positioning according to the road topology data of the traffic block, so as to obtain first environment data of the target vehicle within a positioning preset radius according to the first road condition, the first traffic condition and the first traffic scene, specifically includes:

acquiring an intersection point of each topological line and a position coordinate of each intersection point in the traffic block according to the road topology data of the traffic block;

according to the position coordinates of each intersection point, calculating to obtain the distance between each intersection point and the intersection point of topological connection of each intersection point, taking the intersection point with the distance smaller than or equal to a preset value as the same traffic scene, and taking the intersection point with the distance larger than the preset value as a traffic scene independently;

determining a traffic scene where the target vehicle is located as a first traffic scene according to the current positioning of the target vehicle; the first traffic scene comprises a cross intersection, five or more intersections, a T-shaped intersection and a short-distance double intersection.

As a preferred solution, the analyzing, according to the video data of the target vehicle, obtains lane identification information and surrounding vehicle identification information of the target vehicle within a preset radius, and obtains road quality, light condition and weather condition of the target vehicle within the preset radius according to the sensing data of the target vehicle, and further obtains the second road condition and the second traffic scene according to the lane identification information and the road quality, and obtains the second traffic condition according to the surrounding vehicle identification information, specifically:

Analyzing the video data of the target vehicle frame by frame through a preset lane identification model, and identifying to obtain first lane identification information of the target vehicle within a preset radius;

acquiring the identification of a short wave radar of the target vehicle to a road identification line to obtain the second vehicle lane identification information, and carrying out information fusion on the first vehicle lane identification information and the second vehicle lane identification information to obtain final lane identification information;

identifying and obtaining surrounding vehicles of the target vehicle within a preset radius according to the video data of the target vehicle and the short wave radar, and marking the positions of the identified vehicles, so that the identity information of each vehicle within the preset radius is respectively sent to the corresponding vehicle according to the position marks, and further the surrounding vehicle identification information is obtained;

obtaining the road surface quality of the target vehicle in a preset radius according to the suspension sensing data of the target vehicle, obtaining the light condition according to the light sensing data of the target vehicle, and obtaining the weather condition according to the rainfall sensing data of the target vehicle;

and obtaining a second road condition comprising road surface quality, road surface width and the number of lanes according to the lane identification information and the road surface quality obtained based on the suspension sensing data, and a second traffic scene comprising various intersection types, and obtaining a second traffic condition according to the surrounding vehicle identification information.

As a preferred solution, the obtaining second environmental data of the target vehicle within a positioning preset radius according to the second road condition, the second traffic scene and the second traffic condition, and correcting the first environmental data by the second environmental data, thereby obtaining actual environmental data of the target vehicle specifically includes:

obtaining second environmental data of the target vehicle within a positioning preset radius according to the second road condition, the second traffic scene and the second traffic condition;

and carrying out data correction through the first environmental data and the second environmental data so as to compare the first environmental data with the second environmental data, carrying out mean value calculation on data with phase difference values larger than a preset error range in the first environmental data and the second environmental data, taking the obtained mean value as corrected data, and taking the data with the phase difference value smaller than the preset error range as final data until all the data in the first environmental data and the second environmental data are corrected, and obtaining the actual environmental data of the target vehicle.

Correspondingly, the invention also provides a vehicle detector device, which comprises: the system comprises a vehicle-mounted information module, a road condition module, a traffic scene module, a video sensing module, an environment data module and an uploading module;

The vehicle-mounted information module is used for acquiring vehicle-mounted information of a target vehicle and obtaining positioning, running speed, video data and sensing data of the target vehicle according to the vehicle-mounted information;

the road condition module is used for obtaining a traffic block where the target vehicle is located according to the positioning of the target vehicle, and obtaining a corresponding first road condition according to the traffic block; the traffic blocks are a plurality of, and each traffic block comprises road topology data and first road conditions thereof within a preset range in map navigation data;

the traffic condition module is used for acquiring the vehicle-mounted information of all vehicles in the preset radius of the traffic zone of the target vehicle, so that the first traffic condition of the traffic zone where the target vehicle is located is obtained through the vehicle-mounted information of all vehicles; wherein the first traffic condition includes traffic flow information, vehicle type, and travel speed;

the traffic scene module is used for obtaining a first traffic scene of the target vehicle under the current positioning according to the road topology data of the traffic block, so as to obtain first environment data of the target vehicle within a positioning preset radius according to the first road condition, the first traffic condition and the first traffic scene;

The video sensing module is used for analyzing and obtaining lane identification information and surrounding vehicle identification information of the target vehicle in a preset radius according to video data of the target vehicle, obtaining road quality, light condition and weather condition of the target vehicle in the preset radius according to sensing data of the target vehicle, further obtaining the second road condition and the second traffic scene according to the lane identification information and the road quality, and obtaining the second traffic condition according to the surrounding vehicle identification information;

the environment data module is used for obtaining second environment data of the target vehicle in a positioning preset radius according to the second road condition, a second traffic scene and a second traffic condition, and further correcting the first environment data through the second environment data, so that actual environment data of the target vehicle is obtained;

and the uploading module is used for transmitting the actual environment data and the vehicle-mounted data of the target vehicle to a cloud server in real time, so that the cooperative monitoring of the vehicle and the road of the target vehicle in the complex road environment is realized.

Correspondingly, the invention also provides a terminal device, which comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, wherein the processor realizes the vehicle-road collaborative monitoring method of the complex road environment when executing the computer program.

Accordingly, a computer readable storage medium, the computer readable storage medium comprising a stored computer program, wherein when the computer program runs, the computer readable storage medium is controlled to execute the vehicle-road collaborative monitoring method of the complex road environment according to any one of the above.

Compared with the prior art, the embodiment of the invention has the following beneficial effects:

according to the technical scheme, the position and state information of the target vehicle can be accurately obtained in real time by obtaining the vehicle-mounted information of the target vehicle, including positioning, running speed, video data and sensing data. Meanwhile, according to road topology data of the traffic block and road conditions in a preset range, the first road condition of the traffic block where the target vehicle is located can be obtained, the accuracy of monitoring is further improved, and the first traffic condition of the traffic block where the target vehicle is located can be obtained rapidly by acquiring vehicle-mounted information of all vehicles in a preset radius of the traffic block, wherein the first traffic condition comprises traffic flow information, vehicle type, running speed and the like, so that the traffic condition of the area where the target vehicle is located can be known in real time, the efficiency of monitoring is improved, and the cooperative monitoring of the vehicle and the road of the target vehicle in a complex road environment can be realized by transmitting actual environment data and vehicle-mounted data of the target vehicle to a cloud server in real time. Compared with the traditional manual patrol or a large number of cameras and the like, the method reduces implementation cost and can monitor a plurality of target vehicles.

Further, by acquiring actual environment data of the target vehicle, including road conditions, traffic scenes and the like, the environment where the target vehicle is located can be analyzed and evaluated in real time, early warning information can be sent out timely, a driver can be helped to make corresponding decisions, and traffic accidents are avoided. Meanwhile, the condition and the running condition of the whole traffic system can be known by collecting and analyzing the vehicle-mounted data of a large number of vehicles, data support can be provided for traffic management departments, traffic planning and optimization management can be performed, the overall traffic efficiency and safety are improved, and the information such as the driving habit, the preference and the demand of a user can be known by analyzing the vehicle-mounted data of a target vehicle, personalized services such as recommending an optimal route, providing real-time weather information and the like can be provided for the user, and the travel experience of the user is improved.

Drawings

Fig. 1: the step flow chart of the vehicle-road collaborative monitoring method of the complex road environment provided by the embodiment of the invention;

fig. 2: the embodiment of the invention provides a structural schematic diagram of a vehicle detector device.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Example 1

Referring to fig. 1, a vehicle-road collaborative monitoring method for a complex road environment provided by an embodiment of the present invention includes the following steps S101-S107:

step S101: and acquiring the vehicle-mounted information of the target vehicle, and acquiring the positioning, the running speed, the video data and the sensing data of the target vehicle according to the vehicle-mounted information.

As a preferred solution of this embodiment, the acquiring vehicle-mounted information of the target vehicle, and obtaining, according to the vehicle-mounted information, positioning, running speed, video data and sensing data of the target vehicle specifically includes:

responding to the starting of the target vehicle, and acquiring the identity information of the target vehicle in real time; the identity of the target vehicle is verified according to the identity information, and after the identity verification is passed, a vehicle-mounted information acquisition request is generated and sent to the target vehicle, so that the target vehicle acquires the vehicle-mounted information acquisition request and feeds back the vehicle-mounted information of the target vehicle, and the vehicle-mounted information of the target vehicle is acquired; the vehicle-mounted information comprises identity information, positioning, running speed, video data and sensing data corresponding to the vehicle.

In this embodiment, after the target vehicle is started, the system acquires the identity information of the target vehicle in real time. The identity information can comprise license plate numbers, vehicle types and the like of the vehicles, and the system performs identity verification on the target vehicles according to the acquired identity information of the target vehicles. Wherein authentication may be achieved by interaction with a vehicle management system or a third party authentication platform. Thus, after passing the authentication, the system generates a vehicle-mounted information acquisition request and transmits the vehicle-mounted information acquisition request to the target vehicle. Preferably, the vehicle-mounted information acquisition request includes specific content of the vehicle-mounted information to be acquired, such as identity information, positioning, running speed, video data, sensing data and the like.

In this embodiment, after receiving the vehicle-mounted information acquisition request, the target vehicle feeds back its vehicle-mounted information to the system according to the request. The in-vehicle information may be transmitted to the system via wireless communication technology, for example using an in-vehicle communication module or a wireless network connection.

In this embodiment, after the system receives the vehicle-mounted information of the target vehicle, further processing and analysis may be performed. For example, on-board information is stored in a database for subsequent monitoring and management; or the vehicle-mounted information is integrated with other related data, so that more comprehensive traffic analysis and decision support are provided.

In the embodiment, the vehicle-mounted information of the target vehicle is acquired in real time, so that the state and the position of the vehicle can be known in time, and the monitoring and management efficiency of the vehicle is improved. By carrying out identity verification on the target vehicle, the authenticity and the accuracy of the acquired vehicle-mounted information can be ensured, and the interference of false data is prevented. Meanwhile, the acquisition and the use of the vehicle-mounted information can provide important data support for traffic management departments, are used for traffic planning, congestion monitoring, accident handling and other aspects, and improve the overall traffic management effect. And the integration and analysis of the vehicle-mounted information can provide more comprehensive traffic situation awareness and prediction capability, and help decision makers to make more accurate decisions and plans.

Step S102: according to the positioning of the target vehicle, obtaining a traffic block where the target vehicle is located, and obtaining a corresponding first road condition according to the traffic block; the traffic blocks are a plurality of traffic blocks, and each traffic block comprises road topology data and first road conditions thereof within a preset range in map navigation data.

As a preferred solution of this embodiment, the obtaining, according to the positioning of the target vehicle, a traffic block in which the target vehicle is located, and obtaining, according to the traffic block, a corresponding first road condition, specifically includes:

according to the positioning of the target vehicle, acquiring a traffic block of the target vehicle in map navigation data, and obtaining corresponding road topology data according to the traffic block; marking the road topology data according to the road data information stored in a preset road database, so as to obtain a first road condition of the traffic block according to the marked road data information; the road data information comprises road surface quality, road surface width, number of lanes, traffic lights and lane line types.

In this embodiment, determining, by the positioning information of the target vehicle, the traffic block to which the target vehicle belongs in the map navigation data may be implemented by interacting with the map navigation database to obtain the geographic coordinates of the location of the target vehicle and the surrounding road information. And obtaining corresponding road topology data from a preset road database according to the determined traffic block. Preferably, the road topology data includes a connection relationship of the road, intersection information, a link length, and the like. And comparing and marking the road topology data with the road data information stored in the preset road database. The road data information may include information such as road quality, road width, number of lanes, traffic lights, and lane line type. The road data information of each road in the traffic block can be obtained through comparison and labeling. And finally, obtaining the first road condition of the traffic block through the marked road data information. The first road condition may include information of the quality, width, number of lanes, and traffic signal and lane line type of the road, which may be used to analyze and evaluate traffic conditions, providing real-time navigation and road condition cues.

In the present embodiment, the road topology data includes, but is not limited to: road connection relation, road type, lane information, traffic lights, intersection information, road section information and the like. The road connection relation comprises: the connection manner between roads, such as intersections, entrances and exits, etc., is described. The road types include: the type of road is identified, such as expressway, arterial road, secondary arterial road, etc. The lane information includes: including information on the number of lanes, lane direction, lane width, etc. The traffic signal lamp includes: and recording the information such as the position, the type and the like of the traffic signal lamp. The intersection information includes: detailed information describing the shape of the intersection, turning rules, etc. The link information includes: and recording the information such as the length, speed limit and the like of the road section.

In this embodiment, the data types can be largely classified into two types, vector data and attribute data. The vector data includes geometric elements such as points, lines, planes, etc. for representing spatial entities such as roads, traffic lights, intersections, etc. in the road network, for example, the roads may be line segments, and the traffic lights and intersections may be points. The attribute data includes specific attributes for describing the vector data, such as the name, length, speed limit, etc. of the road.

In this embodiment, by acquiring the positioning information of the target vehicle, the traffic block in which the target vehicle is located can be accurately determined, and the perception capability of the traffic condition is improved. The traffic blocks are marked by utilizing the road data information in the preset road database, so that detailed road attribute information such as road quality, road width, number of lanes and the like can be provided, and more accurate navigation and road condition prompt can be provided for a driver. Meanwhile, by analyzing and evaluating the road data information of each road in the traffic block, the problems and hidden dangers on the road can be found in time, and the traffic safety is improved. In addition, the embodiment can provide important data support for traffic management departments, is used for traffic planning, congestion monitoring, accident handling and other aspects, and improves the overall traffic management effect.

Step S103: acquiring vehicle-mounted information of all vehicles in a preset radius of the traffic zone of the target vehicle, so as to obtain a first traffic condition of the traffic zone of the target vehicle through the vehicle-mounted information of all vehicles; wherein the first traffic condition includes traffic flow information, vehicle type, and travel speed.

As a preferred solution of this embodiment, the acquiring the vehicle-mounted information of all vehicles within the preset radius of the target vehicle in the traffic zone, so as to obtain, through the vehicle-mounted information of all vehicles, the first traffic condition of the traffic zone in which the target vehicle is located, specifically includes:

generating a communication request, and sending the communication request to all vehicles of the target vehicle within a preset radius, so that a communication link is established with each vehicle of the target vehicle within the preset radius in sequence; the method comprises the steps of sequentially obtaining identity information of each vehicle in a preset radius through a communication link, and carrying out identity verification of the vehicle type on each vehicle according to the identity information; reading information of the vehicles after the identity verification is successful, so as to obtain vehicle-mounted information of all vehicles of the target vehicle in a preset radius in the traffic block; according to the positioning and running speeds of the target vehicle and all vehicles in a preset radius, calculating traffic flow information in the preset radius of the target vehicle, and according to the traffic flow information, the vehicle type and the running speed, obtaining the first traffic condition; wherein the first traffic condition includes traffic flow information, vehicle type, and travel speed.

In the present embodiment, the communication request is generated and transmitted to all vehicles of the target vehicle within the preset radius. The communication request may be sent to the target vehicle via a wireless communication technology (e.g., bluetooth, wi-Fi, etc.). Further, a communication link is established with each vehicle of the target vehicle within a preset radius in turn, and upon receipt of a communication request, the vehicle may reply with a confirmation message, thereby establishing a communication link with the system. Meanwhile, through the established communication link, the system sequentially acquires the identity information of each vehicle within the preset radius. The identity information may include a unique identifier of the vehicle, a license plate number, etc.

In this embodiment, further, identity verification of the vehicle type is performed on each vehicle through the acquired identity information. The system can store information of the vehicle type in advance, and judge whether the vehicle type is legal or not through comparison so as to read the information of the vehicle after the identity verification is successful. The system can read the vehicle-mounted information of the vehicle, including position, speed, acceleration and other data. Further, traffic information in a preset radius of the target vehicle is calculated based on the positioning and traveling speeds of the target vehicle and all vehicles in the preset radius. The traffic flow information may represent the number of vehicles passing through a certain area per unit time. And finally, obtaining a first traffic condition within a preset radius in the traffic zone where the target vehicle is located according to the traffic flow information, the vehicle type and the running speed. The first traffic condition may be used to evaluate a road congestion level, predict a traffic accident risk, etc.

In this embodiment, information of vehicles surrounding the target vehicle, including the position, the speed, and the like, is acquired in real time, which contributes to improvement of traffic safety. By calculating the traffic flow information and analyzing the type and the running speed of the vehicle, real-time traffic condition assessment and prediction can be provided to help a driver to make reasonable driving decisions. Meanwhile, based on data collection and analysis of vehicle-mounted information, real-time and accurate data support can be realized, and the vehicle-mounted information is used for traffic planning, congestion monitoring, accident handling and other aspects, so that the overall traffic management effect is improved.

Step S104: and obtaining a first traffic scene of the target vehicle under the current positioning according to the road topology data of the traffic block, so as to obtain first environment data of the target vehicle within a positioning preset radius according to the first road condition, the first traffic condition and the first traffic scene.

As a preferred solution of this embodiment, the obtaining, according to the road topology data of the traffic zone, a first traffic scene of the target vehicle under the current positioning, so as to obtain, according to the first road condition, the first traffic condition and the first traffic scene, first environmental data of the target vehicle within a positioning preset radius, specifically includes:

Acquiring an intersection point of each topological line and a position coordinate of each intersection point in the traffic block according to the road topology data of the traffic block; according to the position coordinates of each intersection point, calculating to obtain the distance between each intersection point and the intersection point of topological connection of each intersection point, taking the intersection point with the distance smaller than or equal to a preset value as the same traffic scene, and taking the intersection point with the distance larger than the preset value as a traffic scene independently; determining a traffic scene where the target vehicle is located as a first traffic scene according to the current positioning of the target vehicle; the first traffic scene comprises a cross intersection, five or more intersections, a T-shaped intersection and a short-distance double intersection.

In this embodiment, road network data of the target traffic block, including connection relation of roads, intersection information, and the like, is acquired through a map API or other related data sources. And further acquiring the intersection point and the position coordinate of each topological line, specifically analyzing the line segments of each road according to the road topological data, finding the intersection point of the line segments, and recording the position coordinate of each intersection point.

Further, the distance between each intersection point and its neighboring intersection point is calculated using a geographical distance formula or a correlation algorithm, for example: calculation modes such as Euclidean distance and the like. And further, according to a preset distance threshold, regarding the intersection point with the distance smaller than or equal to the threshold as the same traffic scene. These intersections may be cross intersections, five-way and above intersections, T-intersections, or short-range double intersections. Finally, determining the traffic scene of the target vehicle, so that the scene closest to the target vehicle is selected from the determined traffic scenes as the first traffic scene according to the current positioning information of the target vehicle.

It should be noted that, the position coordinates of the intersection may be corresponding coordinate information obtained according to an initial coordinate system of the position corresponding to each traffic block, or may be longitude and latitude information.

Step S105: according to the video data of the target vehicle, analyzing and obtaining lane identification information and surrounding vehicle identification information of the target vehicle in a preset radius, according to the sensing data of the target vehicle, obtaining road quality, light condition and weather condition of the target vehicle in the preset radius, further obtaining the second road condition and the second traffic scene according to the lane identification information and the road quality, and obtaining the second traffic condition according to the surrounding vehicle identification information.

As a preferred solution of this embodiment, the analyzing, according to the video data of the target vehicle, obtains lane identification information and surrounding vehicle identification information of the target vehicle within a preset radius, and obtains, according to the sensing data of the target vehicle, road quality, light condition and weather condition of the target vehicle within the preset radius, and further obtains the second road condition and the second traffic scene according to the lane identification information and the road quality, and obtains the second traffic condition according to the surrounding vehicle identification information, specifically:

Analyzing the video data of the target vehicle frame by frame through a preset lane identification model, and identifying to obtain first lane identification information of the target vehicle within a preset radius; acquiring the identification of a short wave radar of the target vehicle to a road identification line to obtain the second vehicle lane identification information, and carrying out information fusion on the first vehicle lane identification information and the second vehicle lane identification information to obtain final lane identification information; identifying and obtaining surrounding vehicles of the target vehicle within a preset radius according to the video data of the target vehicle and the short wave radar, and marking the positions of the identified vehicles, so that the identity information of each vehicle within the preset radius is respectively sent to the corresponding vehicle according to the position marks, and further the surrounding vehicle identification information is obtained; obtaining the road surface quality of the target vehicle in a preset radius according to the suspension sensing data of the target vehicle, obtaining the light condition according to the light sensing data of the target vehicle, and obtaining the weather condition according to the rainfall sensing data of the target vehicle; and obtaining a second road condition comprising road surface quality, road surface width and the number of lanes according to the lane identification information and the road surface quality obtained based on the suspension sensing data, and a second traffic scene comprising various intersection types, and obtaining a second traffic condition according to the surrounding vehicle identification information.

In this embodiment, for the establishment of the lane recognition model, a large amount of vehicle video data may be collected first and labeled, including information such as lanes where the vehicle is located, road types, and the like. Then, a lane recognition model is trained by using a machine learning algorithm (such as a convolutional neural network) so that the lane recognition model can accurately recognize the lane where the vehicle is located according to the input video data. And then inputting the video data of the target vehicle into the trained lane recognition model, and analyzing each frame to obtain the first lane recognition information of the target vehicle within the preset radius.

In this embodiment, for the road identification line identification of the short-wave radar, the short-wave radar device mounted on the target vehicle may be used to identify the road identification line, so as to obtain the second road identification information. And then the first lane identification information and the second lane identification information are subjected to information fusion, and the final lane identification information is obtained through algorithm processing. The accuracy of information fusion can be improved by using a Kalman filter or other methods. And simultaneously, identifying and obtaining surrounding vehicles of the target vehicle within a preset radius according to video data of the target vehicle and the short wave radar, and marking the positions of the identified vehicles.

In this embodiment, according to the position mark, the identity information of each vehicle within the preset radius is sent to the corresponding vehicle, so as to obtain the identification information of surrounding vehicles. The road surface quality, the light condition and the weather condition can be obtained according to the suspension sensing data of the target vehicle, and the road surface quality of the target vehicle in the preset radius can be obtained; the light condition can be obtained according to the light sensing data; weather conditions can be obtained according to the rainfall sensing data. Finally, according to the lane identification information and the road surface quality obtained based on the suspension sensing data, a second road condition including the road surface quality, the road surface width and the number of lanes can be obtained; the second traffic condition may be derived from the identification information of the surrounding vehicles.

In this embodiment, the driver can better grasp the road condition through accurate lane recognition and recognition of surrounding vehicles, thereby avoiding traffic accidents. And further, by acquiring information such as road surface quality, light conditions, weather conditions and the like, real-time traffic information can be provided for a driver, and the driver is helped to make more reasonable driving decisions. By acquiring the identification information and traffic conditions of surrounding vehicles, the road traffic condition can be better known, and the traffic planning and management strategies can be optimized.

Step S106: and obtaining second environmental data of the target vehicle in a positioning preset radius according to the second road condition, the second traffic scene and the second traffic condition, and correcting the first environmental data through the second environmental data, so as to obtain actual environmental data of the target vehicle.

As a preferred solution of this embodiment, the obtaining, according to the second road condition, the second traffic scene, and the second traffic condition, second environmental data of the target vehicle within a positioning preset radius, and further correcting, by the second environmental data, the first environmental data, thereby obtaining actual environmental data of the target vehicle, specifically includes:

obtaining second environmental data of the target vehicle within a positioning preset radius according to the second road condition, the second traffic scene and the second traffic condition; and carrying out data correction through the first environmental data and the second environmental data so as to compare the first environmental data with the second environmental data, carrying out mean value calculation on data with phase difference values larger than a preset error range in the first environmental data and the second environmental data, taking the obtained mean value as corrected data, and taking the data with the phase difference value smaller than the preset error range as final data until all the data in the first environmental data and the second environmental data are corrected, and obtaining the actual environmental data of the target vehicle.

In this embodiment, second environmental data of the target vehicle within the positioning preset radius is obtained through the second road condition, the second traffic scene and the second traffic condition, and specifically, data acquisition can be performed through devices such as a sensor and a camera. Further, the first environmental data and the second environmental data are compared, and a phase difference value between them is calculated. If the difference value is larger than the preset error range, carrying out average value calculation on the item of data, and taking the obtained average value as corrected data. And if the difference value is smaller than the preset error range, taking the second environment data as final data. And repeatedly executing the steps until all the data in the first environment data and the second environment data are corrected, so that the obtained actual environment data of the target vehicle can be ensured to be more accurate and reliable. And finally, analyzing and applying the corrected actual environment data. For example, the method can be used for decision making of an automatic driving system, so that driving safety is improved; and can also be used for traffic planning and optimization.

Further, by correcting errors of the first environmental data and the second environmental data, more accurate environmental data can be obtained, thereby improving accuracy of subsequent analysis and decision. For an automatic driving system, accurate environmental data can improve the perceptibility and decision-making capability of the system, thereby improving the overall performance. Meanwhile, accurate environmental data can provide better reference basis, so that more reasonable traffic planning and optimizing measures are made, traffic efficiency is improved, and congestion is reduced.

Step S107: and transmitting the actual environment data and the vehicle-mounted data of the target vehicle to a cloud server in real time, so that the cooperative monitoring of the vehicle and the road of the target vehicle in the complex road environment is realized.

In the present embodiment, a sensor and an in-vehicle apparatus for collecting actual environmental data and in-vehicle data may be mounted on the target vehicle. These sensors may include GPS locators, temperature sensors, humidity sensors, and the like. And then the acquired actual environment data and vehicle-mounted data are transmitted to the cloud server through a wireless network. Data transmission may be performed using a mobile network (e.g., 4G/5G) or a Wi-Fi network. Meanwhile, after receiving the data transmitted in real time, the cloud server stores the data in a database, wherein the data can be stored by using a relational database or a non-relational database, and a proper database type is selected according to actual requirements.

Further, the cloud server processes and analyzes the stored data. Data analysis algorithms and models can be used to extract useful information and insight and to conduct further analysis and prediction. And simultaneously, the processed and analyzed data are displayed to a user in a visual mode, wherein the data can be presented in a webpage interface, a mobile application and other modes, so that the user can intuitively know the state and the environmental condition of the vehicle. In addition, data can be shared for use by other systems or applications according to user requirements. For example, the data may be provided to traffic management for traffic planning and optimization, or to insurance companies for vehicle insurance pricing, etc. In the whole data transmission and storage process, corresponding security measures are needed to protect confidentiality and integrity of data, and encryption algorithm, access control and other means can be used to ensure the security of the data.

The implementation of the above embodiment has the following effects:

Example two

Referring to fig. 2, a vehicle detector device provided by the present invention includes: a vehicle information module 201, a road condition module 202, a traffic condition module 203, a traffic scene module 204, a video sensing module 205, an environmental data module 206, and an upload module 207.

The vehicle-mounted information module 201 is configured to obtain vehicle-mounted information of a target vehicle, and obtain positioning, running speed, video data and sensing data of the target vehicle according to the vehicle-mounted information;

the road condition module 202 is configured to obtain a traffic block in which the target vehicle is located according to the positioning of the target vehicle, and obtain a corresponding first road condition according to the traffic block; the traffic blocks are a plurality of, and each traffic block comprises road topology data and first road conditions thereof within a preset range in map navigation data;

the traffic condition module 203 is configured to obtain vehicle-mounted information of all vehicles within a preset radius of the traffic zone, so as to obtain a first traffic condition of the traffic zone where the target vehicle is located according to the vehicle-mounted information of all vehicles; wherein the first traffic condition includes traffic flow information, vehicle type, and travel speed;

The traffic scene module 204 is configured to obtain, according to road topology data of the traffic block, a first traffic scene of the target vehicle under the current location, so as to obtain, according to the first road condition, the first traffic condition, and the first traffic scene, first environmental data of the target vehicle within a location preset radius;

the video sensing module 205 is configured to parse and obtain, according to video data of the target vehicle, lane identification information and surrounding vehicle identification information of the target vehicle within a preset radius, and obtain, according to sensing data of the target vehicle, road quality, light condition and weather condition of the target vehicle within the preset radius, and further obtain, according to the lane identification information and the road quality, the second road condition and a second traffic scene, and obtain, according to the surrounding vehicle identification information, a second traffic condition;

the environmental data module 206 is configured to obtain second environmental data of the target vehicle within a positioning preset radius according to the second road condition, the second traffic scene and the second traffic condition, and further correct the second environmental data with the first environmental data, so as to obtain actual environmental data of the target vehicle;

The uploading module 207 is configured to transmit the actual environment data and the vehicle-mounted data of the target vehicle to a cloud server in real time, so as to realize cooperative monitoring of a vehicle path of the target vehicle in a complex road environment.

It will be clear to those skilled in the art that, for convenience and brevity of description, reference may be made to the corresponding process in the foregoing method embodiment for the specific working process of the above-described apparatus, which is not described herein again.

The implementation of the above embodiment has the following effects:

Example III

Correspondingly, the invention also provides a terminal device, comprising: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the vehicle-road co-monitoring method of the complex road environment according to any one of the embodiments above when the computer program is executed.

The terminal device of this embodiment includes: a processor, a memory, a computer program stored in the memory and executable on the processor, and computer instructions. The processor, when executing the computer program, implements the steps of the first embodiment described above, such as steps S101 to S107 shown in fig. 1. Alternatively, the processor, when executing the computer program, performs the functions of the modules/units of the apparatus embodiments described above, such as the video sensing module 205.

The computer program may be divided into one or more modules/units, which are stored in the memory and executed by the processor to accomplish the present invention, for example. The one or more modules/units may be a series of computer program instruction segments capable of performing the specified functions, which instruction segments are used for describing the execution of the computer program in the terminal device. For example, the video sensing module 205 is configured to analyze, according to the video data of the target vehicle, lane identification information and surrounding vehicle identification information of the target vehicle within a preset radius, obtain, according to the sensing data of the target vehicle, road quality, light condition and weather condition of the target vehicle within the preset radius, further obtain, according to the lane identification information and the road quality, the second road condition and the second traffic scene, and obtain, according to the surrounding vehicle identification information, the second traffic condition.

The terminal equipment can be computing equipment such as a desktop computer, a notebook computer, a palm computer, a cloud server and the like. The terminal device may include, but is not limited to, a processor, a memory. It will be appreciated by those skilled in the art that the schematic diagram is merely an example of a terminal device and does not constitute a limitation of the terminal device, and may include more or less components than illustrated, or may combine some components, or different components, e.g., the terminal device may further include an input-output device, a network access device, a bus, etc.

The processor may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is a control center of the terminal device, and which connects various parts of the entire terminal device using various interfaces and lines.

The memory may be used to store the computer program and/or the module, and the processor may implement various functions of the terminal device by running or executing the computer program and/or the module stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the mobile terminal, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.

Wherein the terminal device integrated modules/units may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as stand alone products. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.

Example IV

Correspondingly, the invention further provides a computer readable storage medium, which comprises a stored computer program, wherein the computer program is used for controlling equipment where the computer readable storage medium is located to execute the vehicle-road collaborative monitoring method of the complex road environment according to any one of the embodiments.

The foregoing embodiments have been provided for the purpose of illustrating the general principles of the present invention, and are not to be construed as limiting the scope of the invention. It should be noted that any modifications, equivalent substitutions, improvements, etc. made by those skilled in the art without departing from the spirit and principles of the present invention are intended to be included in the scope of the present invention.

Claims

1. A vehicle-road cooperative monitoring method of a complex road environment is characterized by comprising the following steps:

analyzing lane identification information and surrounding vehicle identification information of the target vehicle within a preset radius according to the video data of the target vehicle, obtaining road quality, light condition and weather condition of the target vehicle within the preset radius according to the sensing data of the target vehicle, obtaining a second road condition and a second traffic scene according to the lane identification information and the road quality, and obtaining a second traffic condition according to the surrounding vehicle identification information;

2. The vehicle-road collaborative monitoring method of the complex road environment according to claim 1, wherein the obtaining vehicle-mounted information of a target vehicle and obtaining positioning, running speed, video data and sensing data of the target vehicle according to the vehicle-mounted information comprises the following specific steps:

3. The vehicle-road collaborative monitoring method according to claim 2, wherein the obtaining a traffic block in which the target vehicle is located according to the positioning of the target vehicle, and obtaining a corresponding first road condition according to the traffic block, specifically comprises:

4. The method for collaborative monitoring of a vehicle road in a complex road environment according to claim 3, wherein the obtaining the vehicle-mounted information of all vehicles within a preset radius of the target vehicle in the traffic zone, so as to obtain the first traffic condition of the traffic zone in which the target vehicle is located through the vehicle-mounted information of all vehicles, specifically comprises:

5. The method for collaborative monitoring of a vehicle and a road in a complex road environment according to claim 4, wherein the method for collaborative monitoring of a vehicle and a road in a complex road environment according to road topology data of the traffic zone is characterized in that a first traffic scene of the target vehicle in a current location is obtained, so that first environmental data of the target vehicle in a location preset radius is obtained according to the first road condition, the first traffic condition and the first traffic scene, specifically:

6. The method for collaborative monitoring of a vehicle and a road according to claim 5, wherein the method for collaborative monitoring of a vehicle and a road according to the video data of the target vehicle is characterized in that the method comprises the steps of analyzing lane identification information and surrounding vehicle identification information of the target vehicle within a preset radius, obtaining road quality, light condition and weather condition of the target vehicle within the preset radius according to the sensing data of the target vehicle, obtaining a second road condition and a second traffic scene according to the lane identification information and the road quality, and obtaining a second traffic condition according to the surrounding vehicle identification information, wherein the method comprises the following steps:

acquiring the identification of a short wave radar of the target vehicle to a road identification line to obtain second lane identification information, and carrying out information fusion on the first lane identification information and the second lane identification information to obtain final lane identification information;

7. The vehicle-road collaborative monitoring method according to claim 6, wherein the second environmental data of the target vehicle within a positioning preset radius is obtained according to the second road condition, the second traffic scene and the second traffic condition, and further the second environmental data and the first environmental data are corrected to obtain actual environmental data of the target vehicle, specifically:

8. A vehicle detector device, comprising: the system comprises a vehicle-mounted information module, a road condition module, a traffic scene module, a video sensing module, an environment data module and an uploading module;

the video sensing module is used for analyzing and obtaining lane identification information and surrounding vehicle identification information of the target vehicle in a preset radius according to the video data of the target vehicle, obtaining road quality, light condition and weather condition of the target vehicle in the preset radius according to the sensing data of the target vehicle, further obtaining a second road condition and a second traffic scene according to the lane identification information and the road quality, and obtaining a second traffic condition according to the surrounding vehicle identification information;

9. A terminal device comprising a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the vehicle road co-monitoring method of a complex road environment according to any one of claims 1 to 7 when the computer program is executed.

10. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored computer program, wherein the computer program when run controls a device in which the computer readable storage medium is located to perform the vehicle road co-monitoring method of the complex road environment according to any one of claims 1 to 7.