Method and device for judging violation of vehicle lane

Abstract

The invention discloses a vehicle lane violation judgment method and device, and relates to the technical field of vehicle lane recognition. The method comprises the following steps: receiving a monitoring request sent by a user; sending a working instruction to laser radar equipment according to the monitoring request, so that the laser radar equipment sends a first laser signal to the target vehicle; receiving a second laser signal fed back by the laser radar equipment, wherein the second laser signal is a signal reflected by the target vehicle according to the first laser signal; target vehicle shape information is determined according to the second laser signal; determining a target vehicle type based on the target vehicle shape information; determining a preset first vehicle type according to the laser radar equipment; and when the target vehicle type does not exist in the preset first vehicle types, determining that the target vehicle is in a lane violation abnormal state, and sending the lane violation abnormal state to the user, so that the user processes the target vehicle. By implementing the technical scheme provided by the invention, the problem of inaccurate image recognition caused by poor image acquisition quality is effectively solved.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle lane recognition, and in particular to a method and device for determining a traffic violation in a vehicle lane. Background Art

[0002] With the continuous evolution of technology and the continuous expansion of its application scope, accurate monitoring of vehicle driving status has become a core element to ensure road traffic safety and operational efficiency. In order to achieve smooth flow of road traffic, the road system is carefully planned into multiple specific lanes to provide optimal driving paths for different types of vehicles. Given that each lane has clear regulations on the type of vehicles passing through, if a vehicle mistakenly enters an unsuitable lane, it will not only seriously disrupt normal traffic flow, but may also directly induce traffic accidents, thereby posing a major risk to public safety.

[0003] Accurately identifying vehicles traveling in lanes is the cornerstone of building a traffic safety defense line. Currently, vehicle identification technology mainly relies on image recognition methods, which capture image information of vehicle types and lanes they occupy, and then use image recognition algorithms to conduct in-depth analysis of the obtained images, and output judgment conclusions based on the analysis results. However, when the image acquisition quality is impaired due to various factors (such as insufficient light, the presence of obstructions, or equipment failure, etc.), resulting in insufficient image clarity, it will affect the accuracy of image recognition technology.

[0004] Therefore, there is an urgent need for a method and device for determining a lane violation of a vehicle that can solve the above-mentioned technical problems. Summary of the invention

[0005] The present application provides a method and device for determining lane violations of vehicles. The method uses a laser radar device to identify the vehicle and monitor whether the vehicle has lane violations, thereby significantly improving the accuracy of identification and effectively solving the problem of inaccurate image recognition due to poor image acquisition quality.

[0006] In the first aspect, the present application provides a method for determining traffic violations in vehicle lanes, which is applied to a server, and the method includes: receiving a monitoring request sent by a user, the monitoring request being a request for traffic violation monitoring of vehicles traveling in a first lane; sending a work instruction to a laser radar device according to the monitoring request, so that the laser radar device sends a first laser signal to a target vehicle; receiving a second laser signal fed back by the laser radar device, the second laser signal being a signal reflected by the target vehicle based on the first laser signal; determining the appearance information of the target vehicle according to the second laser signal; determining the type of the target vehicle based on the appearance information of the target vehicle, the target vehicle types including bus type, truck type and passenger car type; determining a preset first vehicle type according to the laser radar device, and judging whether the target vehicle type exists in the preset first vehicle type; when the target vehicle type does not exist in the preset first vehicle type, confirming that the target vehicle is in a lane violation abnormal state, and sending the lane violation abnormal state to the user so that the user can handle the target vehicle.

[0007] By adopting the above technical scheme, a laser radar device is used to emit a first laser signal to the target vehicle according to a monitoring request, and a second laser signal reflected from the target vehicle is received. The shape of the target vehicle is determined based on the flight time and direction of the laser beam, the appearance information of the target vehicle is determined based on the second laser signal, and the type of the target vehicle is determined based on the appearance information of the target vehicle. The target vehicle type is then compared with a preset first vehicle type. When the target vehicle type does not exist in the preset first vehicle type, it is confirmed that the target vehicle is in an abnormal lane violation state. The laser radar is not limited by environmental conditions and can accurately determine the vehicle type and the lane it occupies, effectively solving the problem of inaccurate image recognition due to poor image acquisition quality.

[0008] Optionally, before sending a work instruction to the laser radar device according to the monitoring request so that the laser radar device sends a first laser signal to the target vehicle, the method also includes: acquiring a first image corresponding to the first lane; processing the first image to obtain an image to be detected; performing vehicle detection on the image to be detected to obtain vehicle information; and determining that the target vehicle is traveling on the first vehicle based on the vehicle information.

[0009] By adopting the above technical solution, the first image of the first lane is acquired in real time, and the first image is processed to detect the vehicle. Vehicle detection is performed on the image to be detected, and relevant information of the vehicle can be accurately extracted. The driving condition of the target vehicle in the first lane can be determined based on the vehicle information, and the vehicle driving in the first lane can be detected in time, reducing the need for manual intervention.

[0010] Optionally, determining the target vehicle appearance information according to the second laser signal; specifically comprising: The target vehicle is scanned according to the second laser signal to obtain three-dimensional point cloud data; the three-dimensional point cloud data is processed to obtain processed three-dimensional point cloud data; the processed three-dimensional point cloud data is extracted to obtain target shape features, the target shape features include length features, height features, width features and window area features, and the target shape features are output as target vehicle shape information.

[0011] By adopting the above technical solution, using laser radar equipment to obtain three-dimensional point cloud data, and processing the three-dimensional point cloud data, noise and errors can be eliminated, and the processed three-dimensional point cloud data can be extracted to obtain target shape features. According to the target shape features, the structure and characteristics of the vehicle can be fully understood, providing an accurate basis for vehicle identification and classification. The entire processing process is automated, without the need for human intervention, and can quickly and accurately complete the extraction of vehicle shape features, thereby improving work efficiency.

[0012] Optionally, after determining the target vehicle's appearance information according to the second laser signal, the method also includes: determining target height data according to the target vehicle's appearance information, the target height data being height data corresponding to the target vehicle; judging whether the target height data is less than or equal to a preset height threshold, the preset height threshold being the passable height data corresponding to the first lane; when the target height data is greater than the preset height threshold, confirming that the target vehicle is in an abnormal state of super-height violation, and sending the abnormal state of super-height violation to the user.

[0013] By adopting the above technical solution, the target height data is determined according to the shape information of the target vehicle. The target height data can accurately reflect the actual height of the target vehicle. By comparing the target height data with the preset height threshold, it is possible to accurately determine whether the target vehicle is overheight, thereby avoiding false alarms caused by measurement errors. The height of vehicles on the lane is monitored in real time. Once an overheight violation occurs, the violation information is sent to the user so that corresponding measures can be taken in time, thereby effectively maintaining traffic safety.

[0014] Optionally, when the target vehicle type does not exist in the preset first vehicle type, after confirming that the target vehicle is in a lane violation abnormal state, the method also includes: acquiring a second image corresponding to the target vehicle; identifying the second image to obtain the target license plate information; generating prompt information based on the target license plate information and the lane violation abnormal state, and sending the prompt information to the user so that the user can handle the target vehicle according to the prompt information.

[0015] By adopting the above technical solution, the license plate information corresponding to the target vehicle is extracted from the second image. When the target vehicle is in an abnormal lane violation state, a prompt message including the license plate information and the violation status can be instantly generated and sent to the user, which helps the user to quickly understand the violation situation and take corresponding measures in time.

[0016] Optionally, after determining whether the target vehicle type exists in the preset first vehicle type, the method also includes: when the target vehicle type exists in the preset first vehicle type, confirming that the target vehicle is in a normal driving state; obtaining a first position corresponding to the target vehicle at a preset time interval, the first position being the position between a first lane line and a second lane line, the first lane line and the second lane line being lane lines corresponding to a current lane of the target vehicle; determining whether the first position is consistent with the second position, the second position being the position corresponding to the first lane of the target vehicle; when the first position is inconsistent with the second position, confirming that the target vehicle is in a lane changing state.

[0017] By adopting the above technical solution, when the target vehicle type is in the preset first vehicle type, it is confirmed that the target vehicle is in a normal driving state, the position information of the target vehicle is obtained at preset intervals, the driving trajectory of the target vehicle is monitored in real time, and the position information of the target vehicle at different time points is compared. It is possible to accurately determine whether it is in a lane changing state. When the first position is inconsistent with the second position, it is confirmed that the target vehicle is in a lane changing state, which helps to improve the efficiency of the overall traffic operation.

[0018] Optionally, when the first position is inconsistent with the second position, after confirming that the target vehicle is in a lane-changing state, the method also includes: determining the second lane based on the first position, and obtaining a preset second vehicle type corresponding to the second lane; determining whether the preset second vehicle type exists with the target vehicle type; when the preset second vehicle type does not exist with the target vehicle type, confirming that the target vehicle is in an abnormal lane violation state.

[0019] By adopting the above technical solution, the lane where the target vehicle is located is determined according to the lane line, and the preset second vehicle types corresponding to these lanes are obtained. The target vehicle type is compared with the preset second vehicle type, and the violation can be quickly identified. When the target vehicle type does not match the vehicle type of the current lane, it is immediately confirmed that the target vehicle is in an abnormal lane violation state, reducing the need for manual intervention, sending and processing illegal vehicles in a timely manner, and reducing the risk of traffic accidents.

[0020] In a second aspect of the present application, a device for determining a violation of a vehicle lane is provided. The device is a server, and the server includes a receiving unit, a processing unit, and a sending unit; the receiving unit receives a monitoring request sent by a user, and the monitoring request is used to request violation monitoring of a vehicle traveling on a first lane; receives a second laser signal fed back by a laser radar device, and the second laser signal is a signal reflected by the target vehicle based on the first laser signal; the processing unit sends a work instruction to the laser radar device according to the monitoring request, so that the laser radar device sends the first laser signal to the target vehicle; determines the appearance information of the target vehicle according to the second laser signal; determines the type of the target vehicle based on the appearance information of the target vehicle, and the target vehicle types include bus types, truck types, and passenger car types; determines a preset first vehicle type according to the laser radar device, and determines whether the target vehicle type exists in the preset first vehicle type; the sending unit confirms that the target vehicle is in a lane violation abnormal state when the target vehicle type does not exist in the preset first vehicle type, and sends the lane violation abnormal state to the user so that the user can handle the target vehicle.

[0021] Optionally, the receiving unit is used to obtain a first image corresponding to the first lane; the processing unit is used to process the first image to obtain an image to be detected; perform vehicle detection on the image to be detected to obtain vehicle information; and determine that the target vehicle is traveling on the first vehicle based on the vehicle information.

[0022] Optionally, the processing unit is used to scan the target vehicle according to the second laser signal to obtain three-dimensional point cloud data; process the three-dimensional point cloud data to obtain processed three-dimensional point cloud data; extract the processed three-dimensional point cloud data to obtain target shape features, the target shape features include length features, height features, width features and window area features, and output the target shape features as target vehicle shape information.

[0023] Optionally, the processing unit is used to determine target height data based on the target vehicle's appearance information, the target height data being the height data corresponding to the target vehicle; judging whether the target height data is less than or equal to a preset height threshold, the preset height threshold being the passable height data corresponding to the first lane; the sending unit is used to confirm that the target vehicle is in an abnormal state of super-height violation when the target height data is greater than the preset height threshold, and send the abnormal state of super-height violation to the user.

[0024] Optionally, the receiving unit is used to obtain a second image corresponding to the target vehicle; the processing unit is used to identify the second image to obtain the target license plate information; the sending unit is used to generate prompt information based on the target license plate information and the abnormal lane violation status, and send the prompt information to the user so that the user can process the target vehicle according to the prompt information.

[0025] Optionally, the processing unit is used to confirm that the target vehicle is in a normal driving state when the target vehicle type exists in the preset first vehicle type; the receiving unit is used to obtain a first position corresponding to the target vehicle at a preset time interval, the first position being the position between the first lane line and the second lane line, the first lane line and the second lane line being the lane lines corresponding to the current lane of the target vehicle; the processing unit is used to determine whether the first position is consistent with the second position, the second position being the position corresponding to the first lane of the target vehicle; when the first position is inconsistent with the second position, it is confirmed that the target vehicle is in a lane changing state.

[0026] Optionally, the receiving unit is used to determine the second lane based on the first position and obtain a preset second vehicle type corresponding to the second lane; the processing unit is used to determine whether there is a target vehicle type in the preset second vehicle type; when the target vehicle type does not exist in the preset second vehicle type, it is confirmed that the target vehicle is in an abnormal lane violation state.

[0027] In a third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory, so that an electronic device executes any one of the methods described above in the present application.

[0028] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, any one of the above methods of the present application is executed.

[0029] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. According to the monitoring request, a laser radar device is used to emit a first laser signal to the target vehicle, and a second laser signal reflected from the target vehicle is received. The shape of the target vehicle is determined based on the flight time and direction of the laser beam, and the shape information of the target vehicle is determined based on the second laser signal. The type of the target vehicle is determined based on the shape information of the target vehicle, and then the type of the target vehicle is compared with the preset first vehicle type. When the target vehicle type does not exist in the preset first vehicle type, it is confirmed that the target vehicle is in an abnormal state of lane violation. The laser radar is not limited by environmental conditions and can accurately determine the vehicle type and the lane it occupies, effectively solving the problem of inaccurate image recognition due to poor image acquisition quality.

[0030] 2. Acquire the first image of the first lane in real time, and process the first image to detect the vehicle. Perform vehicle detection on the image to be detected, accurately extract relevant information of the vehicle, determine the driving condition of the target vehicle in the first lane based on the vehicle information, and detect the vehicle driving in the first lane in time, reducing the need for manual intervention. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a flow chart of a method for determining a traffic violation of a vehicle lane provided in an embodiment of the present application; Figure 2 It is a scene schematic diagram of a method for determining a traffic violation of a vehicle lane provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of a device for determining a traffic violation of a vehicle lane provided in an embodiment of the present application; Figure 4 It is a structural schematic diagram of an electronic device disclosed in an embodiment of the present application.

[0032] Explanation of the reference numerals: 301, receiving unit; 302, processing unit; 303, sending unit; 400, electronic device; 401, processor; 402, communication bus; 403, user interface; 404, network interface; 405, memory. DETAILED DESCRIPTION

[0033] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0034] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0035] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0036] With the continuous evolution of technology and the continuous expansion of its application scope, accurate monitoring of vehicle driving status has become a core element to ensure road traffic safety and operational efficiency. In order to achieve smooth flow of road traffic, the road system is carefully planned into multiple specific lanes to provide optimal driving paths for different types of vehicles. Given that each lane has clear regulations on the type of vehicles passing through, if a vehicle mistakenly enters an unsuitable lane, it will not only seriously disrupt normal traffic flow, but may also directly induce traffic accidents, thereby posing a major risk to public safety.

[0037] Accurately identifying vehicles traveling in lanes is the cornerstone of building a traffic safety defense line. Currently, vehicle identification technology mainly relies on image recognition methods, which capture image information of vehicle types and lanes they occupy, and then use image recognition algorithms to conduct in-depth analysis of the obtained images, and output judgment conclusions based on the analysis results. However, when the image acquisition quality is impaired due to various factors (such as insufficient light, the presence of obstructions, or equipment failure, etc.), resulting in insufficient image clarity, it will affect the accuracy of image recognition technology.

[0038] Therefore, how to solve the problem of inaccurate image recognition due to poor image acquisition quality. The embodiment of the present application provides a method for determining a traffic violation in a vehicle lane, which is applied to a server. The server of the present application is a platform for traffic violation determination for the traffic control department. Figure 1 is a flow chart of a method for determining a traffic violation in a vehicle lane provided in an embodiment of the present application, with reference to Figure 1 The method includes the following steps S101-S107.

[0039] S101: receiving a monitoring request sent by a user, where the monitoring request is used to monitor a vehicle traveling in a first lane for violations.

[0040] In the above S101, when the staff of the traffic management department makes a violation judgment on the vehicles traveling on the road, they need to use relevant equipment to obtain the vehicles traveling on the road, and then make a judgment on the vehicles traveling. The user refers to the staff of the traffic management department. The user can send a monitoring request to the server through the user device or other devices. The monitoring request is used to monitor the vehicles traveling on the first lane for violations. The first lane is any lane on the road. The violation monitoring includes lane monitoring, overheight monitoring, and line pressure monitoring. After receiving the monitoring request sent by the user device, the server parses the monitoring request and determines the lane where the vehicle is judged to be in violation, that is, the first lane.

[0041] In addition, according to the monitoring request, it is determined that the vehicle traveling in the first lane needs to be monitored. When monitoring the first lane, it is necessary to first determine whether there is a vehicle in the first lane. The image of the first lane can be collected, and then the image can be recognized to determine whether there is a vehicle in the first lane. Only when there is a vehicle in the first lane can the laser radar device be triggered to start working. Specifically, it includes: obtaining the first image corresponding to the first lane; processing the first image to obtain the image to be detected; performing vehicle detection on the image to be detected to obtain vehicle information; and determining that the target vehicle is traveling on the first vehicle according to the vehicle information. Specifically, a high-resolution, wide-angle camera can be selected to ensure that the image of the first lane can be clearly captured. Then install the camera in a suitable position, such as a high pole beside the road, a traffic signal pole or a bridge, to avoid obstruction by trees, buildings, etc., and ensure that the shooting angle and range meet the requirements. The camera transmits the captured image data to the server via wired or wireless methods (such as Wi-Fi, 4G / 5G). The received first image is pre-processed such as denoising, smoothing, and enhancement to improve the image quality. Commonly used preprocessing techniques include mean filtering, median filtering, Gaussian filtering, etc., which can remove noise and interference in the image. If the image captured by the camera is distorted or distorted, image correction is required. The image is corrected through image processing algorithms (such as perspective transformation, affine transformation, etc.) to restore it to a real road scene. Then, according to the monitoring requirements, the image is cropped to only retain the image of the first lane area. The cropped image is the image to be detected and is used for subsequent vehicle detection. Then select a suitable vehicle detection algorithm, such as Haar classifier, HOG+SVM algorithm, CNN deep learning algorithm, etc. These algorithms can identify vehicles based on image features and extract information such as the location, size, and shape of the vehicle. When the vehicle information in the first lane is identified, the vehicle traveling in the first lane can be defined as the target vehicle. When it is determined that a vehicle appears in the first lane, the vehicle traveling in the first lane needs to be judged as violating the traffic rules.

[0042] S102: Sending a work instruction to the laser radar device according to the monitoring request, so that the laser radar device sends a first laser signal to the target vehicle.

[0043] In the above S102, it is determined that the target vehicle is traveling on the first lane, and a work instruction can be sent to the laser radar device according to the monitoring request. The laser radar device establishes a communication connection with the server, usually using a wired or wireless method. At this time, the laser radar device is installed on a bracket above the road to scan vehicles traveling on each lane. A work instruction can be sent to the laser radar device through the communication interface, and the work instruction includes the location information and monitoring time of the lane. One lane corresponds to one location information. At this time, there is a vehicle traveling on the first lane, so the first lane needs to be monitored. After receiving the work instruction, the laser radar device starts to send a first laser signal to the target vehicle traveling on the first lane.

[0044] S103: Receive a second laser signal fed back by the laser radar device, where the second laser signal is a signal reflected by the target vehicle based on the first laser signal.

[0045] In the above S103, after the laser radar device sends the first laser signal to the target vehicle, it receives the second laser signal reflected by the target vehicle, performs preprocessing such as filtering and amplification on the second laser signal to improve the signal quality, and transmits the processed second laser signal to the server through the communication interface.

[0046] S104: Determine the target vehicle appearance information according to the second laser signal.

[0047] In the above S104, the target vehicle shape information is determined according to the second laser signal; specifically, the following steps are performed: scanning the target vehicle according to the second laser signal to obtain three-dimensional point cloud data; processing the three-dimensional point cloud data to obtain processed three-dimensional point cloud data; extracting the processed three-dimensional point cloud data to obtain target shape features, the target shape features include length features, height features, width features and window area features, and outputting the target shape features as the target vehicle shape information. Specifically, in order to ensure that the scanning range of the laser radar device can cover the area where the target vehicle is located, a high-precision, high-frequency laser scanner, such as a laser radar (LiDAR), can be selected, which can emit laser beams and receive reflected signals. The laser radar device is installed in a suitable position, such as beside the road or on a traffic monitoring tower. The laser radar device emits laser beams, which are reflected back after hitting the target vehicle. The laser radar device receives the reflected laser signal and records the timestamp, intensity, direction and other information of each signal. The three-dimensional coordinates of each reflection point are calculated based on the time difference between the emission and reception of the laser signal, as well as the position and posture information of the laser radar device. The three-dimensional coordinates of all reflection points are combined to form the three-dimensional point cloud data of the target vehicle. The three-dimensional point cloud data is then processed to remove invalid points, noise points and abnormal points, such as points caused by scanning errors, environmental factors, etc. The point cloud data is filtered, such as bilateral filtering, Gaussian filtering, etc., to reduce noise and non-smoothing phenomena. The processed three-dimensional point cloud data is obtained, the processed three-dimensional point cloud data is extracted, and the feature descriptors such as normal and curvature of the processed three-dimensional point cloud are calculated. These descriptors can reflect the geometric shape and surface characteristics of the point cloud. Appropriate feature extraction algorithms are applied, such as shape descriptor-based methods (such as PFH, FPFH, etc.) or deep learning-based methods to extract target shape features from point cloud data. According to the extracted feature descriptors, the shape features of the target vehicle are identified and quantified, including length features, height features, width features and window area features. It may involve segmentation and clustering of the point cloud data to extract different parts of the vehicle (such as the body, window, etc.) and calculate their geometric dimensions. The extracted target shape features are formatted for subsequent application and analysis. The formatted target vehicle appearance information is output. In order to facilitate the user to intuitively view the corresponding appearance of the target vehicle, the output target vehicle appearance information can also be visualized, such as generating a three-dimensional model, rendering an image, etc. The second laser signal received by the laser radar device is parsed to extract the appearance information of the target vehicle, which includes length information, width information, and height information.

[0048] S105: Determine the target vehicle type based on the target vehicle appearance information, where the target vehicle type includes a bus type, a truck type, and a passenger car type.

[0049] In the above S105, after determining the target vehicle appearance information corresponding to the target vehicle, an appearance feature database can be established first. The appearance feature database is an appearance feature database containing various vehicle types, that is, different vehicles correspond to different appearances. The target vehicle appearance information is input into the appearance feature database for matching to determine the most suitable target vehicle type. This application divides vehicles into three major types. The first type is the bus type, and the bus type includes single-decker buses and double-decker buses. The second type is the truck type. The truck type refers to a large vehicle used to transport goods. The truck type includes light trucks and heavy trucks. The third type is the passenger car type. The passenger car type includes sedans, multi-purpose vehicles, multi-purpose passenger cars and special vehicles. Special vehicles include ambulances, fire trucks, police cars, postal vehicles and sanitation vehicles.

[0050] S106: Determine a preset first vehicle type according to the laser radar device, and judge whether the target vehicle type exists in the preset first vehicle type.

[0051] In the above S106, after determining the target vehicle type corresponding to the target vehicle, since the laser radar device determines the target vehicle on the first lane, the laser radar device determines the vehicle type allowed to travel on the first lane, that is, the preset first vehicle type. The preset first vehicle type is the vehicle type allowed to travel on the first lane based on traffic rules. Since the target vehicle is traveling on the first lane, it is determined whether the target vehicle type exists in the preset first vehicle type.

[0052] S107: When the target vehicle type does not exist in the preset first vehicle type, it is confirmed that the target vehicle is in a lane violation abnormal state, and the lane violation abnormal state is sent to the user so that the user can handle the target vehicle.

[0053] In the above S107, if the target vehicle type does not exist in the preset first vehicle type, it is confirmed that the target vehicle is in a lane violation abnormal state, the violation information, time and location are recorded, and the lane violation abnormal state is sent to the traffic control department so that the traffic control department can handle the violation.

[0054] In addition, after determining that the target vehicle is in an abnormal lane violation state, the target vehicle needs to be marked so that the target vehicle can be found according to the mark later, and the violation of the target vehicle can be processed, which specifically includes: obtaining a second image corresponding to the target vehicle; identifying the second image to obtain the target license plate information; generating prompt information according to the target license plate information and the abnormal lane violation state, and sending the prompt information to the user so that the user can process the target vehicle according to the prompt information. Specifically, when the laser radar device is used to scan the target vehicle, the target vehicle is imaged by a camera to ensure that the image acquisition device has sufficient resolution and clarity so that the detailed information of the target vehicle can be captured. The image information of the target area is obtained in real time by the image acquisition device. When the target vehicle enters the monitoring area, its image is automatically captured as the second image. Ensure that the second image contains the complete license plate information of the target vehicle and sufficient background information for subsequent identification and processing. The second image is preprocessed, including grayscale, binarization, noise removal and other operations to improve the accuracy of license plate recognition. Use license plate location algorithms (such as methods based on color, texture, edge and other features) to accurately find the location of the license plate in the preprocessed image. Split the located license plate to separate each individual character. Use character segmentation algorithms (such as projection-based, connected domain-based, etc.) to ensure the integrity of each character. Feature extraction and classification of the segmented characters. Use character recognition algorithms (such as template matching, neural network, support vector machine, etc.) to recognize the text information on the license plate. Verify the recognized license plate information to ensure its accuracy and completeness. Output the recognized license plate information as the target license plate information. Since it has been confirmed that the target vehicle is currently in a lane violation abnormal state, generate prompt information containing detailed content such as vehicle information, violation time, violation location, violation type, etc. according to the target license plate information and lane violation abnormal state. Ensure that the prompt information is clear, accurate and easy to understand. Send the prompt information to the traffic management department, and select the appropriate communication method to send it based on the actual situation to ensure that the prompt information can be conveyed to the user in a timely and accurate manner so that the user can handle the target vehicle according to the prompt information. It can realize real-time monitoring and prompting of lane violations of target vehicles, provide strong support for traffic management, and also help the traffic department to send violation prompt information to the corresponding drivers according to the prompt information, so as to improve users' awareness of traffic safety and compliance with traffic rules.

[0055] Further, when the target vehicle type exists in the preset first vehicle type, it is confirmed that the target vehicle is in a normal driving state; at a preset time interval, the first position corresponding to the target vehicle is obtained, the first position is the position between the first lane line and the second lane line, and the first lane line and the second lane line are the lane lines corresponding to the current driving lane of the target vehicle; it is determined whether the first position is consistent with the second position, and the second position is the position corresponding to the first lane of the target vehicle; when the first position is inconsistent with the second position, it is confirmed that the target vehicle is in a lane change state. Specifically, since the first lane allows vehicles of the preset first vehicle type to pass, the target vehicle type corresponding to the target vehicle is matched with the preset first vehicle type. If the target vehicle type corresponding to the target vehicle exists in the preset first vehicle type list, it is confirmed that the target vehicle is in a normal driving state. A preset time interval can be set for periodically obtaining the position information of the target vehicle. This time interval can be adjusted according to actual conditions to ensure that the vehicle position information can be obtained in a timely manner without occupying system resources too frequently. After the preset time interval arrives, the first position information of the target vehicle at the current moment is obtained through image recognition, radar detection or other technical means. At this time, the first position refers to the lane position of the target vehicle at the current moment, that is, the position between the first lane line and the second lane line. These two lane lines represent the boundary of the target vehicle's current driving lane. Then compare the first position with the second position. At this time, the second position refers to the lane position of the target vehicle before the preset time interval, that is, the corresponding position when the target vehicle was driving in the first lane. This position was obtained at the previous time point. Compare the first position of the target vehicle with the second position, and the content of the comparison is the lane number, the position of the lane boundary line, etc. If the first position is consistent with the second position, it means that the target vehicle has not changed lanes within the current time interval and is still driving in the original lane. If the first position is inconsistent with the second position, it means that the target vehicle has crossed the lane line within the current time interval and changed lanes from the original lane to another lane. At this time, it can be confirmed that the target vehicle is in a lane change state. Real-time monitoring and judgment of the driving status of the target vehicle can be achieved, and the lane change behavior of the vehicle can be discovered and handled in time, providing strong protection for traffic safety. Figure 2 As shown, the road on which the current target vehicle A is traveling is divided into three lanes, namely lane a, lane b and lane c. The current first position of the target vehicle A is obtained. If the first position is the position corresponding to lane b, the second position corresponding to the target vehicle A before the preset time interval is obtained. If the second position is the position corresponding to lane a, the first position and the second position are inconsistent at this time, so it is indicated that the target vehicle has changed lanes.

[0056] Furthermore, after confirming that the target vehicle has changed lanes, it is necessary to determine the lane in which the target vehicle is currently traveling again to determine whether the target vehicle meets the driving requirements of the current lane, which specifically includes: determining the second lane according to the first position, obtaining the preset second vehicle type corresponding to the second lane; determining whether the preset second vehicle type has the target vehicle type; when the preset second vehicle type does not have the target vehicle type, it is confirmed that the target vehicle is in an abnormal state of lane violation. Specifically, the first position information of the target vehicle can be obtained in real time according to equipment such as a vehicle tracking system, a traffic monitoring system or an on-board sensor. The lane in which the target vehicle is currently located can be determined according to the first position. The lane number or position information can be mapped to a specific lane according to the road design and traffic rules. The second lane corresponding to the first position information can also be found by consulting a road map, a lane layout diagram or a database of a traffic monitoring system. According to the position corresponding to the second lane, the vehicle type restriction information corresponding to the second lane is obtained by accessing the database of the traffic management department or querying traffic regulations. These restriction information usually stipulate which types of vehicles can travel on the lane and which types of vehicles are prohibited or restricted from traveling. According to the lane restriction information, the preset second vehicle type corresponding to the second lane is determined. The preset second vehicle type may include a small car, a large car, a truck, a passenger car, a motorcycle, etc., depending on the design and function of the lane. After determining the target vehicle type based on the target vehicle appearance information, the target vehicle type is matched with the preset second vehicle type, and it is checked whether the target vehicle type is included in the preset second vehicle type list to determine whether the target vehicle meets the driving requirements of the second lane. If the target vehicle type does not exist in the preset second vehicle type, it means that the target vehicle has violated the driving restrictions of the second lane. At this time, it can be confirmed that the target vehicle is in an abnormal state of lane violation. The violation time, location, vehicle type and license plate information are combined, and the combined information is sent to the traffic management department so that the traffic management department can handle it accordingly according to the violation. The processing includes sending a violation notice to the owner or driver of the target vehicle to inform him of the violation and the corresponding penalty measures.

[0057] In a possible implementation, in addition to determining the lane occupied by the target vehicle, the height of the target vehicle can also be monitored and determined in real time, and super-high violations can be discovered and handled in time to provide strong protection for traffic safety, specifically including: determining the target height data according to the target vehicle appearance information, the target height data is the height data corresponding to the target vehicle; judging whether the target height data is less than or equal to the preset height threshold, the preset height threshold is the passable height data corresponding to the first lane; when the target height data is greater than the preset height threshold, it is confirmed that the target vehicle is in an abnormal state of super-high violation, and the super-high violation abnormal state is sent to the user. Specifically, according to the target vehicle appearance information of the target vehicle, data related to the height of the target vehicle is extracted. This is usually obtained through three-dimensional point cloud data or image processing technology, which contains the precise height information of the vehicle. The extracted height features are calculated to obtain the specific height data of the target vehicle. This may require considering factors such as the shape, posture and ground height of the vehicle to ensure the accuracy of the calculation results. It is determined that the target vehicle is traveling in the first lane, and a preset height threshold is set according to the traffic regulations and design standards of the first lane. This threshold represents the maximum vehicle height that can pass through the lane. The calculated target height data is compared with the preset height threshold. It is used to determine whether the height of the target vehicle exceeds the lane's traffic limit. If the target height data is greater than the preset height threshold, the target vehicle is confirmed to be in an abnormal state of super-high violation according to traffic rules. This means that the height of the vehicle exceeds the lane's traffic limit and may pose a threat to traffic safety. The super-high violation abnormal state of the target vehicle is recorded, including the time, location, and vehicle information of the violation, for subsequent query and processing. The license plate information of the target vehicle and the super-high violation abnormal state are then sent to the traffic management department so that the traffic management department can take measures against the target vehicle according to the violation. For example, if the height data corresponding to the target vehicle is 6m, the highest passable height corresponding to the first lane is obtained, the preset height threshold is set to 5m, and the target height data is greater than the preset height threshold, then the target vehicle is confirmed to be in an abnormal state of super-high violation. In addition, when the target height data is less than or equal to the preset height threshold, it is confirmed that the target vehicle is in a normal driving state and the target vehicle continues to be monitored.

[0058] The embodiment of the present application also provides a device for determining a traffic violation of a vehicle lane. Figure 3 is a schematic diagram of a vehicle lane violation determination device provided in an embodiment of the present application, with reference to Figure 3 The device is a server, and the server includes a receiving unit 301, a processing unit 302 and a sending unit 303.

[0059] The receiving unit 301 receives a monitoring request sent by a user, where the monitoring request is used to request violation monitoring of vehicles traveling in the first lane; and receives a second laser signal fed back by a laser radar device, where the second laser signal is a signal reflected by the target vehicle based on the first laser signal.

[0060] The processing unit 302 sends a work instruction to the laser radar device according to the monitoring request, so that the laser radar device sends a first laser signal to the target vehicle; determines the shape information of the target vehicle according to the second laser signal; determines the type of the target vehicle based on the shape information of the target vehicle, and the target vehicle types include bus types, truck types and passenger car types; determines a preset first vehicle type according to the laser radar device, and determines whether the target vehicle type exists in the preset first vehicle type.

[0061] The sending unit 303, when the target vehicle type does not exist in the preset first vehicle type, confirms that the target vehicle is in a lane violation abnormal state, and sends the lane violation abnormal state to the user so that the user can handle the target vehicle.

[0062] In a possible implementation, the receiving unit 301 is used to obtain a first image corresponding to a first lane; the processing unit 302 is used to process the first image to obtain an image to be detected; perform vehicle detection on the image to be detected to obtain vehicle information; and determine, based on the vehicle information, that the target vehicle is traveling on the first vehicle.

[0063] In one possible implementation, the processing unit 302 is used to scan the target vehicle according to the second laser signal to obtain three-dimensional point cloud data; process the three-dimensional point cloud data to obtain processed three-dimensional point cloud data; extract the processed three-dimensional point cloud data to obtain target shape features, the target shape features include length features, height features, width features and window area features, and output the target shape features as target vehicle shape information.

[0064] In one possible implementation, the processing unit 302 is used to determine target height data based on the target vehicle's appearance information, where the target height data is the height data corresponding to the target vehicle; to determine whether the target height data is less than or equal to a preset height threshold, where the preset height threshold is the passable height data corresponding to the first lane; the sending unit 303 is used to confirm that the target vehicle is in an abnormal state of overheight violation when the target height data is greater than the preset height threshold, and to send the abnormal state of overheight violation to the user.

[0065] In one possible implementation, the receiving unit 301 is used to obtain a second image corresponding to the target vehicle; the processing unit is used to identify the second image to obtain the target license plate information; the sending unit 302 is used to generate prompt information based on the target license plate information and the lane violation abnormality status, and send the prompt information to the user so that the user can process the target vehicle according to the prompt information.

[0066] In a possible implementation, the processing unit 302 is used to confirm that the target vehicle is in a normal driving state when the target vehicle type exists in the preset first vehicle type; the receiving unit 301 is used to obtain a first position corresponding to the target vehicle at a preset time interval, the first position being the position between the first lane line and the second lane line, the first lane line and the second lane line being the lane lines corresponding to the target vehicle's current driving lane; the processing unit 302 is used to determine whether the first position is consistent with the second position, the second position being the position corresponding to the first lane of the target vehicle; when the first position is inconsistent with the second position, it is confirmed that the target vehicle is in a lane changing state.

[0067] In a possible implementation, the receiving unit 301 is used to determine the second lane based on the first position and obtain a preset second vehicle type corresponding to the second lane; the processing unit 302 is used to determine whether there is a target vehicle type in the preset second vehicle type; when the target vehicle type does not exist in the preset second vehicle type, it is confirmed that the target vehicle is in an abnormal lane violation state.

[0068] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0069] The present application also discloses an electronic device. Figure 4 , Figure 4 The electronic device 400 may include: at least one processor 401 , at least one network interface 404 , a user interface 403 , a memory 405 , and at least one communication bus 402 .

[0070] The communication bus 402 is used to realize the connection and communication between these components.

[0071] The user interface 403 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 403 may also include a standard wired interface and a wireless interface.

[0072] The network interface 404 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0073] Among them, the processor 401 may include one or more processing cores. The processor 401 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 405, and calling data stored in the memory 405. Optionally, the processor 401 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 401 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application requests; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 401, and it can be implemented separately through a chip.

[0074] Among them, the memory 405 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 405 includes a non-transitory computer-readable storage medium. The memory 405 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 405 may include a program storage area and a data storage area, wherein the program storage area. Instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc. can be stored; the data storage area can store data involved in the above-mentioned various method embodiments, etc. The memory 405 can also be optionally at least one storage device located away from the aforementioned processor 401.

[0075] like Figure 4As shown, the memory 405 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for determining traffic violations on vehicle lanes.

[0076] exist Figure 4 In the electronic device 400 shown, the user interface 403 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 401 can be used to call the application program for determining the violation of the vehicle lane stored in the memory 405. When executed by one or more processors, the electronic device executes one or more of the methods described in the above embodiments.

[0077] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0078] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0079] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0080] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0081] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0082] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0083] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, it will be easy for those skilled in the art to think of other embodiments of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure.

Claims

1. A method for determining a traffic violation in a vehicle lane, characterized in that: Applied in a server, the method comprises: receiving a monitoring request sent by a user, wherein the monitoring request is a request for monitoring a vehicle traveling on a first lane for violations; Sending a work instruction to the laser radar device according to the monitoring request, so that the laser radar device sends a first laser signal to the target vehicle; receiving a second laser signal fed back by the laser radar device, where the second laser signal is a signal reflected by the target vehicle according to the first laser signal; Determining target vehicle appearance information according to the second laser signal; Determine the type of the target vehicle based on the target vehicle appearance information, the target vehicle type including bus type, truck type and passenger car type; Determine a preset first vehicle type according to the laser radar device, and judge whether the target vehicle type exists in the preset first vehicle type; When the target vehicle type does not exist in the preset first vehicle type, it is confirmed that the target vehicle is in a lane violation abnormal state, and the lane violation abnormal state is sent to the user so that the user can process the target vehicle.

2. The method according to claim 1, characterized in that Before sending a work instruction to the laser radar device according to the monitoring request so that the laser radar device sends a first laser signal to the target vehicle, the method further includes: Acquire a first image corresponding to the first lane; Processing the first image to obtain an image to be detected; Performing vehicle detection on the image to be detected to obtain vehicle information; It is determined based on the vehicle information that the target vehicle is traveling on the first vehicle.

3. The method according to claim 1, characterized in that The step of determining the target vehicle appearance information according to the second laser signal specifically includes: Scanning the target vehicle according to the second laser signal to obtain three-dimensional point cloud data; Processing the three-dimensional point cloud data to obtain processed three-dimensional point cloud data; The processed three-dimensional point cloud data is extracted to obtain target shape features, which include length features, height features, width features and window area features, and the target shape features are output as the target vehicle shape information.

4. The method according to claim 3, characterized in that After determining the target vehicle appearance information according to the second laser signal, the method further includes: Determine target height data according to the target vehicle appearance information, wherein the target height data is height data corresponding to the target vehicle; Determine whether the target height data is less than or equal to a preset height threshold, where the preset height threshold is the passable height data corresponding to the first lane; When the target height data is greater than the preset height threshold, it is confirmed that the target vehicle is in an abnormal state of overheight violation, and the abnormal state of overheight violation is sent to the user.

5. The method according to claim 1, characterized in that When the target vehicle type does not exist in the preset first vehicle type, after confirming that the target vehicle is in a lane violation abnormal state, the method further includes: Acquire a second image corresponding to the target vehicle; The second image is recognized to obtain target license plate information; Prompt information is generated according to the target license plate information and the lane violation abnormal state, and the prompt information is sent to the user so that the user can process the target vehicle according to the prompt information.

6. The method according to claim 1, characterized in that After determining whether the target vehicle type exists in the preset first vehicle type, the method further includes: When the target vehicle type exists in the preset first vehicle type, confirming that the target vehicle is in a normal driving state; At a preset time interval, a first position corresponding to the target vehicle is obtained, where the first position is a position between a first lane line and a second lane line, where the first lane line and the second lane line are lane lines corresponding to a lane in which the target vehicle is currently traveling; Determining whether the first position is consistent with a second position, the second position being a position corresponding to the target vehicle traveling in the first lane; When the first position is inconsistent with the second position, it is confirmed that the target vehicle is in a lane changing state.

7. The method according to claim 6, characterized in that After confirming that the target vehicle is in a lane-changing state when the first position is inconsistent with the second position, the method further includes: Determine a second lane according to the first position, and obtain a preset second vehicle type corresponding to the second lane; Determining whether the preset second vehicle type is the target vehicle type; When the preset second vehicle type does not include the target vehicle type, it is confirmed that the target vehicle is in the lane violation abnormal state.

8. A device for determining a traffic violation in a vehicle lane, characterized in that: The device is a server, and the server comprises a receiving unit (301), a processing unit (302) and a sending unit (303); The receiving unit (301) receives a monitoring request sent by a user, the monitoring request being a request for monitoring a vehicle traveling on a first lane for violation of traffic rules; receives a second laser signal fed back by the laser radar device, the second laser signal being a signal reflected by the target vehicle based on the first laser signal; The processing unit (302) sends a working instruction to the laser radar device according to the monitoring request, so that the laser radar device sends a first laser signal to the target vehicle; determines the appearance information of the target vehicle according to the second laser signal; determines the type of the target vehicle based on the appearance information of the target vehicle, and the target vehicle type includes a bus type, a truck type and a passenger car type; determines a preset first vehicle type according to the laser radar device, and determines whether the target vehicle type exists in the preset first vehicle type; The sending unit (303) confirms that the target vehicle is in a lane violation abnormality state when the target vehicle type does not exist in the preset first vehicle type, and sends the lane violation abnormality state to the user so that the user can handle the target vehicle.

9. An electronic device, characterized in that: The electronic device (400) comprises a processor (401), a memory (405), a user interface (403) and a network interface (404), wherein the memory (405) is used to store instructions, the user interface (403) and the network interface (404) are used to communicate with other devices, and the processor (401) is used to execute the instructions stored in the memory (405) so that the electronic device (400) executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is performed.

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