Road traffic converse driving intelligent early warning method, system and equipment
By installing intelligent capture equipment on mobile vehicles, real-time collection and analysis of the front images of the vehicle, and identifying and capturing retrograde vehicles, the monitoring scope and law enforcement efficiency of road traffic counter-traffic supervision is solved, and dynamic supervision and accurate warning of all road sections are achieved throughout the whole period.
Patent Information
- Application Number
- CN202510606629.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-12
- Publication Date
- 2025-07-11
AI Technical Summary
In the prior art, road traffic retrograde supervision has problems such as limited monitoring scope, insufficient law enforcement manpower, inability to supervise all sections of roads throughout the entire period, and difficulty in time to detect and investigate and deal with complex road conditions and remote sections of roads in a timely manner.
Install intelligent capture equipment on mobile vehicles, collect the front images of the vehicle in real time, conduct target detection and license plate recognition in the same lane, judge the conditions for counter-traffic judgment, conduct continuous capture when the conditions are met, and report the capture collection to the traffic management platform.
It has achieved dynamic supervision of all roads in all periods, improved law enforcement efficiency, and improved the accuracy of identification of retrograde behaviors and timely warning.
Smart Images
Figure CN120299263A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of traffic warning, and in particular to an intelligent warning method, system and device for road traffic reverse driving. Background Art
[0002] As a serious traffic violation, vehicle reverse driving not only seriously disrupts the road traffic order, but also greatly increases the risk of traffic accidents. Traditional road traffic reverse driving supervision mainly relies on fixed surveillance cameras and on-site law enforcement by traffic police. Although fixed surveillance cameras can achieve real-time monitoring in specific sections, there are problems such as limited monitoring range, difficulty in covering complex road conditions and remote sections. Especially in some urban-rural junctions and back streets and alleys without surveillance equipment, reverse driving behaviors are difficult to be discovered and investigated in a timely manner; while on-site law enforcement by traffic police can effectively stop and punish reverse driving behaviors, but due to the limitations of manpower, time and space, it is impossible to achieve full-time and full-section supervision, the law enforcement efficiency is low, and there are certain law enforcement blind spots; in addition, some drivers have a fluke mentality and use surveillance blind spots or the gaps in traffic police law enforcement to carry out reverse driving behaviors, further increasing the difficulty of road traffic management and affecting the supervision efficiency and accuracy of road traffic reverse driving behaviors.
[0003] Therefore, in the current related technologies, there are technical problems such as limited monitoring range, insufficient law enforcement manpower, inability to conduct full-time and full-section supervision, and difficulty in timely discovering and investigating reverse driving behaviors in complex road conditions and remote sections. Summary of the Invention
[0004] This application provides an intelligent warning method, system and device for road traffic reverse driving, which solves the technical problems in the prior art of limited monitoring range, insufficient law enforcement manpower, inability to conduct full-time and full-section supervision, and difficulty in timely discovering and investigating reverse driving behaviors in complex road conditions and remote sections, and achieves the technical effects of improving law enforcement efficiency, realizing full-time and full-section dynamic supervision, and improving the accuracy of reverse driving behavior recognition and the timeliness of warning.
[0005] This application provides an intelligent warning method for road traffic reverse driving. The method includes: installing an intelligent capture device on a mobile vehicle; during the driving process of the mobile vehicle, collecting the front view of the vehicle in real time through the intelligent capture device; performing same-lane target detection according to the front view of the vehicle to determine the target vehicle and the target license plate; judging whether the target vehicle meets the reverse driving determination condition; if the target vehicle meets the reverse driving determination condition, continuously capturing based on the target license plate to obtain a vehicle reverse driving capture set; and reporting the vehicle reverse driving capture set to the traffic management platform.
[0006] In a possible implementation, the intelligent early warning method for road traffic reverse driving further performs the following processing: vehicle recognition is performed based on the image in front of the vehicle to obtain multiple recognized vehicles; the current driving lane information of the mobile vehicle is obtained; the multiple recognized vehicles are detected for being in the same lane according to the current driving lane information to obtain the target vehicle; license plate feature recognition is performed on the target vehicle to obtain the target license plate.
[0007] In a possible implementation, the intelligent early warning method for road traffic reverse driving further performs the following processing: lane detection is performed on the multiple recognized vehicles to obtain multiple vehicle lane information; same-lane judgment is performed on the multiple vehicle lane information according to the current driving lane information to obtain multiple same-lane judgment results; the multiple recognized vehicles are matched according to the multiple same-lane judgment results to generate the target vehicle.
[0008] In a possible implementation, the intelligent early warning method for road traffic reverse driving further performs the following processing: taking the mobile vehicle as a reference, orientation detection is performed on the target vehicle to obtain a vehicle orientation detection result; it is determined whether the vehicle orientation detection result meets the reverse driving determination condition.
[0009] In a possible implementation, the intelligent early warning method for road traffic reverse driving further performs the following processing: the reverse driving determination condition is that the front of the target vehicle is directly facing the mobile vehicle.
[0010] In a possible implementation, the intelligent early warning method for road traffic reverse driving further performs the following processing: if the target vehicle meets the reverse driving determination condition, a first reverse driving capture photo is obtained based on the target license plate; based on the target license plate, a second reverse driving capture photo and a third reverse driving capture photo are obtained according to the continuous capture constraint condition; a vehicle reverse driving capture set is generated according to the first reverse driving capture photo, the second reverse driving capture photo, and the third reverse driving capture photo.
[0011] In a possible implementation, the intelligent early warning method for road traffic reverse driving further performs the following processing: the continuous capture constraint condition is that the front of the target vehicle is directly facing the mobile vehicle and the coordinates of the target vehicle are offset.
[0012] The present application also provides a road traffic reverse driving intelligent warning system, which includes: a capture device installation module for installing an intelligent capture device on a mobile vehicle; a picture acquisition module for, during the driving process of the mobile vehicle, collecting the picture in front of the vehicle in real time through the intelligent capture device; a target detection module for performing target detection of the same lane according to the picture in front of the vehicle to determine the target vehicle and the target license plate; a reverse driving judgment module for judging whether the target vehicle meets the reverse driving determination condition; a reverse driving capture module for, if the target vehicle meets the reverse driving determination condition, performing continuous capture based on the target license plate to obtain a vehicle reverse driving capture set; and a capture set reporting module for reporting the vehicle reverse driving capture set to a traffic management platform.
[0013] The present application also provides an electronic device, including: a memory for storing executable instructions; and a processor for implementing a road traffic reverse driving intelligent warning method when executing the executable instructions stored in the memory.
[0014] It is intended to install an intelligent capture device on a mobile vehicle through a road traffic reverse driving intelligent warning method, system and device provided by the present application; during the driving process of the mobile vehicle, collect the picture in front of the vehicle in real time; perform target detection of the same lane to determine the target vehicle and the target license plate; judge whether the target vehicle meets the reverse driving determination condition; if the target vehicle meets the reverse driving determination condition, perform continuous capture to obtain a vehicle reverse driving capture set; and report the vehicle reverse driving capture set to a traffic management platform. This solves the technical problems existing in the prior art, such as limited monitoring range, insufficient law enforcement manpower, inability to conduct full-time and full-section supervision, and difficulty in timely detecting and investigating reverse driving behaviors in complex road conditions and remote sections, achieving the technical effects of improving law enforcement efficiency, realizing full-time and full-section dynamic supervision, and improving the recognition accuracy and warning timeliness of reverse driving behaviors. BRIEF DESCRIPTION OF THE DRAWINGS
[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings of the embodiments of the present disclosure will be briefly introduced below. Flowcharts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the operations in the front or below do not necessarily need to be executed precisely in sequence. On the contrary, according to the need, various steps can be executed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or several operations can be removed from these processes.
[0016] Figure 1 It is a schematic flowchart of a road traffic reverse driving intelligent warning method provided by an embodiment of the present application.
[0017] Figure 2 It is a schematic structural diagram of a road traffic reverse driving intelligent warning system provided by an embodiment of the present application.
[0018] Figure 3 A structural schematic diagram of an electronic device provided by an embodiment of the present application.
[0019] Explanation of reference numerals in the drawings: The intelligent capture device installation module 10, the picture acquisition module 20, the target detection module 30, the oncoming traffic judgment module 40, the oncoming traffic capture module 50, the capture set reporting module 60, the input device 401, the processor 402, the memory 403, the output device 404. Detailed implementation manners
[0020] The above description is only an overview of the technical solution of the present application. In order to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the following specifically gives the detailed implementation manners of the present application.
[0021] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings. The described embodiments should not be regarded as limitations of the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present application.
[0022] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict. The terms "first / second" involved are only used to distinguish similar objects and do not represent a specific order for the objects. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules not clearly listed or inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application.
[0023] An embodiment of the present application provides a method for intelligent early warning of oncoming traffic on roads, as Figure 1 shown. The method includes: Step S100, install an intelligent capture device on a mobile vehicle.
[0024] Preferably, an intelligent device is installed above the inner side of the front windshield of the mobile vehicle, which can not only obtain a good shooting angle, but also avoid the interference and damage of the device by the external environment, or it is installed on the vehicle roof and has rotation and zoom functions. The device for real-time collecting and processing the road information in front of the vehicle specifically includes an image acquisition unit, an image processing unit, a license plate recognition unit, a data transmission unit and a positioning unit. Among them, the image acquisition unit consists of a high-resolution camera, which can, during the driving of the vehicle, capture the images in front of the vehicle in real time at a certain frame rate (such as 25 frames per second or higher), covering a certain viewing angle range (such as a wide angle of 120° or even wider), ensuring that the vehicle conditions in the same lane and surrounding lanes can be captured.
[0025] Preferably, the image processing unit is the core part of the intelligent capture device. By using deep learning and image recognition, it can quickly process and analyze the collected images, and can identify various objects in the pictures, such as vehicles, license plates, traffic signs and markings, etc. By analyzing the characteristics of the vehicle's shape, color, driving trajectory, etc., it can initially judge whether there are abnormal driving behaviors; the license plate recognition unit uses optical character recognition (OCR) to accurately recognize the license plate in the image, and can quickly and accurately extract information such as the license plate number and color. Even in the case of low light, dirty license plates or partial occlusion, it can ensure a high recognition accuracy; the data transmission unit is responsible for transmitting the captured images, the recognized license plate information and related analysis results and other data to the traffic management platform in real time through a wireless communication network (such as 4G, 5G network); the positioning unit uses the Global Positioning System (GPS) or the Beidou satellite positioning system to accurately obtain the position information of the mobile vehicle. Combining with map data, it can determine the specific location where the reverse driving behavior occurs.
[0026] Step S200, during the driving of the mobile vehicle, the intelligent capture device is used to collect the images in front of the vehicle in real time.
[0027] Preferably, during the driving of the vehicle, the intelligent capture device works continuously. The image acquisition unit in the device (such as a high-resolution camera) continuously captures images at a set frame rate (such as 25 frames per second, 30 frames per second or even higher). In each second of the vehicle's driving, multiple consecutive images can be generated to ensure that any situation occurring on the road ahead of the vehicle can be recorded in time; the camera of the intelligent capture device has a certain viewing angle range, usually a wide-angle lens, and the viewing angle can reach 120° or even wider, enabling the device to cover a relatively wide area in front of the vehicle. It can not only capture the vehicles in the same lane but also take into account some situations in the adjacent lanes; the intelligent capture device has good environmental adaptability to cope with various complex environmental conditions. Under different lighting conditions (such as strong light during the day, weak light at night, cloudy days, rainy days, snowy days, etc.), the device can automatically adjust parameters (such as exposure time, gain, etc.) to ensure clear images are captured; the real-time captured images will be quickly transmitted to the image processing unit of the intelligent capture device for preliminary preprocessing (such as image enhancement, denoising, etc.) to improve the image quality and obtain the real-time image of the road ahead of the vehicle.
[0028] Step S300, perform target detection in the same lane based on the image of the road ahead of the vehicle to determine the target vehicle and the target license plate.
[0029] Step S300 further includes step S310, perform vehicle recognition based on the image of the road ahead of the vehicle to obtain multiple recognized vehicles; step S320, obtain the current driving lane information of the mobile vehicle; step S330, perform same-lane detection on the multiple recognized vehicles according to the current driving lane information to obtain the target vehicle; step S340, perform license plate feature recognition on the target vehicle to obtain the target license plate.
[0030] Preferably, after the intelligent capture device collects the front view of the vehicle, it first performs preprocessing operations on the image, including removing the noise in the image (such as interference points caused by factors such as light and sensors), enhancing the contrast of the image to improve the clarity and quality of the image, and then uses advanced deep learning algorithms, such as object detection algorithms based on convolutional neural networks (CNNs) (such as YOLO, Faster R-CNN, etc.), to analyze the preprocessed image, which can accurately identify the vehicle targets in the picture and mark the positions and bounding boxes of the vehicles in the image; furthermore, it records multiple recognized vehicles in the picture; then, using image processing and computer vision, it identifies the lane lines in the front view of the vehicle. By analyzing the characteristics such as the color, texture, and shape of the lane lines in the image, it determines the position and direction of the lane lines. For example, common white or yellow lane lines will have obvious color characteristics in the image, and they can be extracted based on these characteristics. It can also combine the information obtained from other sensors on the vehicle (such as lidar, millimeter-wave radar, etc.) to assist in determining the lane information, and then determine the lane where the mobile vehicle is currently located, such as the leftmost lane, the middle lane, or the rightmost lane.
[0031] Preferably, the position information of the multiple recognized vehicles is matched with the current driving lane information of the mobile vehicle. By comparing the position relationship between the recognized vehicles in the image and the lane lines, it determines which recognized vehicles are in the same lane as the mobile vehicle, and filters out the recognized vehicles in the same lane as the mobile vehicle as the target vehicles; after determining the target vehicles, it further analyzes the image area of the target vehicles to locate the position of the license plate. For example, using the characteristics such as the color, shape, and texture of the license plate, combined with machine learning, it accurately finds the specific position of the license plate in the vehicle image; it performs character segmentation on the located license plate image, separates each character on the license plate, and identifies the segmented characters. Using optical character recognition (OCR) technology, it converts the character image into the corresponding text information; by comparing with the pre-trained character model, it determines the specific content of each character, and finally obtains the license plate number of the target vehicle, that is, obtains the target license plate.
[0032] Further, step S330 further includes step S331, performing lane detection on the multiple recognized vehicles to obtain multiple vehicle lane information; step S332, performing same-lane judgment on the multiple vehicle lane information according to the current driving lane information to obtain multiple same-lane judgment results; step S333, matching the multiple recognized vehicles according to the multiple same-lane judgment results to generate the target vehicles.
[0033] Preferably, lane detection is performed on multiple identified vehicles, including analyzing the area where each identified vehicle is located and its surrounding environment in the picture by using image processing. For example, edge detection algorithms are used to find possible lane line edges, the color of the lane lines (such as common white and yellow) is identified based on color features, and based on the extracted image features, they are matched with a pre-set lane model to determine which lane each identified vehicle is roughly located in, and lane information corresponding to each vehicle is obtained, such as the first lane, the second lane, etc.; then, other sensors on the vehicle, such as lidar and millimeter-wave radar, are combined to assist in judging the relative position relationship between the vehicle and the lane lines, and thus more accurate vehicle lane information is obtained.
[0034] Preferably, the current driving lane information of the mobile vehicle is compared with the lane information of each identified vehicle one by one to determine whether they belong to the same lane. For example, if the lane number of the identified vehicle is the same as that of the mobile vehicle, it is determined to be in the same lane; if not, it is determined to be in different lanes. Finally, a same-lane judgment result is obtained for each identified vehicle, and the result is "yes" or "no"; according to the same-lane judgment result, multiple identified vehicles are screened, that is, the identified vehicles with the same-lane judgment result of "yes" are selected, and these vehicles are used as target vehicles and the operating objects for reverse driving determination.
[0035] Step S400, determining whether the target vehicle meets the reverse driving determination condition.
[0036] Step S400 further includes step S410 of detecting the orientation of the target vehicle with the mobile vehicle as a reference to obtain a vehicle orientation detection result; step S410, determining whether the vehicle orientation detection result meets the reverse driving determination condition.
[0037] Step S410 further includes that the reverse driving determination condition is that the front of the target vehicle is directly facing the mobile vehicle.
[0038] Preferably, the mobile vehicle is set as a reference benchmark, and a reference coordinate system is established in the picture in front of the collected vehicle. For example, the forward direction of the mobile vehicle is taken as the positive direction, and the center of the vehicle is taken as the origin, and then the image of the target vehicle is analyzed to extract features that can reflect the vehicle orientation. For example, the shape of the vehicle's front (usually there are unique structural features such as headlights and air intakes at the front part) and the trend of the contour lines of the vehicle body are used to initially judge the general orientation of the vehicle; then, based on computer vision and image processing, such as the method based on template matching, the image of the target vehicle is matched with pre-prepared vehicle templates with different orientations to determine the orientation angle of the target vehicle relative to the mobile vehicle; then a vehicle orientation detection result is obtained, such as "the front of the vehicle faces the mobile vehicle" or "the front of the vehicle deviates from the mobile vehicle".
[0039] Preferably, compare the obtained vehicle orientation detection result with the set reverse driving determination condition. Herein, the reverse driving determination condition is clearly defined as "the front of the target vehicle is directly facing the mobile vehicle". Based on the comparison result, perform a logical judgment. If the front of the target vehicle is indeed directly facing the mobile vehicle, that is, the reverse driving determination condition is met, then determine that the target vehicle is driving in reverse; if the front of the target vehicle is not directly facing the mobile vehicle, for example, the front is facing away from the mobile vehicle or towards other directions, then determine that the target vehicle does not meet the reverse driving determination condition and there is no reverse driving; thus effectively identifying the vehicle that may have a reverse driving behavior in the same lane.
[0040] Step S500, if the target vehicle meets the reverse driving determination condition, continuously capture based on the target license plate to obtain a vehicle reverse driving capture set.
[0041] Preferably, if the target vehicle meets the reverse driving determination condition, it indicates that the target vehicle is driving in reverse. Then, continuously capture based on the target license plate. Specifically, the intelligent capture device associates the capture operation with the target license plate to ensure that the subsequent captured images are all of the vehicle with this specific license plate. That is to say, the intelligent capture device "locks" the target vehicle driving in reverse according to the target license plate information and activates the continuous capture function. Within a certain time range (for example, the next few seconds or dozens of seconds), continuously capture the target vehicle at a relatively high frame rate (such as 5 frames per second or higher) to comprehensively record the process of the target vehicle's reverse driving behavior and obtain an image sequence reflecting its reverse driving state; at the same time, automatically adjust the shooting parameters (such as exposure, focal length, etc.) according to the actual environmental conditions (such as light changes, weather conditions, etc.) to ensure that the captured images are clear and distinguishable, so as to ensure that the target vehicle and its license plate can be clearly displayed in the images; all the captured images of the target vehicle driving in reverse are arranged in the order of shooting time to form a vehicle reverse driving capture set, comprehensively showing information such as the starting position, driving trajectory, and final state of the vehicle driving in reverse.
[0042] Furthermore, step S500 further includes step S510, if the target vehicle meets the reverse driving determination condition, obtain a first reverse driving capture photo based on the target license plate; step S520, based on the target license plate, obtain a second reverse driving capture photo and a third reverse driving capture photo according to the continuous capture constraint condition; step S530, generate the vehicle reverse driving capture set according to the first reverse driving capture photo, the second reverse driving capture photo, and the third reverse driving capture photo.
[0043] Step S510 further includes that the continuous capture constraint condition is that the front of the target vehicle is directly facing the mobile vehicle and the target vehicle coordinate is offset.
[0044] Preferably, after determining that the target vehicle meets the reverse driving determination condition (i.e., the front of the target vehicle is facing the mobile vehicle), the intelligent capture device immediately performs the first capture on the target vehicle based on the recognized target license plate information. At this time, the device quickly adjusts the shooting parameters (such as exposure, focus, etc.) to obtain a clear photo containing the target vehicle and its license plate, which is used as the first reverse driving capture photo, recording the state of the target vehicle at the moment of being determined to be driving in reverse. Then, based on the target license plate and according to the continuous capture constraint conditions, the target vehicle is captured to obtain the second reverse driving capture photo, further showing the state changes of the target vehicle during the reverse driving process. Among them, when the target vehicle meets the reverse driving determination condition (i.e., the front is facing the mobile vehicle), it is possible to trigger the continuous capture operation, indicating that only when the target vehicle shows an obvious reverse driving posture and drives towards the direction of the mobile vehicle does it meet the basic premise of continuous capture; the target vehicle coordinate shifts (indicating that the vehicle is moving) to ensure that the continuously captured photos can record different states and positions of the target vehicle during the reverse driving process. Similarly, the device continues to perform the third capture according to the continuous capture constraint conditions to obtain the third reverse driving capture photo, also in order to more comprehensively present the reverse driving behavior of the target vehicle and supplement more detailed information; the first reverse driving capture photo, the second reverse driving capture photo, and the third reverse driving capture photo are combined to form a vehicle reverse driving capture set, which contains three reverse driving photos of the target vehicle at different time points or in different states, complementing and corroborating each other, so as to more accurately determine the reverse driving behavior of the vehicle.
[0045] Step S600, report the vehicle reverse driving capture set to the traffic management platform.
[0046] Preferably, all the photos and relevant data of the vehicle reverse driving capture set (such as capture time, shooting location, license plate information of the target vehicle, etc.) are sorted out and encapsulated into a data packet in a certain format. A network connection is established through the built-in data transmission unit (such as 4G, 5G communication module or Wi-Fi module, etc.), and the encapsulated vehicle reverse driving capture set data is sent to the traffic management platform through the network. Then, the data is received and verified, which may include checking the integrity of the data (such as whether all photos and relevant information are received completely), the correctness of the data format (whether it meets the requirements of the platform), and the authenticity of the data (such as verifying the source and authenticity of the data through information such as time stamps and device identifiers). The data that passes the verification will be stored in the database of the traffic management platform, and the database classifies and manages these data, for example, indexing according to fields such as time, location, and license plate number, facilitating subsequent quick query and retrieval by law enforcement officers; and then dealing with the reverse driving vehicles according to these data, such as sending violation notices, imposing fines or deductions and other penalty measures.
[0047] In the above text, with reference to Figure 1A method for intelligent warning of road traffic reverse is described in detail according to an embodiment of the present invention. Next, a system for intelligent warning of road traffic reverse according to an embodiment of the present invention will be described with reference to Figure 2 Describe a system for intelligent warning of road traffic reverse according to an embodiment of the present invention.
[0048] A system for intelligent warning of road traffic reverse according to an embodiment of the present invention is used to solve the technical problems existing in the prior art, such as limited monitoring range, insufficient law enforcement manpower, inability to supervise all time and all sections of the road, and difficulty in timely detecting and investigating reverse behaviors in complex road conditions and remote sections. It achieves the technical effects of improving law enforcement efficiency, realizing all-time and all-section dynamic supervision, and improving the accuracy of reverse behavior recognition and the timeliness of warning. As Figure 2 shown, a system for intelligent warning of road traffic reverse includes: a capture device installation module 10, a picture acquisition module 20, a target detection module 30, a reverse judgment module 40, a reverse capture module 50, and a capture set reporting module 60.
[0049] The capture device installation module 10 is used to install an intelligent capture device on a mobile vehicle; the picture acquisition module 20 is used to collect the front picture of the vehicle in real time through the intelligent capture device during the driving process of the mobile vehicle; the target detection module 30 is used to perform same-lane target detection based on the front picture of the vehicle to determine the target vehicle and the target license plate; the reverse judgment module 40 is used to judge whether the target vehicle meets the reverse judgment condition; the reverse capture module 50 is used to continuously capture based on the target license plate if the target vehicle meets the reverse judgment condition to obtain a vehicle reverse capture set; the capture set reporting module 60 is used to report the vehicle reverse capture set to the traffic management platform.
[0050] Next, the specific configuration of the target detection module 30 will be described in detail. The target detection module 30 further includes: performing vehicle recognition based on the front picture of the vehicle to obtain multiple recognized vehicles; obtaining the current driving lane information of the mobile vehicle; performing same-lane detection on the multiple recognized vehicles according to the current driving lane information to obtain the target vehicle; performing license plate feature recognition on the target vehicle to obtain the target license plate.
[0051] Next, the specific configuration of the target detection module 30 will be further described in detail. The target detection module 30 further includes: performing lane detection on the multiple recognized vehicles to obtain multiple vehicle lane information; performing same-lane judgment on the multiple vehicle lane information according to the current driving lane information to obtain multiple same-lane judgment results; matching the multiple recognized vehicles according to the multiple same-lane judgment results to generate the target vehicle.
[0052] Next, the specific configuration of the reverse driving determination module 40 will be described in detail. The reverse driving determination module 40 further includes: detecting the orientation of the target vehicle based on the mobile vehicle to obtain a vehicle orientation detection result; and determining whether the vehicle orientation detection result meets the reverse driving determination condition.
[0053] Next, the specific configuration of the reverse driving determination module 40 will be further described in detail. The reverse driving determination module 40 further includes: the reverse driving determination condition is that the front of the target vehicle is directly facing the mobile vehicle.
[0054] Next, the specific configuration of the reverse driving capture module 50 will be described in detail. The reverse driving capture module 50 further includes: if the target vehicle meets the reverse driving determination condition, obtaining a first reverse driving capture photo based on the target license plate; obtaining a second reverse driving capture photo and a third reverse driving capture photo based on the target license plate according to the continuous capture constraint condition; and generating the vehicle reverse driving capture set according to the first reverse driving capture photo, the second reverse driving capture photo, and the third reverse driving capture photo.
[0055] Next, the specific configuration of the reverse driving capture module 50 will be further described in detail. The reverse driving capture module 50 further includes: the continuous capture constraint condition is that the front of the target vehicle is directly facing the mobile vehicle and the target vehicle coordinate deviates.
[0056] A road traffic reverse driving intelligent warning system provided by an embodiment of the present invention can execute a road traffic reverse driving intelligent warning method provided by any embodiment of the present invention, and has function modules and beneficial effects corresponding to the execution method.
[0057] Figure 3 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention, showing a block diagram of an exemplary electronic device suitable for implementing the embodiments of the present invention. Figure 3 The displayed electronic device is only an example and should not bring any limitation to the functions and usage scope of the embodiments of the present invention. The electronic device is presented in the form of a general computing device, and its components may include, but are not limited to, an input device 401, a processor 402, a memory 403, and an output device 404. Among them, the processor 402 may be one or more; the memory 403 may include a computer-readable medium and at least one program product, and this program product has a set (at least one) of program modules, and these program modules are configured to execute the functions of the embodiments of the present application.
[0058] The memory 403 shown in the embodiments of the present invention may adopt any combination of one or more computer-readable media; the computer-readable storage medium may be, but is not limited to, infrared rays, semiconductor systems, devices or components, or any combination of the above, and is used to store software programs, computer-executable programs and modules, such as the program instructions / modules corresponding to a method for intelligent warning of traffic road reverse in the embodiments of the present invention. The processor 402 executes various functional applications and data processing of the computer device by running the software programs, instructions and modules stored in the memory 403, that is, implements the above-mentioned method for intelligent warning of traffic road reverse.
[0059] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, however, any number of different modules may be used and run on the user terminal and / or the server. The included individual units and modules are only divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be realized; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the present invention.
[0060] The above specific embodiments do not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present application shall be included within the protection scope of the present application.
Claims
1. A road traffic wrong-way intelligent warning method, characterized in that the method comprises: Installing intelligent capture equipment on mobile vehicles; During the driving of the mobile vehicle, the image in front of the vehicle is captured in real time by the intelligent capture device; Performing lane target detection based on the image in front of the vehicle to determine the target vehicle and target license plate; Determining whether the target vehicle meets a wrong-way determination condition; If the target vehicle meets the wrong-travel determination condition, continuously capture the target vehicle based on its license plate to obtain a wrong-travel vehicle capture set; The vehicle reverse driving snapshot set is reported to the traffic management platform.
2. The intelligent warning method for wrong-way driving in road traffic according to claim 1, characterized in that the method comprises: detecting a target in the same lane based on the image in front of the vehicle to determine the target vehicle and the target license plate; Perform vehicle identification based on the image in front of the vehicle to obtain multiple identified vehicles; Obtaining current driving lane information of the mobile vehicle; Perform same-lane detection on the multiple identified vehicles according to the current driving lane information to obtain the target vehicle; Perform license plate feature recognition on the target vehicle to obtain the target license plate.
3. The intelligent warning method for wrong-way driving in road traffic according to claim 2, wherein the step of performing same-lane detection on the multiple identified vehicles based on the current driving lane information to obtain the target vehicle comprises: Performing lane detection on the multiple identified vehicles to obtain lane information of multiple vehicles; Performing same-lane determination on the lane information of the multiple vehicles according to the current driving lane information to obtain multiple same-lane determination results; The multiple identified vehicles are matched according to the multiple same-lane judgment results to generate the target vehicle.
4. The method for intelligent road traffic wrong-way warning according to claim 1, wherein determining whether the target vehicle meets wrong-way determination conditions comprises: Taking the mobile vehicle as a reference, performing a direction detection on the target vehicle to obtain a vehicle direction detection result; It is determined whether the vehicle direction detection result meets the wrong-way determination condition.
5. A road traffic wrong-way intelligent warning method as described in claim 1, characterized in that the wrong-way determination condition is that the front of the target vehicle is facing the mobile vehicle.
6. The method for intelligent road traffic wrong-way warning according to claim 1, wherein if the target vehicle meets the wrong-way determination condition, continuous capture is performed based on the target license plate to obtain a wrong-way vehicle capture set, including: If the target vehicle meets the wrong-traffic determination condition, obtaining a first wrong-traffic snapshot photo based on the target license plate; Based on the target license plate and in accordance with a continuous capture constraint condition, obtaining a second reverse-traffic capture photo and a third reverse-traffic capture photo; The vehicle wrong-travel snapshot set is generated based on the first wrong-travel snapshot photo, the second wrong-travel snapshot photo, and the third wrong-travel snapshot photo.
7. A road traffic wrong-way intelligent warning method as described in claim 6, characterized in that the continuous capture constraint condition is that the front of the target vehicle is facing the mobile vehicle and the coordinates of the target vehicle are offset.
8. A road traffic wrong-way intelligent warning system, characterized in that the system is used to implement the road traffic wrong-way intelligent warning method according to any one of claims 1 to 7, and the system comprises: Capture device installation module, used to install intelligent capture devices on mobile vehicles; A picture acquisition module is used to capture the picture in front of the vehicle in real time through the intelligent capture device during the driving process of the mobile vehicle; A target detection module is used to detect targets in the same lane based on the image in front of the vehicle and determine the target vehicle and target license plate; A wrong-traffic judgment module is used to judge whether the target vehicle meets the wrong-traffic judgment condition; A wrong-traffic capture module is used to continuously capture the target vehicle based on the target license plate if the target vehicle meets the wrong-traffic determination condition, and obtain a wrong-traffic capture set of vehicles; The snapshot set reporting module is used to report the vehicle reverse driving snapshot set to the traffic management platform.
9. An electronic device, characterized in that the electronic device comprises: a memory for storing executable instructions; The processor is configured to implement the road traffic reverse intelligent warning method according to any one of claims 1 to 7 when executing the executable instructions stored in the memory.