A processing method and device for extracting roadside visual information of a target vehicle

Abstract

This invention relates to a method and apparatus for extracting roadside visual information of a target vehicle. The method includes: receiving roadside visual / perception data from traffic intersections and storing it in an image / perception database; receiving vehicle travel data of the target vehicle and storing it in a travel database; and creating an intersection visual information database for the target vehicle. The method also includes: extracting historical driving trajectories from the travel database using an asynchronous processing mechanism; identifying the intersection information passed through each trajectory; refining each trajectory by combining the intersection information and the perception database; batch extracting roadside visual information for each trajectory based on the image database; and refreshing the intersection visual information database based on the extraction results. Upon receiving a target time period input by the user, the method summarizes all roadside visual information of the target vehicle during the target time period based on the intersection visual information database to generate summary data, which is then fed back to the current user. This invention can improve the efficiency of roadside visual information acquisition and reduce acquisition costs.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a processing method and apparatus for extracting roadside visual information of a target vehicle. Background Technology

[0002] In the development of autonomous driving algorithms / models, a large amount of roadside visual information needs to be collected for training and testing. This roadside visual information includes image sequences captured of vehicles in real traffic environments and videos of vehicles driving in real traffic environments. Currently, most conventional methods of visual information acquisition are accomplished through data collection vehicles. These vehicles collect road videos using onboard perception devices and extract visual information from the videos using onboard perception algorithms and computing resources. However, through practice, we have found significant drawbacks to this conventional approach: 1) Limited by the number of vehicles available, it is difficult to acquire a large amount of visual information in a short period; 2) The high customization cost of these vehicles leads to persistently high data acquisition costs.

[0003] With the maturity and development of intelligent transportation systems, electronic traffic enforcement cameras, checkpoint cameras, and roadside computing units have been installed at many road intersections. Electronic traffic enforcement cameras are used to capture images of vehicles and recognize license plates at intersections. The capture process generates a sequence of vehicle images (typically consisting of three images), each clearly displaying information such as traffic lights, lane / stop lines, license plates, vehicle color, and vehicle type. Checkpoint cameras are used for real-time, 24 / 7 video recording of intersection traffic conditions. Roadside computing units are used to detect the target types of traffic participants at intersections and track and analyze the movement trajectories of each participant based on perception data (such as vehicle image sequences, real-time traffic video, and real-time radar point clouds) from intersection sensing devices (such as electronic traffic enforcement cameras, checkpoint cameras, and LiDAR). Electronic traffic enforcement cameras and checkpoint cameras are generally installed in pairs and can communicate with the roadside computing unit. During installation, the checkpoint camera faces outwards from the intersection to capture video of vehicles entering the intersection, while the electronic traffic enforcement camera faces inwards to capture image sequences of vehicles entering the intersection.

[0004] If the data resources of traffic enforcement cameras / checkpoints and roadside computing units can be further developed, a large amount of roadside visual information can be rapidly accumulated in a short period of time without incurring high data collection costs. To achieve this goal, we propose the following solution: Recruit a group of vehicles as target vehicles, and install a vehicle trip data collection terminal for each target vehicle owner via a mobile client or mini-program. During the journey of each target vehicle, the corresponding information collection terminal continuously acquires the current vehicle's trip data. Simultaneously, data resources from traffic enforcement cameras / checkpoints and roadside computing units at all intersections are continuously acquired. By analyzing the trip trajectory of each target vehicle, the intersection information along the trajectory can be obtained. Given the intersection information, the traffic enforcement camera information along the trajectory can be obtained from the roadside computing unit's data resources. Furthermore, given the camera information, a series of roadside visual information about the current target vehicle can be obtained from the traffic enforcement camera data resources. The core of this solution lies in how to analyze the target vehicle's travel trajectory, how to obtain information from passing cameras based on the travel trajectory, and how to obtain roadside visual information based on the information from passing cameras. This is the technical problem that this invention aims to solve. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by providing a method, apparatus, electronic device, and computer-readable storage medium for extracting roadside visual information of target vehicles. This invention continuously receives roadside visual data from all traffic intersections and stores it in an image database; continuously receives roadside perception data from all traffic intersections and stores it in a perception database; and continuously receives vehicle travel data of the target vehicle and stores it in a corresponding travel database, creating a corresponding intersection visual information database for the target vehicle. It then continuously extracts the historical driving trajectory of the target vehicle from the travel database using an asynchronous processing mechanism, identifies the intersection information passed through each trajectory, refines each trajectory by combining the intersection information and the perception database, and batch extracts the roadside visual information of each refined trajectory based on the image database, refreshing the intersection visual information database based on the extraction results. Upon receiving a target time period input by the user, it summarizes all roadside visual information of the target vehicle during the target time period based on the intersection visual information database, generating corresponding summary data and feeding it back to the current user. This invention provides an automated data production line for roadside visual information of target vehicles, enabling the automatic generation of such information. It also provides a time-based information query mechanism, allowing the acquisition of roadside visual information for target vehicles at any given time. This invention helps improve the efficiency of roadside visual information acquisition and reduces the data acquisition cost.

[0006] To achieve the above objectives, a first aspect of the present invention provides a processing method for extracting roadside visual information of a target vehicle, the method comprising:

[0007] The first processing unit receives roadside visual data from all traffic intersections and stores it in the image database; it also receives roadside perception data from all traffic intersections and stores it in the perception database; it receives vehicle travel data of the target vehicle and stores it in the corresponding travel database; and it creates a corresponding intersection visual information database for the target vehicle.

[0008] The first processing terminal extracts historical driving trajectories from the trip database according to the asynchronous processing mechanism, identifies the intersection information passed by each trajectory, improves each trajectory by combining the intersection information and the perception database, and extracts roadside visual information of each trajectory in batches based on the image database and refreshes the intersection visual information database based on the extraction results.

[0009] When the first processing terminal receives the target time period input by the user, it summarizes all roadside visual information of the target vehicle in the target time period according to the intersection visual information database, generates corresponding first summary data, and feeds it back to the current user.

[0010] Preferably, at least one set of electronic police cameras and checkpoint cameras are installed at each entrance of each traffic intersection; the viewing direction of the electronic police cameras is facing the inside of the current intersection, and the viewing direction of the checkpoint cameras is facing the outside of the current intersection; at least one roadside computing unit is configured at each traffic intersection.

[0011] The electronic police camera is used to continuously capture vehicle license plates, and the image sequence captured each time, along with its corresponding intersection sign, camera sign, and camera type, forms a corresponding roadside visual data which is sent to the first processing terminal.

[0012] The checkpoint camera is used to capture real-time video of the current traffic conditions at the intersection around the clock, and sends a corresponding roadside visual data consisting of the video data of the most recent specified duration and its corresponding intersection sign, camera sign, and camera type to the first processing terminal.

[0013] The roadside computing unit is used to detect the target type of each traffic participant at the current intersection, track and analyze the movement trajectory of each traffic participant, and send the corresponding roadside sensing data, which is composed of the sensing target set and intersection signage within the most recent specified time period, to the first processing terminal.

[0014] The target vehicle continuously records its own driving trajectory during its driving process and periodically sends a latest segment of its driving trajectory to the first processing terminal; the target vehicle is a car, truck, bus, two-wheeled motor vehicle, or three-wheeled motor vehicle.

[0015] Preferably, the image database includes multiple first image records; the first image record includes a first intersection sign, a first camera sign, a first camera type, a first image time period, and first image data; the first camera type includes electronic police cameras and checkpoint cameras; when the first camera type is an electronic police camera, the first image data is an image sequence; when the first camera type is a checkpoint camera, the first image data is a video data.

[0016] The perception database includes multiple first perception records; each first perception record includes a second intersection sign, a first perception time period, and a first perception target set; the first perception target set includes multiple first perception targets; each first perception target includes a first target identifier, a first target type, and a first target trajectory; the first target type includes pedestrians, animals, bicycles, cars, trucks, buses, two-wheeled motor vehicles, and three-wheeled motor vehicles; the first target trajectory includes multiple first trajectory points; each first trajectory point includes a first timestamp and a first coordinate.

[0017] The trip database includes multiple first trip records; each first trip record includes a first trip time period, a first trip trajectory, and a first processing status; the first trip trajectory includes multiple second trajectory points; each second trajectory point includes a second timestamp and a second coordinate; the first processing status includes unprocessed and processed.

[0018] The intersection visual information database includes multiple first visual records; the first visual records include a third intersection sign, a second camera sign, a second camera type, a second image time period, and second image data; the second camera type includes electronic police cameras and checkpoint cameras; when the second camera type is an electronic police camera, the second image data is an image sequence; when the second camera type is a checkpoint camera, the second image data is a video data.

[0019] Preferably, the step of receiving and storing the roadside visual data of all traffic intersections into the image database specifically includes:

[0020] Each time the first processing terminal receives roadside visual data from a traffic intersection camera, it extracts the corresponding intersection sign, camera sign, camera type, and visual data from the current roadside visual data to form the corresponding first intersection sign, first camera sign, first camera type, and first image data. It then identifies the current first camera type. If the first camera type is a traffic enforcement camera, the time interval consisting of the earliest and latest image times of the first image data is used as the corresponding first image time interval. If the first camera type is a checkpoint camera, the time interval consisting of the start and end times of the first image data is used as the corresponding first image time interval. Finally, the first intersection sign, first camera sign, first camera type, first image time interval, and first image data obtained in this processing step are combined to form a corresponding first image record, which is added to the image database.

[0021] Preferably, the step of receiving and storing the roadside sensing data from all traffic intersections into the sensing database specifically includes:

[0022] When the first processing terminal receives the roadside perception data sent by the roadside computing unit of a traffic intersection, it extracts the corresponding intersection identifier and perception target set from the current roadside visual data as the corresponding second intersection identifier and first perception target set; and takes the time period composed of the earliest and latest timestamps of the current first perception target set as the corresponding first perception time period; and adds a corresponding first perception record composed of the second intersection identifier, the first perception time period and the first perception target set obtained this time to the perception database.

[0023] Preferably, the receipt of the target vehicle's trip data and its storage in the corresponding trip database specifically includes:

[0024] Each time the first processing terminal receives a segment of the vehicle's driving trajectory sent by the target vehicle, it takes the current trajectory as the corresponding first trip trajectory; takes the time period composed of the earliest and latest timestamps of the current first trip trajectory as the corresponding first trip time period; sets a corresponding first processing status to unprocessed; and adds a corresponding first trip record composed of the first trip time period, the first trip trajectory, and the first processing status to the trip database.

[0025] Preferably, the asynchronous processing mechanism extracts historical driving trajectories from the trip database, identifies the intersection information passed through each trajectory, refines each trajectory by combining the intersection information and the perception database, and batch extracts roadside visual information for each trajectory based on the image database, and refreshes the intersection visual information database based on the extraction results. Specifically, this includes:

[0026] The first processing unit records all first trip records in the trip database whose first processing status is "unprocessed" as unprocessed records; when the total number of unprocessed records is not 0, it takes the earliest added unprocessed record as the corresponding current trip record; it extracts the first trip trajectory of the current trip record as the corresponding current trip trajectory; it uses a preset first high-precision map to identify the traffic intersection information passed by the current trip trajectory to obtain the corresponding list of intersections passed; when the list of intersections passed is not empty, it first performs trajectory fusion based on the list of intersections passed, the perception database, and the current trip trajectory to obtain the corresponding current fused trajectory; then, it performs batch roadside visual information extraction and visual information database refresh processing based on the current fused trajectory, the list of intersections passed, the preset list of intersection cameras, and the image database; and it resets the first processing status of the current trip record to "processed".

[0027] in,

[0028] When the list of passing intersections is not empty, it consists of one or more passing intersection records; the passing intersection records include traffic intersection signs and the time period of passing through the intersection;

[0029] The intersection camera list includes multiple first intersection records; each first intersection record corresponds one-to-one with a traffic intersection; each first intersection record includes a fourth intersection sign and a first intersection camera set; each first intersection camera set includes multiple first intersection cameras; each first intersection camera includes a third camera sign, a third camera type, first installation position coordinates, a first installation height, and a first installation angle; the third camera type includes electronic police cameras and checkpoint cameras; the first installation position coordinates are the ground projection point coordinates of the current camera position, the first installation height is the height of the current camera position perpendicular to the ground, and the first installation angle is the angle between the current camera axis and the vertical line to the ground.

[0030] Furthermore, the step of using a preset first high-precision map to identify the traffic intersections along the current travel trajectory to obtain a corresponding list of intersections specifically includes:

[0031] The first processing terminal obtains the traffic intersection identifiers and traffic intersection areas of each traffic intersection traversed by the current travel trajectory by querying the first high-precision map; identifies the trajectory time periods of the current travel trajectory in each traffic intersection area and uses the identification results as the corresponding traffic intersection traversal time periods; and forms a corresponding traffic intersection traversal record by combining the traffic intersection identifiers and traffic intersection traversal time periods of each traversed intersection; and forms a corresponding traffic intersection traversal list by combining all the obtained traffic intersection traversal records.

[0032] Furthermore, the step of fusing the current trajectory based on the list of intersections passed through, the perception database, and the current travel trajectory to obtain the corresponding current fused trajectory specifically includes:

[0033] The first processing unit performs a round of traversal on all the traversal intersection records in the traversal intersection list; and during this round of traversal, the currently traversed traversal intersection record is taken as the corresponding current intersection record; and the traffic intersection identifier and the intersection passage time of the current intersection record are taken as the corresponding current identifier and current time period; and the first perception record in the perception database where the second intersection identifier matches the current identifier and the first perception time period intersects with the current time period is recorded as the second perception record; and the first perception target set of all second perception records is merged to obtain a merged target set; and in the merged target set, the first perception targets whose first target type does not match the vehicle type of the target vehicle are deleted, and the first perception targets whose trajectory duration is lower than the preset minimum trajectory duration are deleted; and the first perception target whose target deletion is completed is then deleted. In the merged target set, duplicate first-perceived targets whose first target trajectories overlap are deduplicated; the remaining first target trajectories in the merged target set are taken as the corresponding current target trajectories, and the intersection of the trajectory time periods of the current target trajectories and the current travel trajectory is taken as the current intersection time period. Multiple sampling points are obtained by sampling the current intersection time period at equal intervals, and the shortest trajectory distance between the current target trajectory and the current travel trajectory at each sampling point is calculated. The average distance of all shortest trajectory distances corresponding to the current intersection time period is calculated. The first target trajectory corresponding to the smallest average distance is taken as the current intersection trajectory. The current travel trajectory and the current intersection trajectory are fused, and the fusion result is taken as the new current travel trajectory. At the end of this round of traversal, the latest current travel trajectory is taken as the corresponding current fused trajectory.

[0034] Furthermore, the step of performing batch roadside visual information extraction and visual information database refresh based on the current fused trajectory, the list of intersections passed through, the preset list of intersection cameras, and the image database specifically includes:

[0035] The first processing end identifies the trajectory passing order of all intersection cameras passed by the current fused trajectory according to the list of passing intersections and the list of intersection cameras, and sorts all the passing intersection cameras according to the identification results to obtain the corresponding first intersection camera sequence; the first intersection camera sequence is formed by sequentially sorting multiple first intersection cameras;

[0036] The system iterates through all the cameras in the first intersection camera sequence. During this iteration, the currently iterated first intersection camera is designated as the current camera. The third camera identifier and third camera type of the current camera are used as the corresponding current identifier and current type. The current type is then identified. If the current type is a traffic enforcement camera, the coordinates of the intersection of the current camera's axis and the ground are calculated based on the first installation position coordinates, the first installation height, and the first installation angle, and the calculation result is used as the corresponding current coordinates. If the current type is a checkpoint camera, the first installation position coordinates of the current camera are used as the corresponding current coordinates. The timestamp of the trajectory point whose trajectory coordinates are closest to the current coordinates on the current fusion trajectory is used as the corresponding current time. The first image record in the image database where the first camera identifier matches the current identifier and the first image time period intersects with the current time is used as a corresponding first extraction record.

[0037] At the end of this round of traversal, each of the first extracted records is taken as a corresponding first visual record; and all the first visual records obtained in this round are added to the intersection visual information database.

[0038] Preferably, the step of summarizing all roadside visual information of the target vehicle during the target time period based on the intersection visual information database to generate corresponding first summary data and feeding it back to the current user specifically includes:

[0039] The first processing unit extracts all the first visual records that meet the target time period from the intersection visual information database and sorts them in chronological order to form a corresponding first record sequence; and feeds back the first record sequence as the corresponding first summary data to the current user.

[0040] A second aspect of the present invention provides an apparatus for implementing the processing method for extracting roadside visual information of a target vehicle as described in the first aspect above. The apparatus includes: a data receiving module, a visual information production module, and a visual information query module.

[0041] The data receiving module is used to receive roadside visual data from all traffic intersections and store it in the image database; and to receive roadside perception data from all traffic intersections and store it in the perception database; and to receive vehicle travel data of the target vehicle and store it in the corresponding travel database; and to create a corresponding intersection visual information database for the target vehicle.

[0042] The visual information production module is used to extract historical driving trajectories from the trip database according to the asynchronous processing mechanism, identify the intersection information passed by each trajectory, improve each trajectory by combining the intersection information and the perception database, extract roadside visual information of each trajectory in batches based on the image database, and refresh the intersection visual information database based on the extraction results.

[0043] The visual information query module is used to, upon receiving a target time period input by the user, summarize all roadside visual information of the target vehicle during the target time period based on the intersection visual information database, generate corresponding first summary data, and feed it back to the current user.

[0044] A third aspect of the present invention provides an electronic device, including: a memory, a processor, and a transceiver;

[0045] The processor is used to couple with the memory, read and execute instructions in the memory to implement the steps of the method described in the first aspect above;

[0046] The transceiver is coupled to the processor, and the processor controls the transceiver to send and receive messages.

[0047] A fourth aspect of the present invention provides a computer-readable storage medium storing computer instructions that, when executed by a computer, cause the computer to perform the instructions described in the first aspect.

[0048] This invention provides a method, apparatus, electronic device, and computer-readable storage medium for extracting roadside visual information of a target vehicle. As described above, this invention continuously receives roadside visual data from all traffic intersections and stores it in an image database; continuously receives roadside perception data from all traffic intersections and stores it in a perception database; continuously receives vehicle travel data of the target vehicle and stores it in a corresponding travel database; and creates a corresponding intersection visual information database for the target vehicle. It also continuously extracts the historical driving trajectory of the target vehicle from the travel database using an asynchronous processing mechanism, identifies the intersection information passed through each trajectory, refines each trajectory by combining the intersection information and the perception database, and batch extracts the roadside visual information of each refined trajectory based on the image database, refreshing the intersection visual information database based on the extraction results. Upon receiving a target time period input by the user, it summarizes all roadside visual information of the target vehicle during the target time period based on the intersection visual information database, generates corresponding summary data, and feeds it back to the current user. This invention provides an automated data production line for roadside visual information of target vehicles, enabling the automatic generation of such information. It also provides a time-based information query mechanism, allowing the acquisition of roadside visual information for target vehicles at any given time. This invention improves the efficiency of roadside visual information acquisition and reduces the data acquisition cost. Attached Figure Description

[0049] Figure 1 This is a schematic diagram of a processing method for extracting roadside visual information of a target vehicle according to Embodiment 1 of the present invention;

[0050] Figure 2 This is a module structure diagram of a processing device for extracting roadside visual information of a target vehicle provided in Embodiment 2 of the present invention;

[0051] Figure 3 This is a schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present invention. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0053] Embodiment 1 of the present invention provides a processing method for extracting roadside visual information of a target vehicle, such as... Figure 1The schematic diagram of a processing method for extracting roadside visual information of a target vehicle provided in Embodiment 1 of the present invention is shown, which includes the following main steps:

[0054] Step 1: The first processing terminal receives roadside visual data from all traffic intersections and stores it in the image database; it also receives roadside perception data from all traffic intersections and stores it in the perception database; it receives vehicle travel data of the target vehicle and stores it in the corresponding travel database; and it creates a corresponding intersection visual information database for the target vehicle.

[0055] It should be noted that the first processing end in this embodiment of the invention is a data processing interface, a data processing device, a data processing terminal, a data processing equipment, a data processing server, a data processing service, a data processing system, or a data processing platform.

[0056] It should also be noted that at least one set of electronic police cameras and checkpoint cameras are installed at each entrance of each traffic intersection mentioned in the embodiments of the present invention. The viewing direction of the electronic police cameras is towards the inside of the current intersection, and the viewing direction of the checkpoint cameras is towards the outside of the current intersection; at least one roadside computing unit is configured at each traffic intersection. Specifically: 1) The electronic police cameras are used to continuously capture vehicle license plates, and the image sequence captured each time, along with its corresponding intersection sign, camera sign, and camera type, forms a corresponding roadside visual data and is sent to the first processing end; 2) The checkpoint cameras are used to perform real-time video capture of the current intersection traffic conditions around the clock, and the video data of the most recently specified duration, along with its corresponding intersection sign, camera sign, and camera type, forms a corresponding roadside visual data and is sent to the first processing end; 3) The roadside computing unit is used to detect the target type of each traffic participant at the current intersection, track and analyze the movement trajectory of each traffic participant, and the perceived target set and intersection sign of the most recently perceived duration form a corresponding roadside perception data and is sent to the first processing end.

[0057] It should also be noted that the target vehicle in this embodiment of the invention continuously records its own driving trajectory during driving and periodically sends a latest segment of its own driving trajectory to the first processing terminal; the vehicle type of the target vehicle in this embodiment of the invention is a sedan, truck, bus, two-wheeled motor vehicle or three-wheeled motor vehicle.

[0058] The current step 1 specifically includes:

[0059] Step 11: Receive roadside visual data from all traffic intersections and store it in the image database;

[0060] The image database includes multiple first image records; each first image record includes a first intersection sign, a first camera sign, a first camera type, a first image time period, and first image data; the first camera type includes electronic police cameras and checkpoint cameras; when the first camera type is an electronic police camera, the first image data is an image sequence; when the first camera type is a checkpoint camera, the first image data is a video data.

[0061] Specifically, this includes: each time the first processing terminal receives roadside visual data sent by a traffic intersection camera, it extracts the corresponding intersection sign, camera sign, camera type, and visual data from the current roadside visual data as the corresponding first intersection sign, first camera sign, first camera type, and first image data; and identifies the current first camera type; if the first camera type is an electronic police camera, the time period composed of the earliest and latest image times of the first image data is used as the corresponding first image time period; if the first camera type is a checkpoint camera, the time period composed of the start and end times of the first image data is used as the corresponding first image time period; and adds a corresponding first image record to the image database by combining the first intersection sign, first camera sign, first camera type, first image time period, and first image data obtained in this instance.

[0062] Step 12: Receive roadside sensing data from all traffic intersections and store it in the sensing database;

[0063] The perception database includes multiple first perception records; each first perception record includes a second intersection sign, a first perception time period, and a first perception target set; the first perception target set includes multiple first perception targets; each first perception target includes a first target identifier, a first target type, and a first target trajectory; the first target type includes pedestrians, animals, bicycles, cars, trucks, buses, two-wheeled motor vehicles, and three-wheeled motor vehicles; the first target trajectory includes multiple first trajectory points; each first trajectory point includes a first timestamp and a first coordinate.

[0064] Specifically, this includes: each time the first processing unit receives roadside perception data sent by the roadside computing unit of a traffic intersection, it extracts the corresponding intersection sign and perception target set from the current roadside visual data as the corresponding second intersection sign and first perception target set; and takes the time period composed of the earliest and latest timestamps of the current first perception target set as the corresponding first perception time period; and adds a corresponding first perception record composed of the second intersection sign, the first perception time period, and the first perception target set obtained this time to the perception database.

[0065] Step 13: Receive the vehicle trip data of the target vehicle and store it in the corresponding trip database;

[0066] The trip database includes multiple first trip records; each first trip record includes a first trip time period, a first trip trajectory, and a first processing status; the first trip trajectory includes multiple second trajectory points; each second trajectory point includes a second timestamp and a second coordinate; and the first processing status includes unprocessed and processed.

[0067] Specifically, this includes: each time the first processing end receives a segment of the target vehicle's driving trajectory, it takes the current trajectory as the corresponding first trip trajectory; it takes the time period composed of the earliest and latest timestamps of the current first trip trajectory as the corresponding first trip time period; it sets a corresponding first processing status as unprocessed; and it adds a corresponding first trip record composed of the first trip time period, the first trip trajectory, and the first processing status to the trip database.

[0068] Step 14: Create a corresponding intersection visual information database for the target vehicle;

[0069] The intersection visual information database includes multiple first visual records; the first visual records include third intersection signs, second camera signs, second camera types, second image time periods, and second image data; the second camera types include electronic police cameras and checkpoint cameras; when the second camera type is an electronic police camera, the second image data is an image sequence; when the second camera type is a checkpoint camera, the second image data is a video data.

[0070] Here, the intersection visual information database is initially an empty database with a total of 0 records.

[0071] Step 2: The first processing end extracts historical driving trajectories from the trip database according to the asynchronous processing mechanism, identifies the intersection information passed by each trajectory, improves each trajectory by combining intersection information and perception database, and extracts roadside visual information of each trajectory in batches based on the image database and refreshes the intersection visual information database based on the extraction results.

[0072] Specifically, the process includes: the first processing unit records all first trip records in the trip database that are in an unprocessed state as unprocessed records; when the total number of unprocessed records is not zero, the earliest added unprocessed record is used as the corresponding current trip record; the first trip trajectory of the current trip record is extracted as the corresponding current trip trajectory; and the traffic intersection information passed by the current trip trajectory is identified using a preset first high-precision map to obtain the corresponding list of intersections; when the list of intersections is not empty, the trajectory is first fused based on the list of intersections, the perception database, and the current trip trajectory to obtain the corresponding current fused trajectory; then, based on the current fused trajectory, the list of intersections, the preset list of intersection cameras, and the image database, batch roadside visual information extraction and visual information database refresh processing are performed; and the first processing state of the current trip record is reset to processed.

[0073] Here, when the list of passing intersections in this embodiment of the invention is not empty, it consists of one or more passing intersection records; the passing intersection records include traffic intersection signs and the time period of passing through the intersection.

[0074] The intersection camera list in this embodiment of the invention includes multiple first intersection records; each first intersection record corresponds one-to-one with a traffic intersection; each first intersection record includes a fourth intersection identifier and a first intersection camera set; each first intersection camera set includes multiple first intersection cameras; each first intersection camera includes a third camera identifier, a third camera type, first installation position coordinates, a first installation height, and a first installation angle; the third camera type includes electronic police cameras and checkpoint cameras; the first installation position coordinates are the ground projection point coordinates of the current camera position, the first installation height is the height of the current camera position perpendicular to the ground, and the first installation angle is the angle between the current camera axis and the vertical line to the ground.

[0075] In step 2, the specific processing steps for identifying the traffic intersections along the current travel trajectory using a preset high-precision map to obtain a list of corresponding intersections include:

[0076] Step A1: The first processing end obtains the traffic intersection signs and traffic intersection areas of each traffic intersection along the current travel trajectory by querying the first high-precision map;

[0077] Step A2 involves identifying the time periods of the current travel trajectory in each traffic intersection area and using the identification results as the corresponding time periods of the intersection journey;

[0078] Step A3, and a corresponding intersection record is formed by the traffic intersection signs and the time period of each intersection passed through;

[0079] Step A4, and then form a corresponding list of intersections from all the obtained intersection records.

[0080] In step 2, the specific processing steps for obtaining the corresponding fused trajectory by fusing the route through the list of intersections, the perception database, and the current travel trajectory include:

[0081] Step B1: The first processing unit iterates through all the intersection records in the intersection list; during this iteration, the currently iterated intersection record is taken as the corresponding current intersection record; the traffic intersection sign and intersection passage time of the current intersection record are taken as the corresponding current sign and current time period; the first perception record in the perception database whose second intersection sign matches the current sign and whose first perception time period intersects with the current time period is recorded as the second perception record; the first perception target set of all second perception records is merged to obtain a merged target set; in the merged target set, the first perception targets whose first target type does not match the vehicle type of the target vehicle are deleted, and the first perception targets whose trajectory duration is lower than the preset minimum trajectory duration are deleted. The target is deleted; and in the merged target set after target deletion, the first perceived targets that overlap with the first target trajectory are deduplicated; and each of the remaining first target trajectories in the merged target set is taken as the corresponding current target trajectory, and the intersection of the trajectory time periods of the current target trajectory and the current travel trajectory is taken as the current intersection time period. Multiple sampling points are obtained by sampling at equal intervals in the current intersection time period, and the shortest trajectory distance between the current target trajectory and the current travel trajectory at each sampling point is calculated. The average distance of all shortest trajectory distances corresponding to the current intersection time period is calculated; and the first target trajectory corresponding to the smallest average distance is taken as the current intersection trajectory; and the current travel trajectory and the current intersection trajectory are fused, and the fusion result is taken as the new current travel trajectory.

[0082] Step B2, and at the end of this round of traversal, the latest current travel trajectory is used as the corresponding current fusion trajectory.

[0083] In the current step 2, the specific processing steps for batch extraction of roadside visual information and updating of the visual information database based on the current fusion trajectory, the list of intersections passed through, the preset list of intersection cameras, and the image database include:

[0084] Step C1: The first processing end identifies the trajectory passing order of all intersection cameras passed by the current fused trajectory according to the list of intersections and the list of intersection cameras, and sorts all intersection cameras passed by based on the identification results to obtain the corresponding first intersection camera sequence.

[0085] The first intersection camera sequence is composed of multiple first intersection cameras arranged in sequence;

[0086] Step C2 involves iterating through all the cameras in the first intersection camera sequence. During this iteration, the currently iterated first intersection camera is designated as the current camera. The third camera identifier and third camera type of the current camera are used as the corresponding current identifier and current type. The current type is then identified. If the current type is a traffic enforcement camera, the coordinates of the intersection between the current camera's axis and the ground are calculated based on the first installation position coordinates, first installation height, and first installation angle, and the calculation result is used as the corresponding current coordinates. If the current type is a checkpoint camera, the first installation position coordinates of the current camera are used as the corresponding current coordinates. The timestamp of the trajectory point whose trajectory coordinates are closest to the current coordinates on the current fusion trajectory is used as the corresponding current time. The first image record in the image database that matches the first camera identifier with the current identifier and whose first image time period intersects with the current time is used as a corresponding first extraction record.

[0087] Step C3, and at the end of this round of traversal, each first extracted record is taken as a corresponding first visual record; and all the first visual records obtained this time are added to the intersection visual information database.

[0088] Step 3: When the first processing terminal receives the target time period input by the user, it summarizes all roadside visual information of the target vehicle during the target time period based on the intersection visual information database, generates corresponding first summary data, and feeds it back to the current user.

[0089] Specifically, the first processing unit extracts all first visual records that meet the target time period from the intersection visual information database and sorts them in chronological order to form the corresponding first record sequence; and feeds the first record sequence as the corresponding first summary data back to the current user.

[0090] Figure 2 This is a module structure diagram of a processing device for extracting roadside visual information of a target vehicle according to Embodiment 2 of the present invention. This device can be a terminal device or server implementing the aforementioned method embodiment, or it can be a device that enables the aforementioned terminal device or server to implement the aforementioned method embodiment. For example, the device can be a device or chip system of the aforementioned terminal device or server. Figure 2 As shown, the processing device for extracting roadside visual information of target vehicles provided in Embodiment 2 of the present invention includes: a data receiving module 201, a visual information production module 202, and a visual information query module 203.

[0091] The data receiving module 201 is used to receive roadside visual data from all traffic intersections and store it in the image database; and to receive roadside perception data from all traffic intersections and store it in the perception database; and to receive vehicle travel data of the target vehicle and store it in the corresponding travel database; and to create a corresponding intersection visual information database for the target vehicle.

[0092] The visual information production module 202 is used to extract historical driving trajectories from the trip database according to the asynchronous processing mechanism, identify the intersection information passed by each trajectory, improve each trajectory by combining intersection information and perception database, extract roadside visual information of each trajectory in batches based on the image database, and refresh the intersection visual information database based on the extraction results.

[0093] The visual information query module 203 is used to, upon receiving the target time period input by the user, summarize all roadside visual information of the target vehicle during the target time period based on the intersection visual information database, generate corresponding first summary data, and feed it back to the current user.

[0094] The processing device for extracting roadside visual information of target vehicles provided in this embodiment of the invention can execute the method steps in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described again here.

[0095] It should be noted that the division of the various modules in the above device is merely a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, these modules can be implemented entirely in software via processing element calls; they can be fully implemented in hardware; or some modules can be implemented in software via processing element calls, while others are implemented in hardware. For example, the data receiving module can be a separate processing element, or it can be integrated into a chip in the above device. Alternatively, it can be stored as program code in the memory of the above device, and called and executed by a processing element of the device. The implementation of other modules is similar. Moreover, these modules can be fully or partially integrated together, or they can be implemented independently. The processing element described here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each of the above modules can be completed through integrated logic circuits in the hardware of the processor element or through software instructions.

[0096] For example, these modules can be one or more integrated circuits configured to implement the above methods, such as one or more Application Specific Integrated Circuits (ASICs), one or more Digital Signal Processors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs). As another example, when a module is implemented using processing element scheduler code, the processing element can be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. Furthermore, these modules can be integrated together as a System-on-a-Chip (SOC).

[0097] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. This computer program product includes one or more computer instructions. When these computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the foregoing method embodiments are generated. The computer described above can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The aforementioned computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the aforementioned computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, Bluetooth, microwave, etc.) means. The aforementioned computer-readable storage medium can be any available medium that a computer can access, or a data storage device such as a server or data center that integrates one or more available media. The aforementioned available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state disks (SSDs)).

[0098] Figure 3 This is a schematic diagram of an electronic device provided in Embodiment 3 of the present invention. This electronic device can be a terminal device or server implementing the methods of the aforementioned embodiments, or it can be a terminal device or server connected to the aforementioned terminal device or server implementing the methods of the aforementioned embodiments. Figure 3As shown, the electronic device may include: a processor 301 (e.g., CPU), a memory 302, and a transceiver 303; the transceiver 303 is coupled to the processor 301, and the processor 301 controls the transmission and reception operations of the transceiver 303. The memory 302 may store various instructions for performing various processing functions and implementing the processing steps described in the foregoing embodiments. Preferably, the electronic device involved in the embodiments of the present invention further includes: a power supply 304, a system bus 305, and a communication port 306. The system bus 305 is used to realize communication connections between components. The communication port 306 is used for communication between the electronic device and other peripherals.

[0099] exist Figure 3 The system bus 305 mentioned can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This system bus can be divided into address bus, data bus, control bus, etc. For ease of representation, it is represented by only one thick line in the figure, but this does not indicate that there is only one bus or one type of bus. The communication interface is used to enable communication between the database access device and other devices (e.g., clients, read-write libraries, and read-only libraries). Memory may include Random Access Memory (RAM) and may also include non-volatile memory, such as at least one disk storage device.

[0100] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), graphics processing units (GPUs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0101] It should be noted that the embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when run on a computer, cause the computer to perform the methods and processes provided in the above embodiments.

[0102] This invention provides a method, apparatus, electronic device, and computer-readable storage medium for extracting roadside visual information of a target vehicle. As described above, this invention continuously receives roadside visual data from all traffic intersections and stores it in an image database; continuously receives roadside perception data from all traffic intersections and stores it in a perception database; continuously receives vehicle travel data of the target vehicle and stores it in a corresponding travel database; and creates a corresponding intersection visual information database for the target vehicle. It also continuously extracts the historical driving trajectory of the target vehicle from the travel database using an asynchronous processing mechanism, identifies the intersection information passed through each trajectory, refines each trajectory by combining the intersection information and the perception database, and batch extracts the roadside visual information of each refined trajectory based on the image database, refreshing the intersection visual information database based on the extraction results. Upon receiving a target time period input by the user, it summarizes all roadside visual information of the target vehicle during the target time period based on the intersection visual information database, generates corresponding summary data, and feeds it back to the current user. This invention provides an automated data production line for roadside visual information of target vehicles, enabling the automatic generation of such information. It also provides a time-based information query mechanism, allowing the acquisition of roadside visual information for target vehicles at any given time. This invention improves the efficiency of roadside visual information acquisition and reduces the data acquisition cost.

[0103] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented in hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0104] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A processing method for extracting roadside visual information of a target vehicle, characterized in that, The method includes: The first processing unit receives roadside visual data from all traffic intersections and stores it in the image database; it also receives roadside perception data from all traffic intersections and stores it in the perception database; it receives vehicle travel data of the target vehicle and stores it in the corresponding travel database; and it creates a corresponding intersection visual information database for the target vehicle. The first processing terminal extracts historical driving trajectories from the trip database according to the asynchronous processing mechanism, identifies the intersection information passed by each trajectory, improves each trajectory by combining the intersection information and the perception database, and extracts roadside visual information of each trajectory in batches based on the image database and refreshes the intersection visual information database based on the extraction results. When the first processing terminal receives the target time period input by the user, it summarizes all roadside visual information of the target vehicle in the target time period according to the intersection visual information database, generates corresponding first summary data, and feeds it back to the current user. The trip database includes multiple first trip records; each first trip record includes a first trip time period, a first trip trajectory, and a first processing status. The intersection visual information database includes multiple first visual records; the first visual records include a third intersection sign, a second camera sign, a second camera type, a second image time period, and second image data; the second camera type includes electronic police cameras and checkpoint cameras; when the second camera type is an electronic police camera, the second image data is an image sequence; when the second camera type is a checkpoint camera, the second image data is a video data. The asynchronous processing mechanism extracts historical driving trajectories from the trip database, identifies the intersection information passed through each trajectory, refines each trajectory by combining intersection information and the perception database, and batch extracts roadside visual information for each trajectory based on the image database, and refreshes the intersection visual information database based on the extraction results. Specifically, this includes: The first processing unit records all first trip records in the trip database that are in an unprocessed state as unprocessed records; and when the total number of unprocessed records is not 0, it takes the earliest added unprocessed record as the corresponding current trip record; and extracts the first trip trajectory of the current trip record as the corresponding current trip trajectory; and uses a preset first high-precision map to identify the traffic intersection information passed by the current trip trajectory to obtain the corresponding list of passing intersections; and when the list of passing intersections is not empty, it first performs trajectory fusion based on the list of passing intersections, the perception database, and the current trip trajectory to obtain the corresponding current fused trajectory, and then performs batch roadside visual information extraction and visual information database refresh processing based on the current fused trajectory, the list of passing intersections, the preset list of intersection cameras, and the image database; and then... The first processing status of the current trip record is reset to processed; wherein, when the list of passed intersections is not empty, it consists of one or more passed intersection records; the passed intersection records include traffic intersection signs and intersection passing time periods; the intersection camera list includes multiple first intersection records; the first intersection records correspond one-to-one with traffic intersections; the first intersection records include fourth intersection signs and first intersection camera sets; the first intersection camera sets include multiple first intersection cameras; the first intersection camera includes a third camera sign, a third camera type, first installation position coordinates, a first installation height, and a first installation angle; the third camera type includes electronic police cameras and checkpoint cameras; the first installation position coordinates are the ground projection point coordinates of the current camera position, the first installation height is the height of the current camera position perpendicular to the ground, and the first installation angle is the angle between the current camera axis and the vertical line of the ground.

2. The processing method for extracting roadside visual information of a target vehicle according to claim 1, characterized in that, At least one set of electronic police cameras and checkpoint cameras shall be installed at each entrance of each traffic intersection; the viewing direction of the electronic police cameras shall be facing the inside of the current intersection, and the viewing direction of the checkpoint cameras shall be facing the outside of the current intersection; at least one roadside computing unit shall be configured at each traffic intersection. The electronic police camera is used to continuously capture vehicle license plates, and the image sequence captured each time, along with its corresponding intersection sign, camera sign, and camera type, forms a corresponding roadside visual data which is sent to the first processing terminal. The checkpoint camera is used to capture real-time video of the current traffic conditions at the intersection around the clock, and sends a corresponding roadside visual data consisting of the video data of the most recent specified duration and its corresponding intersection sign, camera sign, and camera type to the first processing terminal. The roadside computing unit is used to detect the target type of each traffic participant at the current intersection, track and analyze the movement trajectory of each traffic participant, and send the corresponding roadside sensing data, which is composed of the sensing target set and intersection signage within the most recent specified time period, to the first processing terminal. The target vehicle continuously records its own driving trajectory during its driving process and periodically sends a latest segment of its driving trajectory to the first processing terminal; the target vehicle is a car, truck, bus, two-wheeled motor vehicle, or three-wheeled motor vehicle.

3. The processing method for extracting roadside visual information of a target vehicle according to claim 1, characterized in that, The image database includes multiple first image records; each first image record includes a first intersection sign, a first camera sign, a first camera type, a first image time period, and first image data; the first camera type includes electronic police cameras and checkpoint cameras; when the first camera type is an electronic police camera, the first image data is an image sequence; when the first camera type is a checkpoint camera, the first image data is a video data. The perception database includes multiple first perception records; each first perception record includes a second intersection sign, a first perception time period, and a first perception target set; the first perception target set includes multiple first perception targets. The first perceived target includes a first target identifier, a first target type, and a first target trajectory; the first target type includes pedestrians, animals, bicycles, cars, trucks, buses, two-wheeled motor vehicles, and three-wheeled motor vehicles; the first target trajectory includes multiple first trajectory points; the first trajectory point includes a first timestamp and a first coordinate; The first travel trajectory includes multiple second trajectory points; the second trajectory points include a second timestamp and a second coordinate; the first processing status includes unprocessed and processed.

4. The processing method for extracting roadside visual information of a target vehicle according to claim 3, characterized in that, The process of receiving roadside visual data from all traffic intersections and storing it in an image database specifically includes: Each time the first processing terminal receives roadside visual data from a traffic intersection camera, it extracts the corresponding intersection sign, camera sign, camera type, and visual data from the current roadside visual data to form the corresponding first intersection sign, first camera sign, first camera type, and first image data. It then identifies the current first camera type. If the first camera type is a traffic enforcement camera, the time interval consisting of the earliest and latest image times of the first image data is used as the corresponding first image time interval. If the first camera type is a checkpoint camera, the time interval consisting of the start and end times of the first image data is used as the corresponding first image time interval. Finally, the first intersection sign, first camera sign, first camera type, first image time interval, and first image data obtained in this processing step are combined to form a corresponding first image record, which is added to the image database.

5. The processing method for extracting roadside visual information of a target vehicle according to claim 3, characterized in that, The process of receiving roadside sensing data from all traffic intersections and storing it in the sensing database specifically includes: When the first processing terminal receives the roadside perception data sent by the roadside computing unit of a traffic intersection, it extracts the corresponding intersection identifier and perception target set from the current roadside visual data as the corresponding second intersection identifier and first perception target set; and takes the time period composed of the earliest and latest timestamps of the current first perception target set as the corresponding first perception time period; and adds a corresponding first perception record composed of the second intersection identifier, the first perception time period and the first perception target set obtained this time to the perception database.

6. The processing method for extracting roadside visual information of a target vehicle according to claim 3, characterized in that, The process of receiving the vehicle's trip data from the target vehicle and storing it in the corresponding trip database specifically includes: Each time the first processing terminal receives a segment of the vehicle's driving trajectory sent by the target vehicle, it takes the current trajectory as the corresponding first trip trajectory; takes the time period composed of the earliest and latest timestamps of the current first trip trajectory as the corresponding first trip time period; sets a corresponding first processing status to unprocessed; and adds a corresponding first trip record composed of the first trip time period, the first trip trajectory, and the first processing status to the trip database.

7. The processing method for extracting roadside visual information of a target vehicle according to claim 3, characterized in that, The step of identifying the traffic intersections along the current travel trajectory using a preset first high-precision map to obtain a corresponding list of intersections specifically includes: The first processing terminal obtains the traffic intersection identifiers and traffic intersection areas of each traffic intersection traversed by the current travel trajectory by querying the first high-precision map; identifies the trajectory time periods of the current travel trajectory in each traffic intersection area and uses the identification results as the corresponding traffic intersection traversal time periods; and forms a corresponding traffic intersection traversal record by combining the traffic intersection identifiers and traffic intersection traversal time periods of each traversed intersection; and forms a corresponding traffic intersection traversal list by combining all the obtained traffic intersection traversal records.

8. The processing method for extracting roadside visual information of a target vehicle according to claim 3, characterized in that, The step of fusing the route based on the list of intersections passed through, the perception database, and the current travel trajectory to obtain the corresponding current fused trajectory specifically includes: The first processing unit performs a round of traversal on all the traversal intersection records in the traversal intersection list; and during this round of traversal, the currently traversed traversal intersection record is taken as the corresponding current intersection record; and the traffic intersection identifier and the intersection passage time of the current intersection record are taken as the corresponding current identifier and current time period; and the first perception record in the perception database where the second intersection identifier matches the current identifier and the first perception time period intersects with the current time period is recorded as the second perception record; and the first perception target set of all second perception records is merged to obtain a merged target set; and in the merged target set, the first perception targets whose first target type does not match the vehicle type of the target vehicle are deleted, and the first perception targets whose trajectory duration is lower than the preset minimum trajectory duration are deleted; and the first perception target whose target deletion is completed is then deleted. In the merged target set, duplicate first-perceived targets whose first target trajectories overlap are deduplicated; the remaining first target trajectories in the merged target set are taken as the corresponding current target trajectories, and the intersection of the trajectory time periods of the current target trajectories and the current travel trajectory is taken as the current intersection time period. Multiple sampling points are obtained by sampling the current intersection time period at equal intervals, and the shortest trajectory distance between the current target trajectory and the current travel trajectory at each sampling point is calculated. The average distance of all shortest trajectory distances corresponding to the current intersection time period is calculated. The first target trajectory corresponding to the smallest average distance is taken as the current intersection trajectory. The current travel trajectory and the current intersection trajectory are fused, and the fusion result is taken as the new current travel trajectory. At the end of this round of traversal, the latest current travel trajectory is taken as the corresponding current fused trajectory.

9. The processing method for extracting roadside visual information of a target vehicle according to claim 3, characterized in that, The step of performing batch roadside visual information extraction and visual information database refresh based on the current fused trajectory, the list of intersections passed through, the preset list of intersection cameras, and the image database specifically includes: The first processing end identifies the trajectory passing order of all intersection cameras passed by the current fused trajectory according to the list of passing intersections and the list of intersection cameras, and sorts all the passing intersection cameras according to the identification results to obtain the corresponding first intersection camera sequence; the first intersection camera sequence is formed by sequentially sorting multiple first intersection cameras; The system iterates through all the cameras in the first intersection camera sequence. During this iteration, the currently iterated first intersection camera is designated as the current camera. The third camera identifier and third camera type of the current camera are used as the corresponding current identifier and current type. The current type is then identified. If the current type is a traffic enforcement camera, the coordinates of the intersection of the current camera's axis and the ground are calculated based on the first installation position coordinates, the first installation height, and the first installation angle, and the calculation result is used as the corresponding current coordinates. If the current type is a checkpoint camera, the first installation position coordinates of the current camera are used as the corresponding current coordinates. The timestamp of the trajectory point whose trajectory coordinates are closest to the current coordinates on the current fusion trajectory is used as the corresponding current time. The first image record in the image database where the first camera identifier matches the current identifier and the first image time period intersects with the current time is used as a corresponding first extraction record. At the end of this round of traversal, each of the first extracted records is taken as a corresponding first visual record; and all the first visual records obtained in this round are added to the intersection visual information database.

10. The processing method for extracting roadside visual information of a target vehicle according to claim 3, characterized in that, The step of summarizing all roadside visual information of the target vehicle during the target time period based on the intersection visual information database to generate corresponding first summary data and feeding it back to the current user specifically includes: The first processing unit extracts all the first visual records that meet the target time period from the intersection visual information database and sorts them in chronological order to form a corresponding first record sequence; and feeds back the first record sequence as the corresponding first summary data to the current user.

11. An apparatus for performing the processing method of extracting roadside visual information of a target vehicle according to any one of claims 1-10, characterized in that, The device includes: a data receiving module, a visual information production module, and a visual information query module; The data receiving module is used to receive roadside visual data from all traffic intersections and store it in the image database; and to receive roadside perception data from all traffic intersections and store it in the perception database; and to receive vehicle travel data of the target vehicle and store it in the corresponding travel database; and to create a corresponding intersection visual information database for the target vehicle. The visual information production module is used to extract historical driving trajectories from the trip database according to the asynchronous processing mechanism, identify the intersection information passed by each trajectory, improve each trajectory by combining the intersection information and the perception database, extract roadside visual information of each trajectory in batches based on the image database, and refresh the intersection visual information database based on the extraction results. The visual information query module is used to, upon receiving a target time period input by the user, summarize all roadside visual information of the target vehicle during the target time period based on the intersection visual information database, generate corresponding first summary data, and feed it back to the current user.

12. An electronic device, comprising: include: Memory, processor, and transceiver; The processor is configured to be coupled to the memory, read and execute instructions in the memory to implement the method according to any one of claims 1-10; The transceiver is coupled with the processor, and the transceiver is controlled by the processor to perform message transceiving.

13. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions, when the computer instructions are executed by a computer, the computer executes the method in any one of claims 1-10.

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