Method for Detecting Traffic Violations, Cloud Platform and Road Test Controller

Abstract

The present application provides a method for detecting traffic violations, a cloud platform, and a roadside controller. The method includes: receiving target image information and target perception information of a target area at a target detection time, where the target detection time is the time when the roadside controller detects that a target object has a violation action; based on at least one of the target image information and the target perception information, determining whether there is occlusion in the target area at the target detection time, and in the case of occlusion, based on the target perception information, drawing a radar view screen and a three-dimensional view screen of the target area at the target detection time; sending the image view screen, the radar view screen, and the three-dimensional view screen to a display screen of the cloud platform, so that an administrator can re-check the violation action based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen, thereby solving the problem of low accuracy in detecting violation actions in traffic caused by occlusion in the prior art.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to a traffic violation detection method, a cloud platform, a road test controller, and a traffic violation detection system. Background Art

[0002] Traffic management for cities usually uses cameras and / or LiDAR devices deployed on streets and / or intersections to detect various violations on the road, such as running red lights, speeding, and driving against the flow.

[0003] For the method of using visual devices such as cameras for violation detection, it is usually based on a solution combining video streaming and machine learning, and the violation on the road is detected by parsing the video content or obtaining key frames. For the solution combining cameras with laser radar, the violation on the road is usually detected through the video content or image information captured by the camera and the perception information of the laser radar.

[0004] The above two methods do not take into account the occlusion situation, such as the occlusion in front of the viewing area, the occlusion between objects, and the camera dirt, etc. In the case of occlusion, due to the existence of blind spots in the field of view, the detection of illegal actions in traffic is not only low in accuracy, but also has problems such as missed detection and false alarms. Summary of the invention

[0005] The main purpose of the present application is to provide a traffic violation detection method, a cloud platform, a road test controller and a traffic violation detection system, so as to at least solve the problem of low accuracy in detecting illegal actions in traffic due to occlusion in the prior art.

[0006] To achieve the above object, according to one aspect of the present application, a method for detecting traffic violations is provided. The detection method is applied to a cloud platform and includes: receiving target image information and target perception information of a target area at a target detection time, where the target detection time is the time when a roadside controller detects that a target object has a violation action, the target image information is the image information of the target area captured by a camera at the target detection time, and the target perception information is the perception information of the target area collected by a lidar at the target detection time. The target object includes at least one of the following: a vehicle, a pedestrian; based on at least one of the target image information and the target perception information, determining whether there is occlusion in the target area at the target detection time. In the case of occlusion, based on the target perception information, drawing a radar view screen and a three-dimensional view screen of the target area at the target detection time; sending the image view screen, the radar view screen, and the three-dimensional view screen to a display screen of the cloud platform so that an administrator can re-check the violation action based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen, where the image view screen is a screen composed of the target image information.

[0007] Optionally, based on at least one of the target image information and the target perception information, determining whether there is occlusion in the target area at the target detection time includes at least one of the following: based on the target perception information, determining the position information of the target object in the world coordinate system, and based on the position information of the lidar in the world coordinate system and the position information of the target object, determining whether there is occlusion in the target area at the target detection time; performing target detection on the target image information to obtain a plurality of target bounding boxes, and based on the plurality of target bounding boxes, determining whether there is occlusion in the target area at the target detection time. The target bounding box is the bounding box of a target object in the target image information, and the target object includes the target object and other objects. The other objects include at least one of the following: a building, a tree, a vehicle other than the target object, and a pedestrian other than the target object.

[0008] Optionally, determining whether there is occlusion in the target area at the target detection moment based on the position information of the lidar and the position information of the target object in the world coordinate system includes: constructing a straight line segment between the position information of the lidar and the position information of the target object based on the position information of the lidar and the position information of the target object; determining whether there is another object passing through the straight line segment; in the case that there is another object passing through the straight line segment, determining that there is occlusion in the target area at the target detection moment; in the case that there is no other object passing through the straight line segment, determining that there is no occlusion in the target area at the target detection moment.

[0009] Optionally, determining whether there is occlusion in the target area at the target detection moment based on multiple target bounding boxes includes: determining whether there is overlap between any two of the target bounding boxes; in the case that there is overlap between any two of the target bounding boxes, determining that there is occlusion in the target area at the target detection moment; in the case that there is no overlap between any two of the target bounding boxes, determining that there is no occlusion in the target area at the target detection moment.

[0010] Optionally, the detection method further includes: in the case that it is detected that there is occlusion in the target area at the target detection moment, sending a prompt message to the display screen, where the prompt message is used to indicate the existence of occlusion in the target area at the target detection moment.

[0011] Optionally, drawing a radar view screen and a 3D view screen of the target area at the target detection moment based on the target perception information includes: drawing a radar view screen of the target area at the target detection moment based on the target perception information; performing 3D digital twin on the radar view screen to obtain the 3D view screen.

[0012] According to another aspect of the present application, a method for detecting traffic violations is provided. The detection method is applied to a road test controller, and the detection method includes: based on the target image information captured by a camera and the target perception information collected by a lidar, detecting whether a target object in a target area has a violation action, where the target object includes at least one of the following: a vehicle, a pedestrian; in the case where the target object in the target area has a violation action, determining the moment when the target object has the violation action as the target detection moment; sending the target image information and the target perception information corresponding to the target detection moment to a cloud platform, so that the cloud platform determines whether there is occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information. In the case of occlusion, based on the target perception information, drawing a radar view screen and a three-dimensional view screen of the target area at the target detection moment, and sending the image view screen, the radar view screen, and the three-dimensional view screen to a display screen of the cloud platform, so that an administrator can perform a re-inspection of the violation action based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen, where the image view screen is a screen composed of the target image information.

[0013] Optionally, the process by which the cloud platform determines whether there is occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information includes at least one of the following: based on the target perception information, determining the position information of the target object in the world coordinate system, and based on the position information of the lidar in the world coordinate system and the position information of the target object, determining whether there is occlusion in the target area at the target detection moment; performing target detection on the target image information to obtain a plurality of target bounding boxes, and based on the plurality of target bounding boxes, determining whether there is occlusion in the target area at the target detection moment, where the target bounding box is the bounding box of a target object in the target image information, and the target object includes the target object and other objects, and the other objects include at least one of the following: a building, a tree, a vehicle other than the target object, a pedestrian other than the target object.

[0014] Optionally, the process by which the cloud platform determines whether there is occlusion in the target area at the target detection moment based on the position information of the lidar and the position information of the target object in the world coordinate system includes: constructing a straight line segment between the position information of the lidar and the position information of the target object based on the position information of the lidar and the position information of the target object; determining whether there is another object passing through the straight line segment; in the case that there is another object passing through the straight line segment, determining that there is occlusion in the target area at the target detection moment; in the case that there is no other object passing through the straight line segment, determining that there is no occlusion in the target area at the target detection moment.

[0015] Optionally, the process by which the cloud platform determines whether there is occlusion in the target area at the target detection moment based on a plurality of the target bounding boxes includes: determining whether there is an overlap between any two of the target bounding boxes; in the case that there is an overlap between any two of the target bounding boxes, determining that there is occlusion in the target area at the target detection moment; in the case that there is no overlap between any two of the target bounding boxes, determining that there is no occlusion in the target area at the target detection moment.

[0016] Optionally, in the case that the cloud platform detects that there is occlusion in the target area at the target detection moment, the cloud platform sends a prompt message to the display screen, and the prompt message is used to indicate the existence of occlusion in the target area at the target detection moment.

[0017] Optionally, the process by which the cloud platform draws the radar view screen and the three-dimensional view screen of the target area at the target detection moment based on the target perception information includes: drawing the radar view screen of the target area at the target detection moment based on the target perception information; performing three-dimensional digital twin on the radar view screen to obtain the three-dimensional view screen.

[0018] According to another aspect of the present application, a cloud platform is provided, including: a first receiving unit, configured to receive target image information and target perception information of a target area at a target detection moment, where the target detection moment is the moment when a road test controller detects that a target object has a violation action, the target image information is the image information of the target area captured by a camera at the target detection moment, the target perception information is the perception information of the target area collected by a lidar at the target detection moment, and the target object includes at least one of the following: a vehicle, a pedestrian; a first determination unit, configured to determine whether there is occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information, and in the case of occlusion, draw a radar view screen and a three-dimensional view screen of the target area at the target detection moment based on the target perception information; a first sending unit, configured to send an image view screen, the radar view screen, and the three-dimensional view screen to a display screen of the cloud platform, so that an administrator can recheck the violation action based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen, and the image view screen is a screen composed of the target image information.

[0019] According to yet another aspect of the present application, a road test controller is provided, including: a detection unit, configured to detect whether a target object in a target area has a violation action based on target image information captured by a camera and target perception information collected by a lidar, where the target object includes at least one of the following: a vehicle, a pedestrian; a second determination unit, configured to, in the case that the target object in the target area has a violation action, determine the moment when the target object has the violation action as the target detection moment; a third sending unit, configured to send the target image information and the target perception information corresponding to the target detection moment to a cloud platform, so that the cloud platform determines whether there is occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information, and in the case of occlusion, draw a radar view screen and a three-dimensional view screen of the target area at the target detection moment based on the target perception information, and send an image view screen, the radar view screen, and the three-dimensional view screen to the display screen of the cloud platform, so that an administrator can recheck the violation action based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen, and the image view screen is a screen composed of the target image information.

[0020] According to one aspect of the present application, a traffic violation detection system is provided, including: a cloud platform for performing any one of the traffic violation detection methods; a roadside controller communicating with the cloud platform for performing any one of the traffic violation detection methods.

[0021] Applying the technical solution of the present application, first, when the roadside controller detects that a target object in a target area has a violation action at a target detection moment, it sends the target image information of the target area at the target detection moment captured by the camera and the target perception information of the target area at the target detection time collected by the lidar to the cloud platform, and the cloud platform receives the target image information and the target perception information sent by the roadside controller; then, the cloud platform determines whether there is occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information. In the case of occlusion, based on the target perception information, it draws a radar view screen and a three-dimensional view screen of the target area at the target detection moment; finally, the cloud platform sends the image view screen, the radar view screen, and the three-dimensional view screen to the display screen, so that the administrator can re-check the violation action of the target object based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen displayed on the display screen. The detection method of this solution considers the occlusion situation, and determines whether there is occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information. In the case of occlusion, it draws a radar view screen and a three-dimensional view screen of the target area at the target detection moment, so as to facilitate the administrator to quickly obtain the specific situation of the target area at the target detection moment, ensure that it can be more accurately determined whether the target object has a violation action, avoid false alarms and missed detections, and thus solve the problem of low accuracy in detecting traffic violation actions due to occlusion in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings forming a part of this application are used to provide a further understanding of this application. The schematic embodiments of this application and their descriptions are used to explain this application and do not constitute an improper limitation to this application. In the drawings:

[0023] Figure 1 Shows a hardware structure block diagram of a mobile terminal for performing a traffic violation detection method provided in an embodiment of the present application;

[0024] Figure 2 Shows a flowchart of a traffic violation detection method provided in an embodiment of the present application;

[0025] Figure 3 Shows a schematic diagram of a radar view screen provided in an embodiment of the present application;

[0026] Figure 4 Shows a schematic flow chart of a traffic violation detection method provided according to an embodiment of the present application;

[0027] Figure 5 Shows a schematic flow chart of a specific traffic violation detection method provided according to an embodiment of the present application;

[0028] Figure 6 Shows a schematic structural diagram of a cloud platform provided according to an embodiment of the present application;

[0029] Figure 7 Shows a schematic structural diagram of a road test controller provided according to an embodiment of the present application.

[0030] Among them, the above-mentioned drawings include the following reference numerals:

[0031] 102, processor; 104, memory; 106, transmission device; 108, input / output device. Detailed implementation manners

[0032] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the drawings and in combination with the embodiments.

[0033] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such used data may be interchanged under appropriate circumstances so as to describe the embodiments of the present application here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily need to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these process, method, product or device.

[0035] As introduced in the background art, due to the occlusions existing in front of the viewing area, the occlusions between objects, camera dirt, etc., the detection of traffic violation actions not only has a low accuracy rate, but also there will be missed detections and false alarms. To solve the above problems, embodiments of the present application provide a traffic violation detection method, a cloud platform, a roadside controller, and a traffic violation detection system.

[0036] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention.

[0037] The method embodiments provided in the embodiments of the present application can be executed on a mobile terminal, a computer terminal, or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 is a hardware structure block diagram of a mobile terminal of a traffic violation detection method according to an embodiment of the present invention. As Figure 1 shown, the mobile terminal may include one or more ( Figure 1 only one is shown in the figure) processors 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Among them, the above mobile terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those of ordinary skill in the art can understand that Figure 1 the structure shown is only schematic and does not limit the structure of the above mobile terminal. For example, the mobile terminal may further include more or fewer components than Figure 1 shown in the figure, or have a different configuration from Figure 1 shown in the figure.

[0038] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the traffic violation detection method in the embodiments of the present invention. The processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, that is, implements the above-mentioned method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memories. In some instances, the memory 104 may further include a memory remotely disposed relative to the processor 102, and these remote memories can be connected to the mobile terminal through a network. Examples of the above-mentioned network include but are not limited to the Internet, enterprise intranet, local area network, mobile communication network and their combinations. The transmission device 106 is used to receive or send data via a network. Specific examples of the above-mentioned network may include the wireless network provided by the communication provider of the mobile terminal. In one instance, the transmission device 106 includes a network adapter (Network Interface Controller, abbreviated as NIC), which can be connected to other network devices through a base station and thus can communicate with the Internet. In one instance, the transmission device 106 may be a radio frequency (Radio Frequency, abbreviated as RF) module, which is used to communicate with the Internet wirelessly.

[0039] In this embodiment, a traffic violation detection method running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0040] Figure 2 It is a flowchart of the traffic violation detection method according to the embodiments of the present application. This detection method is applied in a cloud platform, such as Figure 2 As shown, this detection method includes the following steps:

[0041] Step S201, receiving the target image information and target perception information of the target area at the target detection moment. The above-mentioned target detection moment is the moment when the roadside controller detects that the target object has a violation action. The above-mentioned target image information is the image information of the target area captured by the camera at the above-mentioned target detection moment. The above-mentioned target perception information is the perception information of the target area collected by the lidar at the above-mentioned target detection moment. The above-mentioned target object includes at least one of the following: vehicle, pedestrian;

[0042] Specifically, the above-mentioned target area can be the area that can be detected by both the camera and the lidar. For example, the above-mentioned target area can be an area within 10 meters with the positions of the camera and the lidar as the origin and the directions in which the camera and the lidar are facing. In a specific application scenario, the above-mentioned target area can be an intersection area. Of course, the above-mentioned target area is not limited to the intersection area and can also be an area on a regular road.

[0043] In the actual application process, the above-mentioned camera and lidar can be deployed on the intersection signal pole or on the street lamp pole. In addition, in this application, the device for capturing the target image information includes, but is not limited to, the camera, and can also be other visual detection devices. The device for collecting the target perception information includes, but is not limited to, the lidar, and can also be other devices that can obtain perception information.

[0044] In a specific embodiment of the present application, the above-mentioned target perception information can also be the perception information collected by the lidar and obtained after contour processing of the point cloud information collected by the lidar.

[0045] Specifically, the above-mentioned illegal actions include, but are not limited to: vehicles running red lights, vehicles driving in reverse, vehicles speeding, and pedestrians running red lights.

[0046] Step S202: Based on at least one of the above-mentioned target image information and the above-mentioned target perception information, determine whether there is an occlusion in the above-mentioned target area at the above-mentioned target detection moment. In the case of an occlusion, based on the above-mentioned target perception information, draw the radar view screen and the three-dimensional view screen of the above-mentioned target area at the above-mentioned target detection moment;

[0047] In the above step S202, as Figure 3 shown, the radar view screen is the screen of the target area at the target detection moment obtained by contour processing of the point cloud information collected by the lidar.

[0048] Step S203: Send the image view screen, the above-mentioned radar view screen, and the above-mentioned three-dimensional view screen to the display screen of the above-mentioned cloud platform so that the administrator can conduct a re-inspection of illegal actions based on at least one of the above-mentioned image view screen, the above-mentioned radar view screen, and the above-mentioned three-dimensional view screen. The above-mentioned image view screen is the screen composed of the above-mentioned target image information.

[0049] The image view screen in the above step S203 is the screen composed of the target image information. That is to say, the image view screen is the screen corresponding to the target image information of the target area at the target detection moment.

[0050] Through this embodiment, first, when the road test controller detects that the target object in the target area has a violation action at the target detection moment, it sends the target image information of the target area captured by the camera at the target detection moment and the target perception information of the target area collected by the lidar at the target detection time to the cloud platform, and the cloud platform receives the target image information and the target perception information sent by the road test controller; then, the cloud platform determines whether there is occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information. In the case of occlusion, based on the target perception information, it draws the radar view screen and the three-dimensional view screen of the target area at the target detection moment; finally, the cloud platform sends the image view screen, the radar view screen, and the three-dimensional view screen to the display screen, so that the administrator can re-check the violation action of the target object based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen displayed on the display screen. The detection method of this solution considers the occlusion situation, and determines whether there is occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information. In the case of occlusion, it draws the radar view screen and the three-dimensional view screen of the target area at the target detection moment, so as to facilitate the administrator to quickly obtain the specific situation of the target area at the target detection moment, ensure that it can be more accurately determined whether the target object has a violation action, avoid false alarms and missed detections, and thus solve the problem of low accuracy of detecting violation actions in traffic caused by occlusion in the prior art.

[0051] For the detection method of this application, the road test controller based on the target image information and the target perception information, real-time detects whether there is a violation action of the target object in the target area. When the road test controller detects that there is a violation action in the target area, it determines the moment when the target object has a violation action as the target detection moment. The road test controller then sends the target image information and the target perception information at the target detection moment to the cloud platform. That is to say, the target image information and the target perception information received by the cloud platform in this application are sent by the road test controller when it detects a violation action, rather than receiving the target image information and the target perception information at all times. This ensures that the number of target image information and target perception information received by the cloud platform is small, which can not only reduce the computing amount of the cloud platform, but also save the memory of the cloud platform.

[0052] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0053] In order to ensure that the computational load of the cloud platform is small and it is relatively simple to determine whether there is occlusion in the target area at the target detection moment, in the specific implementation process, the above step S202 can be implemented by one of the following steps.

[0054] Step S2021: Based on the above target perception information, determine the position information of the above target object in the world coordinate system. Based on the position information of the above lidar in the above world coordinate system and the position information of the above target object, determine whether there is occlusion in the above target area at the above target detection moment;

[0055] Step S2022: Perform target detection on the above target image information to obtain a plurality of target bounding boxes. Based on the plurality of above target bounding boxes, determine whether there is occlusion in the above target area at the above target detection moment. The above target bounding box is the bounding box of the target object in the above target image information. The above target object includes the above target object and other objects. The above other objects include at least one of the following: buildings, trees, vehicles other than the above target object, and pedestrians other than the above target object.

[0056] In the above embodiment, based on the target perception information, determining the position information of the target object (i.e., the vehicle or pedestrian with a violation action) in the world coordinate system is to determine the position information of the target object in the three-dimensional world. In addition, since the position information of the lidar in the three-dimensional world is known when the lidar is deployed, a straight line segment between the lidar and the target object can be constructed relatively simply. Of course, in the actual application process, when constructing the straight line segment between the lidar and the target object, the center point of the target object in the three-dimensional world can also be determined first, and then the straight line segment between the position information of the lidar and the center point position information of the target object can be constructed.

[0057] In the actual application process, any feasible method in the prior art can be used to perform target detection on the target object in the target image information, so as to obtain a plurality of target bounding boxes. Specifically, the obtained target bounding box can be the smallest rectangular box containing the target object.

[0058] Specifically, the above vehicle other than the target object can be other vehicles in the target area except the vehicle that is the target object. The above pedestrian other than the target object can be other pedestrians in the target area except the pedestrian that is the target object.

[0059] In order to more simply determine whether there is occlusion in the target area at the target detection moment, the above-mentioned step S2021 of this application can also be implemented through the following steps: Based on the above-mentioned position information of the lidar and the position information of the above-mentioned target object, construct a straight line segment between the above-mentioned position information of the lidar and the above-mentioned position information of the above-mentioned target object; Determine whether there is any other object passing through the above-mentioned straight line segment; In the case that there is any other object passing through the above-mentioned straight line segment, determine that there is occlusion in the above-mentioned target area at the above-mentioned target detection moment; In the case that there is no other object passing through the above-mentioned straight line segment, determine that there is no occlusion in the above-mentioned target area at the above-mentioned target detection moment.

[0060] In some specific embodiments, the above-mentioned step S2022 can also be implemented in the following manner: Determine whether there is overlap between any two of the above-mentioned target bounding boxes; In the case that there is overlap between any two of the above-mentioned target bounding boxes, determine that there is occlusion in the above-mentioned target area at the above-mentioned target detection moment; In the case that there is no overlap between any two of the above-mentioned target bounding boxes, determine that there is no occlusion in the above-mentioned target area at the above-mentioned target detection moment. In this embodiment, by determining whether there is overlap between any two target bounding boxes, it is determined whether there is occlusion in the target area at the target detection moment, which further realizes a relatively simple determination of whether there is occlusion in the target area at the target detection moment, and further ensures that the computational amount of the cloud platform for determining whether there is occlusion in the target area at the target detection moment is small.

[0061] In some embodiments, the detection method of this application further includes step S204: When it is detected that there is occlusion in the above-mentioned target area at the above-mentioned target detection moment, send a prompt message to the above-mentioned display screen, and the above-mentioned prompt message is used to indicate the existence of occlusion in the above-mentioned target area at the above-mentioned target detection moment. In this solution, when the cloud platform detects that there is occlusion in the target area at the target detection moment, it sends a prompt message to the display screen, so that the administrator can timely know the possibility of false alarms for such illegal actions, and further timely reminds the management personnel to recheck the illegal actions based on the radar view screen and the 3D view screen.

[0062] In one embodiment of this application, the above-mentioned step S202 can also be implemented through step S2023: Based on the above-mentioned target perception information, draw a radar view screen of the above-mentioned target area at the above-mentioned target detection moment; Perform 3D digital twin on the above-mentioned radar view screen to obtain the above-mentioned 3D view screen, that is to say, on the basis of the radar view screen, combine the urban building twin and the 3D twin of the target object to obtain the 3D view screen.

[0063] In the actual application process, in order to ensure that the entire radar view screen is relatively neat and convenient for administrators to process efficiently, the contour lines of the target object and the objects within 10 meters nearby are drawn. Specifically, see Figure 3 as shown.

[0064] In addition, in the above-mentioned embodiment, the administrator can perform operations such as high-degree-of-freedom rotation, movement, and scaling on the above three-dimensional view screen.

[0065] In addition, based on the operation controls displayed on the display screen, the administrator can arbitrarily switch between the image view screen, the radar view screen, and the three-dimensional view screen, which ensures a high degree of operability for the administrator. When the administrator switches to the three-dimensional view screen, the administrator can also choose to display it in the default perspective. Of course, the administrator can also rotate, move, or scale the three-dimensional view screen, etc. Among them, the above-mentioned default perspective can be the direction of the line connecting the position information of the lidar and the target object.

[0066] In a typical embodiment of the present application, a traffic violation detection method is also provided. The detection method is applied to a roadside controller. As Figure 4 shown, the detection method includes:

[0067] Step S401: Based on the target image information captured by the camera and the target perception information collected by the lidar, detect whether there are any violation actions of the target object in the target area. The above target object includes at least one of the following: vehicle, pedestrian;

[0068] In the above step S401, the roadside controller can adopt any feasible method in the prior art to determine whether there are any violation actions of the target object in the target area based on the target image information captured by the camera and the target perception information collected by the lidar, and at the same time combine traffic rules. In the present application, the specific method for the roadside controller to determine whether there are any violation actions of the target object in the target area based on the target image information captured by the camera and the target perception information collected by the lidar is not limited.

[0069] Specifically, the above target area can be the area that can be detected by both the camera and the lidar. For example, the above target area can be an area within 10 meters with the positions of the camera and the lidar as the origin and the directions in which the camera and the lidar are facing. In a specific application scenario, the above target area can be an intersection area. Of course, the above target area is not limited to the intersection area, and can also be an area on a conventional road.

[0070] In the actual application process, the above-mentioned camera and lidar can be deployed on the intersection signal pole or on the street lamp pole. In addition, in this application, the device for capturing target image information includes, but is not limited to, a camera, and can also be other visual detection devices. The device for collecting target perception information includes, but is not limited to, a lidar, and can also be other devices that can obtain perception information.

[0071] In a specific embodiment of this application, the above-mentioned target perception information can also be the perception information collected by the lidar and processed for the contour of the point cloud information collected by the lidar.

[0072] Specifically, the above-mentioned illegal actions include, but are not limited to: vehicles running red lights, vehicles going in the wrong direction, vehicles speeding, and pedestrians running red lights.

[0073] Step S402: When there is an illegal action of the target object in the above-mentioned target area, determine the moment when the illegal action of the target object occurs as the target detection moment;

[0074] In the above step S402, the moment when the target object in the target area has an illegal action is determined as the target detection moment. In this way, the target image information and target perception information corresponding to the target detection moment can be sent to the cloud platform later. This not only reduces the computational workload of occlusion detection on the cloud platform but also saves the storage space of the cloud platform relatively.

[0075] Step S403: Send the above-mentioned target image information and the above-mentioned target perception information corresponding to the target detection moment to the cloud platform, so that the cloud platform determines whether there is occlusion in the above-mentioned target area at the above-mentioned target detection moment based on at least one of the above-mentioned target image information and the above-mentioned target perception information. In the case of occlusion, based on the above-mentioned target perception information, draw the radar view screen and the three-dimensional view screen of the above-mentioned target area at the above-mentioned target detection moment, and send the image view screen, the above-mentioned radar view screen, and the above-mentioned three-dimensional view screen to the display screen of the above-mentioned cloud platform, so that the administrator can re-check the illegal actions based on at least one of the above-mentioned image view screen, the above-mentioned radar view screen, and the above-mentioned three-dimensional view screen. The above-mentioned image view screen is the screen composed of the above-mentioned target image information.

[0076] In the above step S403, as Figure 3 shown, the radar view screen is the screen of the target area at the target detection moment obtained by processing the contour of the point cloud information collected by the lidar.

[0077] The image view screen in the above step S403 is the screen composed of the target image information. That is to say, the image view screen is the screen corresponding to the target image information of the target area at the target detection moment.

[0078] Through the detection method of this embodiment, first, when the road test controller detects that the target object in the target area has a violation action at the target detection moment, it sends the target image information of the target area at the target detection moment captured by the camera and the target perception information of the target area at the target detection time collected by the lidar to the cloud platform, and the cloud platform receives the target image information and the target perception information sent by the road test controller; then, based on at least one of the target image information and the target perception information, the cloud platform determines whether there is occlusion in the target area at the target detection moment. In the case of occlusion, based on the target perception information, it draws the radar view screen and the three-dimensional view screen of the target area at the target detection moment; finally, the cloud platform sends the image view screen, the radar view screen, and the three-dimensional view screen to the display screen, so that the administrator can re-check the violation actions of the target object based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen displayed on the display screen. The detection method of this solution takes into account the occlusion situation, and determines whether there is occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information. In the case of occlusion, it draws the radar view screen and the three-dimensional view screen of the target area at the target detection moment, so that it is convenient for the administrator to quickly obtain the specific situation of the target area at the target detection moment, ensuring that it can be more accurately determined whether the target object has a violation action, avoiding false alarms and missed detections, and thus solving the problem of low accuracy in detecting violation actions in traffic due to occlusion in the prior art.

[0079] In order to ensure that the computational amount of the cloud platform is small and it is relatively simple to determine whether there is occlusion in the target area at the target detection moment, in some specific embodiments, the above step S403 can also be implemented through the following steps:

[0080] Step S4031: Based on the above target perception information, determine the position information of the above target object in the world coordinate system. Based on the position information of the above lidar and the position information of the above target object in the above world coordinate system, determine whether there is occlusion in the above target area at the above target detection moment;

[0081] Step S4032: Perform target detection on the above target image information to obtain a plurality of target bounding boxes. Based on the plurality of above target bounding boxes, determine whether there is occlusion in the above target area at the above target detection moment. The above target bounding box is the bounding box of the target object in the above target image information, and the above target object includes the above target object and other objects. The above other objects include at least one of the following: buildings, trees, vehicles other than the above target object, and pedestrians other than the above target object.

[0082] In the above embodiments, based on the target perception information, the position information of the target object (i.e., the vehicle or pedestrian with a violation action) in the world coordinate system is determined, which is to determine the position information of the target object in the three-dimensional world. In addition, since the position information of the lidar in the three-dimensional world is known when the lidar is deployed, a straight line segment between the lidar and the target object can be constructed relatively simply. Of course, in the actual application process, when constructing the straight line segment between the lidar and the target object, the center point of the target object in the three-dimensional world can also be determined first, and then the straight line segment between the position information of the lidar and the center point of the target object can be constructed.

[0083] In the actual application process, any feasible method in the prior art can be used to perform target detection on the target object in the target image information, so as to obtain a plurality of target bounding boxes. Specifically, the obtained target bounding box can be the smallest rectangular box containing the target object.

[0084] Specifically, the vehicle that is not the target object can be other vehicles in the target area except for the vehicle that is the target object. The pedestrian that is not the target object can be other pedestrians in the target area except for the pedestrian that is the target object.

[0085] In order to more simply determine whether there is occlusion in the target area at the target detection moment, in some embodiments, the above step S4031 can also be implemented as follows: based on the position information of the lidar and the position information of the target object, construct a straight line segment between the position information of the lidar and the position information of the target object; determine whether there is any other object passing through the straight line segment; in the case that there is any other object passing through the straight line segment, determine that there is occlusion in the target area at the target detection moment; in the case that there is no other object passing through the straight line segment, determine that there is no occlusion in the target area at the target detection moment.

[0086] In the actual application process, the above step S4032 can also be implemented as follows: determine whether there is overlap between any two of the above target bounding boxes; in the case that there is overlap between any two of the target bounding boxes, determine that there is occlusion in the target area at the target detection moment; in the case that there is no overlap between any two of the target bounding boxes, determine that there is no occlusion in the target area at the target detection moment. In this embodiment, by determining whether there is overlap between any two target bounding boxes, it is determined whether there is occlusion in the target area at the target detection moment, which further realizes a relatively simple determination of whether there is occlusion in the target area at the target detection moment, and further ensures that the computational amount of the cloud platform for determining whether there is occlusion in the target area at the target detection moment is small.

[0087] In one embodiment of the present application, when the cloud platform detects that there is an occlusion in the target area at the target detection moment, the cloud platform sends a prompt message to the display screen, and the prompt message is used to indicate that there is an occlusion in the target area at the target detection moment. In this solution, when the cloud platform detects that there is an occlusion in the target area at the target detection moment, it sends a prompt message to the display screen, so that the administrator can timely know the possibility of false alarms for such illegal actions, and further timely remind the management personnel to re-check the illegal actions based on the radar view screen and the 3D view screen.

[0088] In another embodiment of the present application, the process of the cloud platform drawing the radar view screen and the 3D view screen of the target area at the target detection moment based on the target perception information includes: drawing the radar view screen of the target area at the target detection moment based on the target perception information; performing 3D digital twin on the radar view screen to obtain the 3D view screen, that is, on the basis of the radar view screen, combining the twin of urban buildings and the 3D twin of the target object to obtain the 3D view screen.

[0089] In the actual application process, in order to ensure that the entire radar view screen is relatively neat and convenient for the administrator to process efficiently, the contour lines of the target object and the objects within 10 meters nearby are drawn, as specifically shown in Figure 3 shown.

[0090] In addition, in the above embodiment, the administrator can perform operations such as high-degree-of-freedom rotation, movement, and scaling on the 3D view screen.

[0091] In addition, the administrator can freely switch between the image view screen, the radar view screen, and the 3D view screen based on the operation controls displayed on the display screen, which ensures a high degree of operability for the administrator. When the administrator switches to the 3D view screen, the administrator can also choose to display it in the default perspective. Of course, the administrator can also rotate, move, or scale the 3D view screen, etc. Among them, the default perspective mentioned above can be the direction of the line connecting the position information of the lidar and the target object.

[0092] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the implementation process of the traffic violation detection method of the present application will be described in detail below with specific embodiments.

[0093] This embodiment relates to a specific traffic violation detection method, as shown in Figure 5 shown, and includes the following steps:

[0094] Step S1: The road test controller receives the target image information and the target perception information in real time, and based on the received target image information and target perception information, and in accordance with the preset traffic rules, determines whether there is a violation action of the target object in the target area (that is, the road test controller detects whether there is a violation action).

[0095] Step S2: When the road test controller detects that there is a violation action of the target object in the target area, the road test controller determines the moment when the target object has a violation action as the target detection moment. When the road test controller does not detect that there is a violation action of the target object in the target area, the road test controller continues to receive the target image information and the target perception information in real time.

[0096] Step S3: The road test controller sends the target image information and the target perception information at the target detection moment to the cloud platform.

[0097] Step S4: The cloud platform determines whether there is occlusion in the target area at the target detection moment based on one of the received target image information and target perception information at the target detection moment.

[0098] Step S5: When the cloud platform detects that there is occlusion in the target area at the target detection moment, the cloud platform sends a prompt message to the display screen so that the administrator can timely know that there is a problem of false alarm for the violation action at the target detection moment. When the cloud platform does not detect that there is occlusion in the target area at the target detection moment, the process ends.

[0099] Step S6: When the cloud platform detects that there is occlusion in the target area at the target detection moment, based on the target perception information of the target area at the target detection moment, a radar view screen and a three-dimensional view screen are drawn, and the drawn radar view screen, three-dimensional view screen and image view screen are sent to the display screen.

[0100] Step S7: The administrator rechecks the violation action of the target object at the target detection moment based on one or more of the image view screen, radar view screen and three-dimensional view screen displayed on the display screen.

[0101] The embodiment of the present application also provides a cloud platform. It should be noted that the cloud platform of the embodiment of the present application can be used to execute the detection method for traffic violations provided by the embodiment of the present application. The device for implementing the above embodiments and the preferred implementation manners has been described and will not be repeated here. As used below, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0102] The cloud platform provided by the embodiments of the present application will be introduced below.

[0103] Figure 6 It is a schematic structural diagram of the cloud platform according to the embodiments of the present application. As Figure 6 shown, the cloud platform includes:

[0104] A first receiving unit 10, configured to receive target image information and target perception information of a target area at a target detection moment, where the target detection moment is the moment when a road test controller detects that a target object has a violation action, the target image information is the image information of the target area captured by a camera at the target detection moment, the target perception information is the perception information of the target area collected by a lidar at the target detection moment, and the target object includes at least one of the following: a vehicle, a pedestrian;

[0105] Specifically, the target area may be an area that can be jointly detected by the camera and the lidar. For example, the target area may be an area within 10 meters with the positions of the camera and the lidar as the origin and in the direction of the camera and the lidar. In a specific application scenario, the target area may be an intersection area. Of course, the target area is not limited to the intersection area, and may also be an area on a conventional road.

[0106] In the actual application process, the camera and the lidar may be deployed on a traffic signal pole at an intersection or on a street lamp pole. In addition, in the present application, the device for capturing the target image information includes, but is not limited to, a camera, and may also be other visual detection devices. The device for collecting the target perception information includes, but is not limited to, a lidar, and may also be other devices that can obtain perception information.

[0107] In a specific embodiment of the present application, the target perception information may also be the perception information collected by the lidar and obtained by performing contour processing on the point cloud information collected by the lidar.

[0108] Specifically, the above-mentioned violation actions include, but are not limited to: a vehicle running a red light, a vehicle going in the wrong direction, a vehicle speeding, and a pedestrian running a red light.

[0109] A first determination unit 20, configured to determine whether there is occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information, and in the case of occlusion, draw a radar view screen and a three-dimensional view screen of the target area at the target detection moment based on the target perception information;

[0110] As Figure 3 shown, the radar view screen is a screen of the target area at the target detection moment obtained by performing contour processing on the point cloud information collected by the lidar.

[0111] A first sending unit 30 is configured to send the image view screen, the radar view screen, and the three-dimensional view screen to the display screen of the cloud platform, so that an administrator can re-check for any violation actions based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen. The image view screen is a screen composed of the above-mentioned target image information.

[0112] The image view screen in the first sending unit is a screen composed of target image information. That is to say, the image view screen is a screen corresponding to the target image information of the target area at the target detection moment.

[0113] In this embodiment, when the road test controller detects that there is a violation action of the target object in the target area at the target detection moment, it sends the target image information of the target area at the target detection moment captured by the camera and the target perception information of the target area at the target detection time collected by the lidar to the cloud platform. The first receiving unit is configured to receive the target image information and the target perception information sent by the road test controller; the first determining unit is configured to determine whether there is an occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information. In the case of an occlusion, based on the target perception information, a radar view screen and a three-dimensional view screen of the target area at the target detection moment are drawn; the first sending unit is configured to send the image view screen, the radar view screen, and the three-dimensional view screen to the display screen. In this way, the administrator can re-check the violation actions of the target object based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen displayed on the display screen. The cloud platform of this solution takes into account the occlusion situation, and determines whether there is an occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information. In the case of an occlusion, a radar view screen and a three-dimensional view screen of the target area at the target detection moment are drawn, so that it is convenient for the administrator to quickly obtain the specific situation of the target area at the target detection moment, ensuring that it can be more accurately determined whether the target object has committed a violation action, avoiding false alarms and missed detections, and thus solving the problem of low accuracy in detecting violation actions in traffic due to occlusion in the prior art.

[0114] To ensure that the computational load of the cloud platform is small and to determine whether there is occlusion in the target area at the target detection moment more simply, in the specific implementation process, the above-mentioned first determination unit includes a first determination module and a second determination module. Among them, the above-mentioned first determination module is used to determine the position information of the target object in the world coordinate system based on the above-mentioned target perception information, and determine whether there is occlusion in the target area at the target detection moment based on the position information of the lidar in the world coordinate system and the position information of the target object; the above-mentioned second determination module is used to perform target detection on the above-mentioned target image information to obtain a plurality of target bounding boxes, and determine whether there is occlusion in the target area at the target detection moment based on the plurality of above-mentioned target bounding boxes. The above-mentioned target bounding box is the bounding box of the target object in the above-mentioned target image information, and the above-mentioned target object includes the above-mentioned target object and other objects. The above-mentioned other objects include at least one of the following: buildings, trees, vehicles other than the above-mentioned target object, and pedestrians other than the above-mentioned target object.

[0115] In the above-mentioned embodiment, based on the target perception information, determining the position information of the target object (i.e., the vehicle or pedestrian with a violation action) in the world coordinate system is to determine the position information of the target object in the three-dimensional world. In addition, since the position information of the lidar in the three-dimensional world is known when the lidar is deployed, a straight line segment between the lidar and the target object can be constructed relatively simply. Of course, in the actual application process, when constructing the straight line segment between the lidar and the target object, the center point of the target object in the three-dimensional world can also be determined first, and then the straight line segment between the position information of the location where the lidar is located and the center point of the target object can be constructed.

[0116] In the actual application process, any feasible method in the prior art can be used to perform target detection on the target object in the target image information, so as to obtain a plurality of target bounding boxes. Specifically, the obtained target bounding box can be the smallest rectangular box containing the target object.

[0117] Specifically, the above-mentioned vehicle other than the target object can be other vehicles in the target area except for the vehicle that is the target object. The above-mentioned pedestrian other than the target object can be other pedestrians in the target area except for the pedestrian that is the target object.

[0118] In order to more simply determine whether there is occlusion in the target area at the target detection moment, the first determination module of the present application includes a construction sub-module, a first determination sub-module, a second determination sub-module, and a third determination sub-module. Among them, the construction sub-module is used to construct a straight line segment between the position information of the lidar and the position information of the target object based on the position information of the lidar and the position information of the target object; the first determination sub-module is used to determine whether there is any other object passing through the straight line segment; the second determination sub-module is used to determine that there is occlusion in the target area at the target detection moment when there is any other object passing through the straight line segment; the third determination sub-module is used to determine that there is no occlusion in the target area at the target detection moment when there is no other object passing through the straight line segment.

[0119] In some specific embodiments, the second determination module includes a fourth determination sub-module, a fifth determination sub-module, and a sixth determination sub-module. Among them, the fourth determination sub-module is used to determine whether there is an overlap between any two of the target bounding boxes; the fifth determination sub-module is used to determine that there is occlusion in the target area at the target detection moment when there is an overlap between any two of the target bounding boxes; the sixth determination sub-module is used to determine that there is no occlusion in the target area at the target detection moment when there is no overlap between any two of the target bounding boxes. In this embodiment, by determining whether there is an overlap between any two target bounding boxes, it is determined whether there is occlusion in the target area at the target detection moment, so that it is further realized to more simply determine whether there is occlusion in the target area at the target detection moment, and further ensure that the amount of calculation for the cloud platform to determine whether there is occlusion in the target area at the target detection moment is small.

[0120] In some embodiments, the cloud platform of the present application further includes a second sending unit, which is used to send a prompt message to the display screen when it is detected that there is occlusion in the target area at the target detection moment, and the prompt message is used to indicate the existence of occlusion in the target area at the target detection moment. In this solution, when the cloud platform detects that there is occlusion in the target area at the target detection moment, it sends a prompt message to the display screen, so that the administrator can timely know the possibility of false alarms for such illegal actions, and further timely remind the management personnel to recheck the illegal actions based on the radar view screen and the 3D view screen.

[0121] In an embodiment of the present application, the first determination unit further includes a first drawing module and a second drawing module. Among them, the first drawing module is used to draw a radar view screen of the target area at the target detection moment based on the target perception information; the second drawing module is used to perform three-dimensional digital twinning on the radar view screen to obtain the three-dimensional view screen. That is to say, on the basis of the radar view screen, combined with the digital twin of urban buildings and the three-dimensional twin of the target object, the three-dimensional view screen is obtained.

[0122] In the actual application process, in order to ensure that the entire screen of the radar view screen is relatively neat and convenient for the administrator to process efficiently, the contour lines of the target object and the objects within 10 meters nearby are drawn. Specifically, it can be seen Figure 3 as shown.

[0123] In addition, in the above embodiment, the administrator can perform operations such as high-degree-of-freedom rotation, movement, and scaling on the three-dimensional view screen.

[0124] In addition, based on the operation controls displayed on the display screen, the administrator can arbitrarily switch between the image view screen, the radar view screen, and the three-dimensional view screen, which ensures a high degree of operability for the administrator. When the administrator switches to the three-dimensional view screen, the administrator can also choose to display it in the default perspective. Of course, the administrator can also rotate, move, or scale the three-dimensional view screen, etc. Among them, the above-mentioned default perspective can be the direction of the line connecting the position information of the lidar and the target object.

[0125] In a typical embodiment of the present application, as Figure 7 shown, a road test controller is also provided. The road test controller includes:

[0126] A detection unit 40, configured to detect whether there are any illegal actions of the target object in the target area based on the target image information captured by the camera and the target perception information collected by the lidar. The target object includes at least one of the following: vehicles, pedestrians;

[0127] A second determination unit 50, configured to determine the moment when the target object has an illegal action as the target detection moment when there is an illegal action of the target object in the target area;

[0128] A third sending unit 60, configured to send the target image information and the target perception information corresponding to the above-mentioned target detection moment to a cloud platform, so that the cloud platform determines whether there is an occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information. In the case of an occlusion, based on the target perception information, a radar view screen and a three-dimensional view screen of the target area at the target detection moment are drawn, and the image view screen, the radar view screen, and the three-dimensional view screen are sent to a display screen of the cloud platform, so that an administrator can re-check for violation actions based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen. The image view screen is a screen composed of the target image information.

[0129] In the above-mentioned road test controller, the detection unit is configured to detect whether there is a violation action of a target object in a target area based on target image information captured by a camera and target perception information collected by a lidar; the second determination unit is configured to, when there is a violation action of the target object in the target area, determine the moment when the target object has a violation action as the target detection moment; the third sending unit is configured to send the target image information and the target perception information corresponding to the target detection moment to a cloud platform, so that the cloud platform determines whether there is an occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information. In the case of an occlusion, based on the target perception information, a radar view screen and a three-dimensional view screen of the target area at the target detection moment are drawn, and the image view screen, the radar view screen, and the three-dimensional view screen are sent to a display screen of the cloud platform, so that an administrator can re-check for violation actions based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen. The image view screen is a screen composed of the target image information. The road test controller of this solution takes into account the occlusion situation, and determines whether there is an occlusion in the target area at the target detection moment through at least one of the target image information and the target perception information. In the case of an occlusion, a radar view screen and a three-dimensional view screen of the target area at the target detection moment are drawn, so that it is convenient for the administrator to quickly obtain the specific situation of the target area at the target detection moment, ensuring that it can be more accurately determined whether the target object has a violation action, avoiding false alarms and missed detections, and thus solving the problem of low accuracy in detecting violation actions in traffic due to occlusion in the prior art.

[0130] In order to ensure that the computational load of the cloud platform is small and to more simply determine whether there is occlusion in the target area at the target detection moment, in some specific embodiments, the above-mentioned third determination unit includes a first determination module and a second determination module. Among them, the above-mentioned first determination module is used to determine the position information of the target object in the world coordinate system based on the above-mentioned target perception information, and determine whether there is occlusion in the target area at the target detection moment based on the position information of the lidar in the world coordinate system and the position information of the target object; the second determination module is used to perform target detection on the above-mentioned target image information to obtain a plurality of target bounding boxes, and determine whether there is occlusion in the target area at the target detection moment based on the plurality of above-mentioned target bounding boxes. The above-mentioned target bounding box is the bounding box of the target object in the above-mentioned target image information, and the above-mentioned target object includes the above-mentioned target object and other objects. The above-mentioned other objects include at least one of the following: buildings, trees, vehicles other than the above-mentioned target object, and pedestrians other than the above-mentioned target object.

[0131] In order to more simply determine whether there is occlusion in the target area at the target detection moment, in some embodiments, the first determination module includes a construction sub-module, a first determination sub-module, a second determination sub-module, and a third determination sub-module. Among them, the above-mentioned construction sub-module is used to construct a straight line segment between the position information of the lidar and the position information of the target object based on the position information of the lidar and the position information of the target object; the above-mentioned first determination sub-module is used to determine whether there is any of the above-mentioned other objects passing through the straight line segment; the above-mentioned second determination sub-module is used to determine that there is occlusion in the target area at the target detection moment when there is any of the above-mentioned other objects passing through the straight line segment; the above-mentioned third determination sub-module is used to determine that there is no occlusion in the target area at the target detection moment when there is no any of the above-mentioned other objects passing through the straight line segment.

[0132] In the actual application process, the above-mentioned second determination module includes a fourth determination sub-module, a fifth determination sub-module, and a sixth determination sub-module. Among them, the above-mentioned fourth determination sub-module is used to determine whether there is overlap between any two of the above-mentioned target bounding boxes; the above-mentioned fifth determination sub-module is used to determine that there is occlusion in the target area at the target detection moment when there is overlap between any two of the above-mentioned target bounding boxes; the above-mentioned sixth determination sub-module is used to determine that there is no occlusion in the target area at the target detection moment when there is no overlap between any two of the above-mentioned target bounding boxes. In this embodiment, by determining whether there is overlap between any two target bounding boxes, it is determined whether there is occlusion in the target area at the target detection moment, which further realizes a relatively simple determination of whether there is occlusion in the target area at the target detection moment, and further ensures that the computational load of the cloud platform for determining whether there is occlusion in the target area at the target detection moment is small.

[0133] In one embodiment of the present application, when the cloud platform detects that there is an occlusion in the target area at the target detection moment, the cloud platform sends a prompt message to the display screen, and the prompt message is used to indicate the existence of occlusion in the target area at the target detection moment. In this solution, when the cloud platform detects that there is an occlusion in the target area at the target detection moment, it sends a prompt message to the display screen, so that the administrator can timely know the possibility of false alarms for such illegal actions, and further timely remind the management personnel to recheck the illegal actions based on the radar view screen and the 3D view screen.

[0134] In another embodiment of the present application, the third determination unit further includes a first drawing module and a second drawing module. Among them, the first drawing module is used to draw the radar view screen of the target area at the target detection moment based on the target perception information; the second drawing module is used to perform 3D digital twin on the radar view screen to obtain the 3D view screen. That is to say, on the basis of the radar view screen, combining the city building twin and the 3D twin of the target object to obtain the 3D view screen.

[0135] In the actual application process, in order to ensure that the entire radar view screen is relatively neat and convenient for the administrator to process efficiently, the contour lines of the target object and the objects within 10 meters nearby are drawn, as specifically shown in Figure 3 shown.

[0136] In addition, in the above embodiment, the administrator can perform operations such as high-degree-of-freedom rotation, movement, and scaling on the 3D view screen.

[0137] In addition, the administrator can perform arbitrary mutual switching among the image view screen, the radar view screen, and the 3D view screen based on the operation controls displayed on the display screen, which ensures a high operability for the administrator. When the administrator switches to the 3D view screen, the administrator can also choose to display it in the default perspective. Of course, the administrator can also rotate, move, or scale the 3D view screen, etc. Among them, the above-mentioned default perspective can be the direction of the connection line between the position information of the lidar and the target object.

[0138] The cloud platform includes a processor and a memory. The first receiving unit, the first determination unit, the first sending unit, etc. are all stored in the memory as program units, and the processor executes the program units stored in the memory to implement the corresponding functions. The above modules are all located in the same processor; or, the above modules are respectively located in different processors in any combination form.

[0139] The processor contains a kernel, which retrieves the corresponding program units from the memory. One or more kernels can be set, and by adjusting the kernel parameters, the problem of low accuracy in detecting traffic violations caused by occlusion in the prior art can be solved.

[0140] The memory may include non-permanent memory in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. The memory includes at least one memory chip.

[0141] An embodiment of the present invention provides a computer-readable storage medium. The computer-readable storage medium includes a stored program. When the program runs, it controls the device where the computer-readable storage medium is located to execute the above traffic violation detection method.

[0142] Specifically, the traffic violation detection method includes:

[0143] Step S201: Receive the target image information and target perception information of the target area at the target detection moment. The target detection moment is the moment when the roadside controller detects that the target object has a violation action. The target image information is the image information of the target area captured by the camera at the target detection moment. The target perception information is the perception information of the target area collected by the lidar at the target detection moment. The target object includes at least one of the following: vehicle, pedestrian.

[0144] Step S202: Based on at least one of the target image information and the target perception information, determine whether there is occlusion in the target area at the target detection moment. In the case of occlusion, based on the target perception information, draw the radar view screen and the three-dimensional view screen of the target area at the target detection moment.

[0145] Step S203: Send the image view screen, the radar view screen, and the three-dimensional view screen to the display screen of the cloud platform, so that the administrator can conduct a re-inspection of the violation action based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen. The image view screen is the screen composed of the target image information.

[0146] An embodiment of the present invention provides an electronic device, including a memory and a processor. A computer program is stored in the memory, and the processor is configured to execute the above traffic violation detection method through the computer program.

[0147] Specifically, the traffic violation detection method includes:

[0148] Step S201: Receive the target image information and target perception information of the target area at the target detection moment. The target detection moment is the moment when the road test controller detects that the target object has a violation action. The target image information is the image information of the target area captured by the camera at the target detection moment. The target perception information is the perception information of the target area collected by the lidar at the target detection moment. The target object includes at least one of the following: vehicle, pedestrian.

[0149] Step S202: Based on at least one of the target image information and the target perception information, determine whether there is occlusion in the target area at the target detection moment. In the case of occlusion, based on the target perception information, draw the radar view screen and the three-dimensional view screen of the target area at the target detection moment.

[0150] Step S203: Send the image view screen, the radar view screen, and the three-dimensional view screen to the display screen of the cloud platform, so that the administrator can conduct a re-inspection of the violation action based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen. The image view screen is the screen composed of the target image information.

[0151] In a typical embodiment of the present application, a traffic violation detection system is further provided. The system includes a cloud platform and a road test controller. Among them, the cloud platform is used to execute any one of the above traffic violation detection methods; the road test controller communicates with the cloud platform, and the road test controller is used to execute any one of the above traffic violation detection methods.

[0152] The traffic violation detection system of the present application determines whether there is occlusion in the target area at the target detection moment through at least one of the target image information and the target perception information. In the case of occlusion, it draws the radar view screen and the three-dimensional view screen of the target area at the target detection moment, so that it is convenient for the administrator to quickly obtain the specific situation of the target area at the target detection moment, ensuring that it can be more accurately determined whether the target object has a violation action, avoiding false alarms and missed detections, and thus solving the problem of low accuracy in detecting traffic violation actions caused by occlusion in the prior art.

[0153] An embodiment of the present invention provides a device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements at least the following steps:

[0154] Step S201: Receive the target image information and target perception information of the target area at the target detection moment. The target detection moment is the moment when the road test controller detects that the target object has a violation action. The target image information is the image information of the target area captured by the camera at the target detection moment, and the target perception information is the perception information of the target area collected by the lidar at the target detection moment. The target object includes at least one of the following: vehicle, pedestrian;

[0155] Step S202: Based on at least one of the target image information and the target perception information, determine whether there is occlusion in the target area at the target detection moment. In the case of occlusion, based on the target perception information, draw the radar view screen and the three-dimensional view screen of the target area at the target detection moment;

[0156] Step S203: Send the image view screen, the radar view screen, and the three-dimensional view screen to the display screen of the cloud platform, so that the administrator can conduct a re-inspection of the violation action based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen. The image view screen is the screen composed of the target image information.

[0157] The device in this article can be a server, a PC, a PAD, a mobile phone, etc.

[0158] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program initialized with at least the following method steps:

[0159] Step S201: Receive the target image information and target perception information of the target area at the target detection moment. The target detection moment is the moment when the road test controller detects that the target object has a violation action. The target image information is the image information of the target area captured by the camera at the target detection moment, and the target perception information is the perception information of the target area collected by the lidar at the target detection moment. The target object includes at least one of the following: vehicle, pedestrian;

[0160] Step S202: Based on at least one of the target image information and the target perception information, determine whether there is occlusion in the target area at the target detection moment. In the case of occlusion, based on the target perception information, draw the radar view screen and the three-dimensional view screen of the target area at the target detection moment;

[0161] Step S203: Send the image view screen, the above-mentioned radar view screen, and the above-mentioned 3D view screen to the display screen of the above-mentioned cloud platform, so that the administrator can conduct a re-inspection of the illegal actions based on at least one of the above-mentioned image view screen, the above-mentioned radar view screen, and the above-mentioned 3D view screen. The above-mentioned image view screen is a screen composed of the above-mentioned target image information.

[0162] Obviously, those skilled in the art should understand that the various modules or steps of the present invention described above can be implemented by a general-purpose computing device. They can be concentrated on a single computing device or distributed over a network composed of multiple computing devices. They can be implemented by program codes executable by the computing device. Thus, they can be stored in a storage device and executed by the computing device. And in some cases, the steps shown or described here can be executed in a different order, or they can be separately fabricated into individual integrated circuit modules, or multiple modules or steps among them can be fabricated into a single integrated circuit module to be implemented. In this way, the present invention is not limited to any specific combination of hardware and software.

[0163] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0164] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0165] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured product including an instruction device, and the instruction device realizes the functions in the flow Figure 1 one flow or multiple flows and / or blocks Figure 1the functions specified in one or more boxes.

[0166] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide for implementing the steps for the functions specified in one Figure 1 one process or more processes and / or boxes Figure 1 or more boxes.

[0167] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0168] The memory may include non-permanent memory in the computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

[0169] Computer-readable media includes permanent and non-permanent, removable and non-removable media and can store information by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0170] It should also be noted that the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

[0171] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0172] 1), in the detection method of the present application, first, when the road test controller detects that the target object in the target area has a violation action at the target detection moment, it sends the target image information of the target area at the target detection moment captured by the camera and the target perception information of the target area at the target detection time collected by the lidar to the cloud platform, and the cloud platform receives the target image information and the target perception information sent by the road test controller; then, the cloud platform determines whether there is occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information. In the case of occlusion, based on the target perception information, it draws the radar view screen and the three-dimensional view screen of the target area at the target detection moment; finally, the cloud platform sends the image view screen, the radar view screen and the three-dimensional view screen to the display screen, so that the administrator can re-check the violation action of the target object based on at least one of the image view screen, the radar view screen and the three-dimensional view screen displayed on the display screen. The detection method of this solution considers the occlusion situation, and determines whether there is occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information. In the case of occlusion, it draws the radar view screen and the three-dimensional view screen of the target area at the target detection moment, so as to facilitate the administrator to quickly obtain the specific situation of the target area at the target detection moment, ensure that it can be more accurately determined whether the target object has a violation action, avoid false alarms and missed detections, and thus solve the problem of low accuracy of detecting violation actions in traffic due to occlusion in the prior art.

[0173] 2) In the cloud platform of the present application, the first receiving unit is used to receive the target image information and the target perception information sent by the road test controller; the first determining unit is used to determine whether there is an occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information. In the case of an occlusion, based on the target perception information, a radar view screen and a three-dimensional view screen of the target area at the target detection moment are drawn; the first sending unit is used to send the image view screen, the radar view screen, and the three-dimensional view screen to the display screen, so that the administrator can re-check the illegal actions of the target object based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen displayed on the display screen. The cloud platform of this solution takes into account the occlusion situation, and determines whether there is an occlusion in the target area at the target detection moment through at least one of the target image information and the target perception information. In the case of an occlusion, a radar view screen and a three-dimensional view screen of the target area at the target detection moment are drawn, so that it is convenient for the administrator to quickly obtain the specific situation of the target area at the target detection moment, ensuring that it can be more accurately determined whether the target object has performed an illegal action, avoiding false alarms and missed detections, and thus solving the problem of low accuracy in detecting illegal actions in traffic caused by occlusion in the prior art.

[0174] 3) The traffic violation detection system of the present application takes into account the occlusion situation, and determines whether there is an occlusion in the target area at the target detection moment through at least one of the target image information and the target perception information. In the case of an occlusion, a radar view screen and a three-dimensional view screen of the target area at the target detection moment are drawn, so that it is convenient for the administrator to quickly obtain the specific situation of the target area at the target detection moment, ensuring that it can be more accurately determined whether the target object has performed an illegal action, avoiding false alarms and missed detections, and thus solving the problem of low accuracy in detecting illegal actions in traffic caused by occlusion in the prior art.

[0175] The above are only the preferred embodiments of the present application and are not used to limit the present application. For those skilled in the art, the present application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for detecting traffic violations, characterized in that, the detection method is applied to a cloud platform, and the detection method includes: receiving target image information and target perception information of a target area at a target detection time, where the target detection time is the time when a roadside controller detects that a target object has a violation action, the target image information is image information of the target area captured by a camera at the target detection time, the target perception information is perception information of the target area collected by a lidar at the target detection time, and the target object includes at least one of the following: a vehicle, a pedestrian; based on at least one of the target image information and the target perception information, determining whether there is occlusion in the target area at the target detection time, and in the case of occlusion, based on the target perception information, drawing a radar view screen and a three-dimensional view screen of the target area at the target detection time; sending the image view screen, the radar view screen, and the three-dimensional view screen to a display screen of the cloud platform, so that an administrator can recheck the violation action based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen, and the image view screen is a screen composed of the target image information.

2. The detection method according to claim 1, characterized in that, determining whether there is occlusion in the target area at the target detection time based on at least one of the target image information and the target perception information includes at least one of the following: determining position information of the target object in a world coordinate system based on the target perception information, and determining whether there is occlusion in the target area at the target detection time based on the position information of the lidar and the position information of the target object in the world coordinate system; performing target detection on the target image information to obtain a plurality of target bounding boxes, and determining whether there is occlusion in the target area at the target detection time based on the plurality of target bounding boxes, where the target bounding box is a bounding box of a target object in the target image information, and the target object includes the target object and other objects, and the other objects include at least one of the following: a building, a tree, a vehicle other than the target object, a pedestrian other than the target object.

3. The detection method according to claim 2, characterized in that, determining whether there is occlusion in the target area at the target detection time based on the position information of the lidar and the position information of the target object in the world coordinate system includes: constructing a straight line segment between the position information of the lidar and the position information of the target object based on the position information of the lidar and the position information of the target object; determining whether there is any of the other objects passing through the straight line segment; in the case of any of the other objects passing through the straight line segment, determining that there is occlusion in the target area at the target detection time; In the case where no other object passes through the straight line segment, it is determined that there is no occlusion in the target area at the target detection moment.

4. The detection method according to claim 2, wherein, determining whether there is occlusion in the target area at the target detection moment based on a plurality of the target bounding boxes includes: determining whether there is an overlap between any two of the target bounding boxes; in the case where there is an overlap between any two of the target bounding boxes, determining that there is occlusion in the target area at the target detection moment; in the case where there is no overlap between any two of the target bounding boxes, determining that there is no occlusion in the target area at the target detection moment.

5. The detection method according to any one of claims 1 to 4, wherein, the detection method further includes: in the case where it is detected that there is occlusion in the target area at the target detection moment, sending a prompt message to the display screen, and the prompt message is used to indicate the existence of occlusion in the target area at the target detection moment.

6. The detection method according to any one of claims 1 to 4, wherein, drawing a radar view screen and a three-dimensional view screen of the target area at the target detection moment based on the target perception information, including: drawing a radar view screen of the target area at the target detection moment based on the target perception information; performing three-dimensional digital twin on the radar view screen to obtain the three-dimensional view screen.

7. A detection method for traffic violations, wherein, the detection method is applied to a roadside controller, and the detection method includes: detecting whether a target object in a target area has a violation action based on target image information captured by a camera and target perception information collected by a lidar, and the target object includes at least one of the following: a vehicle, a pedestrian; in the case where the target object in the target area has a violation action, determining the moment when the target object has the violation action as the target detection moment; sending the target image information and the target perception information corresponding to the target detection moment to a cloud platform, so that the cloud platform determines whether there is occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information, and in the case of occlusion, drawing a radar view screen and a three-dimensional view screen of the target area at the target detection moment based on the target perception information, and sending an image view screen, the radar view screen, and the three-dimensional view screen to a display screen of the cloud platform, so that an administrator can perform a re-inspection of the violation action based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen, and the image view screen is a screen composed of the target image information.

8. The detection method according to claim 7, wherein, the process by which the cloud platform determines whether there is occlusion in the target area at the target detection moment based on at least one of the target image information and the target perception information includes at least one of the following: Based on the target perception information, determine the position information of the target object in the world coordinate system. Based on the position information of the lidar in the world coordinate system and the position information of the target object, determine whether there is an occlusion in the target area at the target detection moment. Perform target detection on the target image information to obtain multiple target bounding boxes. Based on the multiple target bounding boxes, determine whether there is an occlusion in the target area at the target detection moment. The target bounding box is the bounding box of the target object in the target image information, and the target object includes the target object and other objects. The other objects include at least one of the following: buildings, trees, vehicles other than the target object, and pedestrians other than the target object.

9. The detection method according to claim 8, characterized in that, The process by which the cloud platform determines whether there is an occlusion in the target area at the target detection moment based on the position information of the lidar in the world coordinate system and the position information of the target object includes: Based on the position information of the lidar and the position information of the target object, construct a straight line segment between the position information of the lidar and the position information of the target object. Determine whether there is any of the other objects passing through the straight line segment. In the case where there is any of the other objects passing through the straight line segment, determine that there is an occlusion in the target area at the target detection moment. In the case where there is no other object passing through the straight line segment, determine that there is no occlusion in the target area at the target detection moment.

10. The detection method according to claim 8, characterized in that, The process by which the cloud platform determines whether there is an occlusion in the target area at the target detection moment based on the multiple target bounding boxes includes: Determine whether there is an overlap between any two of the target bounding boxes. In the case where there is an overlap between any two of the target bounding boxes, determine that there is an occlusion in the target area at the target detection moment. In the case where there is no overlap between any two of the target bounding boxes, determine that there is no occlusion in the target area at the target detection moment.

11. The detection method according to any one of claims 6 to 10, characterized in that, In the case where the cloud platform detects that there is an occlusion in the target area at the target detection moment, the cloud platform sends a prompt message to the display screen, and the prompt message is used to indicate the existence of the occlusion in the target area at the target detection moment.

12. The detection method according to any one of claims 6 to 10, characterized in that, The process by which the cloud platform draws the radar view screen and the 3D view screen of the target area at the target detection moment based on the target perception information includes: Based on the target perception information, draw the radar view screen of the target area at the target detection moment. Perform 3D digital twin on the radar view screen to obtain the 3D view screen.

13. A cloud platform, characterized in that, including: A first receiving unit, configured to receive target image information and target perception information of a target area at a target detection time, where the target detection time is the time when a road test controller detects that a target object has a violation action, the target image information is image information of the target area captured by a camera at the target detection time, the target perception information is perception information of the target area collected by a lidar at the target detection time, and the target object includes at least one of the following: a vehicle, a pedestrian; A first determining unit, configured to determine whether there is occlusion in the target area at the target detection time based on at least one of the target image information and the target perception information. In the case of occlusion, a radar view screen and a three-dimensional view screen of the target area at the target detection time are drawn based on the target perception information; A first sending unit, configured to send an image view screen, the radar view screen, and the three-dimensional view screen to a display screen of the cloud platform, so that an administrator can re-check the violation action based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen, where the image view screen is a screen composed of the target image information.

14. A road test controller Characterized in that It includes: A detection unit, configured to detect whether a target object in a target area has a violation action based on target image information captured by a camera and target perception information collected by a lidar, where the target object includes at least one of the following: a vehicle, a pedestrian; A second determining unit, configured to, when the target object in the target area has a violation action, determine the time when the target object has the violation action as the target detection time; A third sending unit, configured to send the target image information and the target perception information corresponding to the target detection time to a cloud platform, so that the cloud platform determines whether there is occlusion in the target area at the target detection time based on at least one of the target image information and the target perception information. In the case of occlusion, a radar view screen and a three-dimensional view screen of the target area at the target detection time are drawn based on the target perception information, and an image view screen, the radar view screen, and the three-dimensional view screen are sent to the display screen of the cloud platform, so that an administrator can re-check the violation action based on at least one of the image view screen, the radar view screen, and the three-dimensional view screen, where the image view screen is a screen composed of the target image information.

15. A traffic violation detection system Characterized in that It includes: A cloud platform, where the cloud platform is configured to execute the traffic violation detection method according to any one of claims 1 to 6; A road test controller, communicating with the cloud platform, where the road test controller is configured to execute the traffic violation detection method according to any one of claims 7 to 12.

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