Emergency lane abnormal occupation identification method, device and equipment and storage medium

Abstract

The invention relates to the technical field of traffic control, and provides an emergency lane abnormal occupation identification method, device and equipment and a storage medium, and the method comprises the steps: selecting a to-be-identified vehicle from a starting point driving video shot by a camera at a starting point of a congested road section when the existence of the congested road section is detected; determining a terminal driving video shot by the terminal camera when the to-be-identified vehicle passes through the terminal camera of the congested road section; determining reference driving data of a reference vehicle and to-be-identified driving data of the to-be-identified vehicle based on the to-be-identified vehicle, the starting point driving video and the terminal point driving video; and according to the reference driving data and the to-be-identified driving data, carrying out emergency lane abnormal occupation identification on the to-be-identified vehicle. According to the method, the to-be-recognized vehicle is selected, and the reference driving data and the to-be-recognized driving data corresponding to the to-be-recognized vehicle are acquired based on the driving videos at the starting point and the ending point of the congested road section, so that the to-be-recognized vehicle is subjected to emergency lane abnormal occupation recognition.

Description

Technical Field

[0001] The present application relates to the field of traffic control technology, and in particular to a method, device, equipment and storage medium for identifying abnormal occupancy of an emergency lane. Background Art

[0002] With the continuous increase in the number of motor vehicles in my country, the traffic pressure on highways is increasing. As a life channel on highways, the emergency lane plays an important role in handling traffic accidents, rescue and other emergency situations. The illegal occupation of the emergency lane seriously affects the efficiency of road traffic and emergency rescue. Therefore, it is particularly important to strengthen the monitoring and investigation of illegal behaviors in the emergency lane.

[0003] In order to identify whether vehicles occupy the emergency lane during road congestion, it is necessary to install cameras along the highway to monitor the occupancy of the emergency lane in real time. However, since video surveillance is based on the installed cameras, it can only shoot the sections that the cameras can shoot, and identify the abnormal occupancy of the emergency lane based on the shot video. It is impossible to identify the abnormal occupancy of the emergency lane in the area without camera between two cameras. Summary of the invention

[0004] The main purpose of this application is to provide a method, device, equipment and storage medium for identifying abnormal occupation of an emergency lane, aiming to solve the technical problem that the prior art cannot identify abnormal occupation of an emergency lane on a camera-free section between two cameras on a congested section.

[0005] To achieve the above objectives, the present application proposes a method for identifying abnormal occupancy of an emergency lane, the method comprising: When a congested road section is detected, a vehicle to be identified is selected from the starting point driving video captured by a camera at the starting point of the congested road section; Determine the terminal driving video captured by the terminal camera when the vehicle to be identified passes through the terminal camera of the congested road section; Determine reference driving data of a reference vehicle and driving data to be identified of the vehicle to be identified based on the vehicle to be identified, the starting point driving video, and the end point driving video; Abnormal occupation of the emergency lane is identified for the vehicle to be identified based on the reference driving data and the driving data to be identified.

[0006] In one embodiment, the step of determining the reference driving data of the reference vehicle and the driving data to be identified of the vehicle to be identified based on the vehicle to be identified, the starting point driving video and the end point driving video includes: Determine, based on the vehicle to be identified and the starting point driving video, a calibration time point when the vehicle to be identified passes through the starting point of the congested road section; Determine a reference vehicle according to the starting point driving video and the calibration time point; Determine the driving data of the vehicle to be identified based on the vehicle to be identified, the starting point driving video and the end point driving video; Reference driving data of the reference vehicle is determined according to the reference vehicle, the starting point driving video and the ending point driving video.

[0007] In one embodiment, the step of determining a reference vehicle according to the starting driving video and the calibration time point includes: Determine the remaining vehicles based on the starting point driving video and the calibrated time point; Comparing the vehicle appearances of the remaining vehicles with the vehicle appearance of the vehicle to be identified for similarity; A reference vehicle is obtained by screening from the remaining vehicles based on the similarity comparison result.

[0008] In one embodiment, the step of identifying abnormal occupation of the emergency lane of the vehicle to be identified based on the reference driving data and the driving data to be identified includes: Obtaining a reference driving duration of the reference vehicle according to the reference driving data, and obtaining a driving duration threshold according to the reference driving duration; Obtaining a driving time of the vehicle to be identified based on the driving data to be identified, and comparing the driving time to be identified with the driving time threshold; If the driving time length of the vehicle to be identified reaches the driving time length threshold, it is determined that the vehicle to be identified abnormally occupies the emergency lane.

[0009] In one embodiment, after the step of comparing the driving duration to be identified with the driving duration threshold, the method further includes: If the driving time of the vehicle to be identified does not reach the driving time threshold, it is determined that the vehicle to be identified does not occupy the emergency lane; Selecting a cooperative vehicle from the starting point driving video based on the vehicle to be identified, and acquiring a driving image of the cooperative vehicle when the cooperative vehicle arrives at a preset position in the congested road section; Abnormal occupation of the emergency lane is identified for the recorded vehicle recorded in the driving image.

[0010] In one embodiment, before the step of acquiring the driving image of the cooperative vehicle when the cooperative vehicle arrives at the preset position in the congested road section, the step further includes: Acquire the standard driving speed of the vehicle to be identified from the driving data to be identified, and acquire the cooperative driving duration of the cooperative vehicle based on the starting point driving video; Acquire the current vehicle position of the cooperative vehicle based on the standard driving speed and the cooperative driving duration; Based on the current vehicle position, it is determined whether the cooperative vehicle has arrived at a preset position in the congested road section.

[0011] In one embodiment, the step of obtaining a reference driving duration of the reference vehicle according to the reference driving data includes: Obtaining the entrance and exit driving video captured by the camera at the service station in the congested road section; Obtaining a reference temporary stop duration of the reference vehicle based on the import and export driving video, and obtaining a reference total driving duration of the reference vehicle based on the reference driving data; Obtaining a reference driving time of the reference vehicle according to the reference total driving time and the reference temporary stop time; The step of obtaining the driving time of the vehicle to be identified based on the driving data to be identified includes: Obtaining the temporary stop time of the vehicle to be identified based on the entry and exit driving video, and obtaining the total driving time of the vehicle to be identified based on the driving data to be identified; The driving time to be identified of the reference vehicle is obtained according to the total driving time to be identified and the temporary stop time to be identified.

[0012] In addition, to achieve the above purpose, the present application also proposes a device for identifying abnormal occupation of an emergency lane, the device comprising: A starting point identification module is used to select a vehicle to be identified from the starting point driving video shot by a camera at the starting point of the congested road section when a congested road section is detected; The end point recognition module is used to determine the end point driving video captured by the camera at the end point when the vehicle to be identified passes through the camera at the end point of the congested road section; A data acquisition module, used to determine the reference driving data of the reference vehicle and the to-be-identified driving data of the to-be-identified vehicle based on the to-be-identified vehicle, the starting point driving video and the end point driving video; The occupancy identification module is used to identify abnormal occupancy of the emergency lane of the vehicle to be identified based on the reference driving data and the driving data to be identified.

[0013] In addition, to achieve the above-mentioned purpose, the present application also proposes an emergency lane abnormal occupation identification device, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the emergency lane abnormal occupation identification method as described above.

[0014] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the method for identifying abnormal occupancy of the emergency lane as described above are implemented.

[0015] The present application proposes a method, device, equipment and storage medium for identifying abnormal occupation of an emergency lane. The method comprises: when a congested road section is detected, selecting a vehicle to be identified from a starting point driving video taken by a camera at the starting point of the congested road section; determining an end point driving video taken by a camera at the end point when the vehicle to be identified passes through the camera at the end point of the congested road section; determining reference driving data of a reference vehicle and driving data to be identified of the vehicle to be identified based on the vehicle to be identified, the starting point driving video and the end point driving video; and identifying abnormal occupation of the emergency lane for the vehicle to be identified based on the reference driving data and the driving data to be identified. This application can retrieve the starting point driving video shot by the camera at the starting point of the congested section after detecting the existence of the congested section, and select the vehicle to be identified from the starting point driving video, determine the reference driving data of the reference vehicle and the driving data to be identified of the ground vehicle based on the starting point driving video and the terminal driving video of the vehicle to be identified passing through the terminal of the congested section, and perform abnormal occupation of the emergency lane on the vehicle to be identified according to the driving data to be identified and the driving data of the reference vehicle. Since the driving time and driving speed of the vehicle in the normal driving of the congested section are different from those of the vehicle occupying the emergency lane, there is a difference between the driving data of the normal driving vehicle and the driving data of the vehicle occupying the emergency lane. Therefore, this application determines the driving data to be identified of the vehicle to be identified and the reference driving data corresponding to the reference vehicle based on the starting point driving video shot at the starting point of the congested section and the terminal driving video at the terminal of the congested section, and judges whether the vehicle to be identified occupies the emergency lane by comparing the driving data to be identified with the reference driving data, so as to realize the abnormal occupation of the emergency lane on the section without camera between two cameras in the congested section. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0018] Figure 1 This is a flow chart of a first embodiment of the method for identifying abnormal occupation of an emergency lane proposed in this embodiment; Figure 2 A schematic diagram of a congested road section in the method for identifying abnormal occupation of an emergency lane proposed in this embodiment; Figure 3 A schematic diagram of a road section to be detected in the method for identifying abnormal occupation of an emergency lane proposed in this embodiment; Figure 4 This is a flow chart of a second embodiment of the method for identifying abnormal occupation of an emergency lane proposed in this embodiment; Figure 5 This is a working principle diagram of the cooperative vehicle in the method for identifying abnormal occupation of the emergency lane proposed in this embodiment; Figure 6 A diagram of the emergency lane abnormal occupancy identification device provided in this embodiment; Figure 7 The figure is a schematic diagram of the structure of an emergency lane abnormal occupancy recognition device suitable for implementing the present embodiment.

[0019] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0020] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0021] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0022] It should be noted that all directional indications in the embodiments of the present application (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0023] It is understandable that with the continuous increase in the number of motor vehicles in my country, the traffic pressure on highways is increasing. As a life channel on highways, the emergency lane plays an important role in handling traffic accidents, rescue and other emergency situations. The illegal occupation of the emergency lane seriously affects the efficiency of road traffic and emergency rescue. Therefore, it is particularly important to strengthen the monitoring and investigation of illegal behaviors in the emergency lane.

[0024] In order to identify whether vehicles occupy the emergency lane during road congestion, it is necessary to install cameras along the highway to monitor the occupancy of the emergency lane in real time. However, since video surveillance is based on the installed cameras, it can only shoot the sections that the cameras can shoot, and identify the abnormal occupancy of the emergency lane based on the shot video. It is impossible to identify the abnormal occupancy of the emergency lane in the area without camera between two cameras.

[0025] Therefore, in order to solve the problem that the existing technology cannot identify abnormal occupation of the emergency lane in the section without a camera between two cameras in a congested section, this embodiment proposes a method, device, equipment and storage medium for identifying abnormal occupation of the emergency lane. Since the driving time and driving speed of the vehicle in the normal driving of the congested section are different from those of the vehicle occupying the emergency lane, there is a difference between the driving data of the vehicle in normal driving and the driving data of the vehicle occupying the emergency lane. Therefore, this application determines the driving data of the vehicle to be identified and the reference driving data corresponding to the reference vehicle based on the starting driving video taken at the starting point of the congested section and the end driving video taken at the end point of the congested section. By comparing the driving data to be identified with the reference driving data, it is determined whether the vehicle to be identified occupies the emergency lane, so as to realize the identification of abnormal occupation of the emergency lane in the section without a camera between two cameras in the congested section.

[0026] For ease of understanding, the following combination Figures 1 to 7 The emergency lane abnormal occupancy identification method provided in the embodiment of the present application and the emergency lane abnormal occupancy identification method, device, equipment and storage medium provided in the following embodiments are specifically introduced.

[0027] The present application embodiment provides a method for identifying abnormal occupation of an emergency lane, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the method for identifying abnormal occupation of the emergency lane proposed in this embodiment.

[0028] like Figure 1 As shown, the method includes: Step S10: When a congested road section is detected, a vehicle to be identified is selected from the starting point driving video captured by a camera at the starting point of the congested road section.

[0029] It should be noted that the execution subject of this embodiment may be a computing service device with emergency lane abnormal occupation recognition, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, etc. The following takes the emergency lane abnormal occupation recognition device (hereinafter referred to as the device) as an example to illustrate this embodiment and the following embodiments.

[0030] It should be noted that, in this embodiment, the location where a camera exists in the road section can be used as a sampling point, and the above-mentioned congested road section can be a road section between at least two cameras and the traffic data of the sampling points corresponding to the two cameras meet the preset congestion conditions. The above-mentioned traffic data can be the traffic volume and traffic speed in the video captured by the above-mentioned sampling point, and the above-mentioned preset congestion condition can be the traffic volume and traffic speed preset by the user. The above-mentioned starting point driving video can be a driving video captured by the camera at the starting point of the above-mentioned congested road section, and the above-mentioned vehicle to be identified can be a vehicle that passes through the starting point of the above-mentioned congested road section and is captured by the camera at the starting point of the above-mentioned congested road section. In this embodiment, the above-mentioned device can divide the sampling points corresponding to the above-mentioned at least two cameras according to the direction of traffic flow to obtain the starting point and the end point of the congested road section.

[0031] In one example, in order to ensure that the vehicle to be identified is a vehicle that needs to be identified for abnormal occupation of the emergency lane when passing through the congested road section, it is necessary to ensure that the vehicle passes through the starting point and the end point of the congested road section. Therefore, it is necessary to perform image analysis on the starting point driving video shot by the camera at the starting point of the congested road section and the end point driving video shot by the camera at the end point of the congested road section, and select the vehicle that passes through the starting point and the end point of the congested road section as the vehicle to be identified. The end point driving video can be a driving video shot by the camera at the end point of the congested road section.

[0032] refer to Figure 2 , Figure 2 Schematic diagram of a congested road section in the method for identifying abnormal occupation of an emergency lane proposed in this embodiment. In a specific implementation, after detecting the presence of a congested road section, the above device can use the current traffic flow method (i.e. Figure 2 The starting point of the above congested road section (i.e. Figure 2 The starting point of the congested section in Figure 2 The end point of the congested section in the figure) and the camera at the starting point of the congested section (i.e. Figure 2 The starting point driving video captured by camera 1) and the end point camera of the congested road section (i.e. Figure 2The destination driving video captured by camera 2) is processed by video analysis on the starting driving video to obtain the license plate number of the vehicle passing the starting point of the congested road section and record it; the destination driving video is processed by video analysis to obtain the license plate number of the vehicle passing the end point of the congested road section, and the vehicle corresponding to the same license plate number recorded at both the starting point and the end point is selected as the vehicle to be identified.

[0033] Furthermore, in order to detect whether there is a congested road section, before the step of detecting the presence of a congested road section, the method further includes: Obtain the sampling point video shot by the camera at each sampling point of the road section to be detected; Obtaining traffic data corresponding to each of the sampling points based on the video shot at the sampling points; When at least two of the traffic data satisfy the preset congestion condition, the road section between the sampling points is determined to be a congested road section.

[0034] It should be noted that the road section to be detected may be a road section with at least two sampling points. Since the location of the camera in the road section is used as the sampling point in this embodiment, each sampling point has a camera to shoot a video around the sampling point. The video shot at the sampling point may be a video obtained by the camera at the sampling point shooting the area. The traffic data may be data such as the traffic volume and traffic speed at the sampling point, and the preset congestion condition may be a preset traffic volume and traffic speed.

[0035] refer to Figure 3 , Figure 3 Schematic diagram of the road section to be detected in the method for identifying abnormal occupation of the emergency lane proposed in this embodiment. In a specific implementation, the above device can correspond to all sampling points (i.e. Figure 3 The camera (i.e. Figure 3 The video of the sampling point taken by the camera in the sampling point is analyzed to obtain the traffic volume and traffic speed corresponding to each sampling point. When the traffic volume reaches the preset traffic volume in the preset congestion condition or the traffic speed reaches the preset traffic speed in the preset congestion condition, the sampling point is determined to be a congestion node (i.e. Figure 3 The above device determines all the congested nodes by analyzing the traffic volume and traffic speed corresponding to each sampling point. When there are at least two congested nodes, the road section between the congested nodes is determined as a congested road section (i.e. Figure 3 congested sections in the road), and through the traffic flow direction (i.e. Figure 3 The traffic direction in the congested section), taking the above congested node as the starting point of the congested section (i.e. Figure 3 The starting point of the congested section in the Figure 3the end point of the congested section in the route).

[0036] Step S20: determining the destination driving video captured by the camera at the destination when the vehicle to be identified passes through the camera at the destination of the congested road section.

[0037] In a specific implementation, after determining the vehicle to be identified, the above-mentioned device finds the time point when the vehicle to be identified passes the end point of the congested road section from all the license plate numbers captured and recorded by the camera at the end point through the license plate number of the vehicle to be identified, and based on the time point, retrieves a video of a preset length as the end point driving video.

[0038] Step S30: Determine reference driving data of a reference vehicle and driving data to be identified of the vehicle to be identified based on the vehicle to be identified, the starting point driving video, and the end point driving video.

[0039] It should be noted that the reference vehicle may be a vehicle that passes through the starting point of the congested road section at the same time period as the vehicle to be identified and has a similar appearance to the vehicle to be identified. The reference driving data may be the driving data of the reference vehicle when it is traveling on the congested road section, such as driving time and driving speed. The driving data to be identified may be the driving data of the vehicle to be identified when it is traveling on the congested road section, such as driving time and driving speed.

[0040] In a specific implementation, the above-mentioned device determines the time when the vehicle to be identified passes through the starting point of the congested section and the end point of the congested section by analyzing the above-mentioned vehicle to be identified, the starting point driving video and the end point driving video, and obtains the total driving time taken by the vehicle to be identified to pass through the congested section based on the time at the end point of the congested section minus the time at the starting point of the congested section, and obtains the driving speed of the vehicle to be identified based on the length of the congested section and the total driving time to be identified, and uses the total driving time to be identified and the driving speed to be identified as the driving data to be identified, and based on the above principle, obtains the reference total driving time and reference driving speed corresponding to the reference measurement as reference driving data.

[0041] Further, in order to determine the reference driving and thus obtain the reference driving data, the step of determining the reference driving data of the reference vehicle and the driving data to be identified of the vehicle to be identified based on the vehicle to be identified, the starting point driving video and the end point driving video includes: Step S31: determining a calibration time point when the vehicle to be identified passes the starting point of the congested road section based on the vehicle to be identified and the starting point driving video.

[0042] It should be noted that the above-mentioned calibration time point may be the time point when the vehicle to be identified passes the starting point of the congested road section.

[0043] Step S32: determining a reference vehicle according to the starting driving video and the calibration time point; It should be noted that the reference vehicle may be a vehicle that passes the starting point of the congested road section at the same time period as the vehicle to be identified and has a similar appearance to the vehicle to be identified. The time period may be a time period consisting of a period before and a period after the calibration time point. The period may be a preset period, such as a few minutes, a dozen seconds, etc.

[0044] Step S33: determining the driving data of the vehicle to be identified based on the vehicle to be identified, the starting point driving video and the end point driving video; Step S34: Determine reference driving data of the reference vehicle according to the reference vehicle, the starting point driving video and the end point driving video.

[0045] In a specific implementation, after obtaining the calibration time point when the vehicle to be identified passes through the starting point of the congested road section, the above device obtains a section of driving video of the starting point with a first preset time length before the calibration time point and a second preset time length after the calibration time point, and performs image analysis on the section of driving video of the starting point to obtain a reference vehicle. The above first preset time length can be a user-preset time length, such as a few minutes, more than ten seconds, etc. The above second preset time length can be a user-preset time length, such as a few minutes, more than ten seconds, etc.

[0046] After the reference vehicle is determined, the reference total driving time consumed by each reference vehicle from the starting point to the end point of the congested section is determined based on the starting point driving video and the end point driving video, and the reference driving speed of the reference vehicle is determined based on the reference total driving time and the length of the congested section, and the reference driving data is obtained based on the reference total driving time and the reference driving speed. The above-mentioned device can also determine the total driving time to be identified that the vehicle to be identified consumes from the starting point of the congested section to the end point of the congested section based on the starting point driving video and the end point driving video, and obtain the driving speed to be identified based on the total driving time to be identified and the length of the congested section, and finally use the total driving time to be identified and the driving speed to be identified as the driving data to be identified.

[0047] Furthermore, since the driving speeds of different types of vehicles (such as cars and trucks) on the highway vary greatly (the speed of trucks is generally lower than that of cars, and the traffic efficiency is relatively lower when congestion occurs), in order to increase the accuracy of identifying abnormal occupancy of the emergency lane, the step of determining the reference vehicle according to the starting driving video and the calibration time point includes: Step S321: determining the remaining vehicles based on the starting driving video and the calibrated time point; Step S322: comparing the vehicle appearances of the remaining vehicles with the vehicle appearance of the vehicle to be identified for similarity; Step S323: Filter and obtain a reference vehicle from the remaining vehicles based on the similarity comparison result.

[0048] It should be noted that the remaining vehicles may be all vehicles that appear in the driving video at the starting point of the time interval formed by the calibration time, the first preset time and the second preset time. The vehicle shape may be the size or appearance of the vehicle, and the similarity comparison result may be the similarity between the vehicle shape of the remaining vehicles and the vehicle shape of the vehicle to be identified.

[0049] In a specific implementation, after obtaining the calibration time, the above-mentioned device then obtains the driving video of the starting point of the time interval consisting of the first preset time length before the calibration time point and the second preset time length after the calibration time point, performs image analysis on the driving video of the above-mentioned time interval, obtains all vehicles passing through the starting point of the above-mentioned congested road section in the time interval as the remaining vehicles, and compares the vehicle appearance of the remaining vehicles with the vehicle appearance of the vehicle to be identified, obtains the size similarity and appearance similarity of the remaining vehicles with the vehicle to be identified, and when there is a vehicle in the remaining vehicles whose size similarity with the size of the vehicle to be identified reaches a similarity threshold and the appearance similarity of the vehicle reaches a similarity threshold, the vehicle is selected from the remaining vehicles as a reference vehicle, and if there is a vehicle in the remaining vehicles whose size similarity with the size of the vehicle to be identified does not reach the similarity threshold or the appearance similarity of the vehicle does not reach the similarity threshold, the vehicle is selected and not used as a reference vehicle. The above-mentioned similarity threshold can be a percentage value preset by the user.

[0050] In another example, in order to prevent misjudgment caused by other vehicles leaving the highway or changing routes, the step of selecting a reference vehicle from the other vehicles based on the similarity comparison result further includes: Obtaining the exit driving video shot by the camera at the highway exit of the congested road section; A reference vehicle is obtained by screening from the remaining vehicles based on the exit driving video and the similarity comparison result.

[0051] It should be noted that the exit driving video may be a video taken by a camera at the exit of the congested road section. In a specific implementation, after determining the remaining vehicles, the device may also retrieve the exit driving video taken by a camera at the exit of the congested road section, and determine whether there are other vehicles leaving the highway or changing routes. When there are other vehicles appearing in the exit driving video, the departing vehicle is deleted from the remaining vehicles to obtain the remaining remaining vehicles, and the vehicle appearance of the remaining remaining vehicles is compared with the vehicle appearance of the vehicle to be identified for similarity, and based on the similarity comparison result, the vehicle whose similarity comparison result reaches the similarity threshold is selected from the remaining remaining vehicles as a reference vehicle.

[0052] Step S40: identifying abnormal occupation of the emergency lane of the vehicle to be identified based on the reference driving data and the driving data of the vehicle to be identified.

[0053] In a specific implementation, the above-mentioned device can obtain the reference total driving time consumed by the corresponding reference vehicle from the starting point of the above-mentioned congested road section to the end point of the congested road section based on the above-mentioned reference driving data, and obtain the total driving time consumed by the vehicle to be identified from the starting point of the above-mentioned congested road section to the end point of the congested road section based on the above-mentioned driving data to be identified, and obtain a driving time threshold based on each reference total driving time. The driving time threshold can be an average driving time obtained based on each reference total driving time, or it can be a threshold obtained based on the average time and a preset percentage. In this embodiment, the average driving time is used for explanation, but this embodiment is not specifically limited. When the above-mentioned total driving time to be identified reaches the above-mentioned driving time threshold, it is determined that the vehicle to be identified abnormally occupies the emergency lane.

[0054] For ease of understanding, the following is explained by way of examples, but no specific limitation is imposed on this embodiment. The above-mentioned device can obtain the road condition information of the target road section, and when the road condition information meets the preset emergency occupation condition, request to obtain the traffic data of the target road section, execute the traffic abnormality analysis process to perform image processing on the driving image, identify the license plate of the passing vehicle, and record the corresponding location and passage time. Among them, the above-mentioned device can cooperate with highway / traffic related units to obtain data access and call permissions of the relevant platform to obtain basic information such as road condition information and traffic data, among which the road condition information can be the traffic volume and vehicle speed. At this time, the emergency occupation condition can be that the traffic volume reaches the traffic jam threshold. Traffic data includes the sampling point location corresponding to the high-speed camera and the captured driving video.

[0055] The above equipment can analyze the driving time and speed of vehicles on the road when the road is congested, and compare them with similar vehicles to analyze whether they illegally occupy the emergency lane. For example, if a section of a highway is congested, vehicle A takes 10 minutes to pass, while vehicles B, C, and D in similar situations take at least 20 minutes to pass, then A is suspected of illegally using the emergency lane.

[0056] In one example, after determining that the vehicle to be identified is abnormally occupying the emergency lane, the above-mentioned device can also send a warning to the relevant vehicle owner through text messages or ringtones, so as to better monitor the emergency lane and reduce the chance of illegal occupation.

[0057] The present embodiment proposes a method for identifying abnormal occupancy of an emergency lane, the method comprising: due to the different driving time and driving speed of vehicles driving normally in a congested section and vehicles occupying the emergency lane, there is a difference between the driving data of the vehicle driving normally and the driving data of the vehicle occupying the emergency lane. Therefore, in the present embodiment, the driving data of the vehicle to be identified and the reference driving data corresponding to the reference vehicle are determined according to the starting driving video taken at the starting point of the congested section and the ending driving video taken at the end point of the congested section. By comparing the driving data to be identified with the reference driving data, it is determined whether the vehicle to be identified occupies the emergency lane, thereby realizing the identification of abnormal occupancy of the emergency lane for the blank section without camera between two cameras in the congested section.

[0058] Based on the first embodiment, in the second embodiment, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be described in detail later. Figure 4 , Figure 4 This is a flow chart of a second embodiment of the method for identifying abnormal occupation of an emergency lane proposed in this embodiment. In order to further determine whether the vehicle to be identified abnormally occupies the emergency lane, the step of identifying abnormal occupation of the emergency lane for the vehicle to be identified based on the reference driving data and the driving data to be identified includes: Step S41: obtaining a reference driving duration of the reference vehicle according to the reference driving data, and obtaining a driving duration threshold according to the reference driving duration.

[0059] Furthermore, since there are service stations in the expressway, in order to prevent the reference vehicle from entering the service station for temporary parking, resulting in deviation in the reference driving time, the step of obtaining the reference driving time of the reference vehicle according to the reference driving data includes: Obtaining the entrance and exit driving video captured by the camera at the service station in the congested road section; Obtaining a reference temporary stop duration of the reference vehicle based on the import and export driving video, and obtaining a reference total driving duration of the reference vehicle based on the reference driving data; A reference driving time of the reference vehicle is obtained according to the reference total driving time and the reference temporary stop time.

[0060] It should be noted that the above-mentioned import and export driving video may be the video shot by the camera at the service station in the above-mentioned congested road section. The above-mentioned reference temporary stop duration may be the duration of the temporary stop of the reference vehicle at the above-mentioned service station. In a specific implementation, the above-mentioned device may also retrieve the import and export driving video shot by the camera at the service station in the above-mentioned congested road section, and analyze the import and export driving video to determine whether the reference vehicle enters the service station. If so, the reference entry time point of the reference vehicle entering the service station and the reference exit time point of the reference vehicle exiting the service station are obtained. Based on the reference entry time point and exit time point, the reference temporary stop duration of the reference vehicle temporarily stopping at the above-mentioned service station is obtained. Finally, the reference driving duration of the reference vehicle is obtained by subtracting the reference temporary stop duration from the above-mentioned reference total driving duration.

[0061] Step S42: obtaining the driving time of the vehicle to be identified based on the driving data to be identified, and comparing the driving time to be identified with the driving time threshold; Furthermore, since there are service stations in the expressway section, in order to prevent the reference driving time from being deviated due to the vehicle to be identified entering the service station for temporary parking, the step of obtaining the driving time of the vehicle to be identified based on the driving data of the vehicle to be identified includes: Obtaining the temporary stop time of the vehicle to be identified based on the entry and exit driving video, and obtaining the total driving time of the vehicle to be identified based on the driving data to be identified; The driving time to be identified of the reference vehicle is obtained according to the total driving time to be identified and the temporary stop time to be identified.

[0062] It should be noted that the above-mentioned temporary stop duration to be identified can be the duration of temporary stop of the vehicle to be identified at the above-mentioned service station. In a specific implementation, the above-mentioned device can also retrieve the entry and exit driving video captured by the camera at the service station in the above-mentioned congested road section, and analyze the entry and exit driving video to determine whether the vehicle to be identified has entered the service station. If it has entered, the entry time point to be identified when the vehicle to be identified enters the service station and the exit time point to be identified when the vehicle to be identified exits the service station are obtained. Based on the entry time point to be identified and the exit time point to be identified, the temporary stop duration to be identified of the vehicle to be identified temporarily stopping at the above-mentioned service station is obtained. Finally, the driving time to be identified of the vehicle to be identified is obtained by subtracting the temporary stop duration to be identified from the above-mentioned total driving time to be identified.

[0063] Step S43: If the driving time of the vehicle to be identified reaches the driving time threshold, it is determined that the vehicle to be identified abnormally occupies the emergency lane.

[0064] In a specific implementation, the above-mentioned device can obtain the reference driving time consumed by the corresponding reference vehicle from the above-mentioned congested road section starting point to the congested road section end point according to the above-mentioned reference driving data, and obtain the driving time consumed by the vehicle to be identified from the above-mentioned congested road section starting point to the congested road section end point according to the above-mentioned driving data to be identified, and obtain a driving time threshold based on each reference driving time, and the driving time threshold can be an average driving time obtained based on each reference driving time or a threshold obtained based on the average time and a preset percentage. In this embodiment, the average driving time is used for explanation, but no specific limitation is made to this embodiment. When the above-mentioned driving time to be identified reaches the above-mentioned driving time threshold, it is determined that the vehicle to be identified abnormally occupies the emergency lane.

[0065] It should be noted that vehicle vision networking technology and electronic traffic police vision collaboration refer to the combination of the vehicle's vision system with the traffic monitoring system (such as the electronic traffic police system) to achieve more efficient and safe traffic management, in which the traffic police can send an electronic traffic police vision collaboration request to the corresponding vehicle / vehicle data background management party.

[0066] Furthermore, in order to more accurately identify abnormal occupation of the emergency lane for vehicles in the unmonitored congested road section between the two cameras, after the step of comparing the driving time to be identified with the driving time threshold, the method further includes: If the driving time of the vehicle to be identified does not reach the driving time threshold, it is determined that the vehicle to be identified does not occupy the emergency lane; Selecting a cooperative vehicle from the starting point driving video based on the vehicle to be identified, and acquiring a driving image of the cooperative vehicle when the cooperative vehicle arrives at a preset position in the congested road section; Abnormal occupation of the emergency lane is identified for the recorded vehicle recorded in the driving image.

[0067] It should be noted that the above-mentioned cooperative vehicle can be a vehicle with visual networking conditions, and the above-mentioned driving image can be an image captured by the driving recorder or other camera equipment of the above-mentioned cooperative vehicle. The above-mentioned preset position can be a position obtained by evenly dividing the length of the above-mentioned congested road section. For example, when the length of the congested road section is 3 kilometers, the positions of 500m-1000m, 1500m, and 2500-3000m are selected as preset positions. In a specific implementation, after the driving time of the vehicle to be identified does not reach the driving time threshold and it is determined that the vehicle to be identified does not occupy the emergency lane, the above-mentioned device analyzes the vehicle appearing in the starting driving video, obtains the license plate number of the vehicle, and retrieves the corresponding vehicle management record of the vehicle management office based on the license plate number to determine whether the vehicle has visual networking conditions. When a vehicle with visual networking conditions is detected, the position of the cooperative vehicle is determined based on the driving data to be identified corresponding to the above-mentioned vehicle to be identified. When the cooperative vehicle drives to the preset position, an electronic traffic police visual cooperation request is sent to the corresponding cooperative vehicle to obtain the driving image that can be captured by the cooperative vehicle. By analyzing the driving image, the recorded vehicle recorded in the driving image is obtained, and through image analysis, it is determined whether the recorded vehicle recorded in the driving image is occupying the emergency lane, so as to identify the abnormal occupation of the emergency lane for the recorded vehicle.

[0068] Furthermore, before the step of acquiring the driving image of the cooperative vehicle when the cooperative vehicle arrives at the preset position in the congested road section, the step further includes: Acquire the standard driving speed of the vehicle to be identified from the driving data to be identified, and acquire the cooperative driving duration of the cooperative vehicle based on the starting point driving video; Acquire the current vehicle position of the cooperative vehicle based on the standard driving speed and the cooperative driving duration; Based on the current vehicle position, it is determined whether the cooperative vehicle has arrived at a preset position in the congested road section.

[0069] It should be understood that the above-mentioned standard driving speed may be the driving speed of the vehicle to be identified that is determined not to occupy the emergency lane when passing through the above-mentioned congested section, the above-mentioned collaborative driving duration may be the duration of time that the collaborative vehicle has passed the starting point of the congested section in the above-mentioned starting point driving video, and the above-mentioned current vehicle position may be the position of the above-mentioned collaborative vehicle.

[0070] In a specific implementation, after determining that the vehicle to be identified is not occupying the emergency lane, the above-mentioned device obtains the driving speed corresponding to the vehicle to be identified as the standard driving speed of vehicles in the congested section, and by analyzing the driving video of the above-mentioned starting point, confirms the collaborative driving time that has passed after the above-mentioned collaborative vehicle passed the starting point of the congested section, and determines whether the collaborative vehicle has reached the preset position based on the collaborative driving time and the standard driving speed.

[0071] Furthermore, considering that if the cooperative vehicle is not in a lane adjacent to the emergency lane, the occupancy of the emergency lane may not be captured, in order to ensure that the driving image captured by the cooperative vehicle is an image of the emergency lane, it is necessary to first determine that the cooperative vehicle is in a lane adjacent to the emergency lane, and then the step of identifying abnormal occupancy of the emergency lane for the recorded vehicle recorded in the driving image includes: Based on the driving image, a relative distance between the cooperative vehicle and a road boundary of the congested road section is obtained; When the relative distance satisfies a preset distance condition, the driving image is analyzed to obtain a recorded vehicle recorded in the driving image; The relative position of the recorded vehicle and the cooperative vehicle is obtained, and based on the relative position, abnormal occupation of the emergency lane of the recorded vehicle is identified.

[0072] It should be noted that the preset distance condition may be the distance between the rightmost lane in the congested road section and the road boundary, i.e., the width of the emergency lane. The relative distance may be the distance between the cooperative vehicle and the road boundary. The recorded vehicle may be the vehicle that appears in the driving image, and the relative position may be the position of the recorded vehicle relative to the cooperative vehicle.

[0073] refer to Figure 5 , Figure 5 This is a working principle diagram of the cooperative vehicle in the emergency lane abnormal occupancy identification method proposed in this embodiment. In the specific implementation, in order to ensure that the cooperative vehicle is located in the rightmost lane of the congested road section, so as to ensure that the driving image captured on the right side of the cooperative vehicle is the emergency lane image, the above-mentioned device can perform distance analysis on the driving image fed back by the cooperative vehicle to confirm the section boundary (i.e. Figure 5 The distance between the road boundary) Figure 5 The relative distance between the cooperative vehicle and the road segment boundary is the emergency lane (i.e. Figure 5 When the width of the emergency lane in the congested road section is greater than that of the emergency lane in the congested road section, it is determined that the cooperative vehicle is traveling in the rightmost lane of the congested road section, and the driving image is analyzed to obtain the recorded vehicle recorded in the driving image, and the relative position of the recorded vehicle and the cooperative vehicle (i.e. Figure 5 The relative positions 1, 2, 3 and 4 in the above-mentioned recording vehicle are used to determine the current position of the recording vehicle based on the relative positions, and whether the recording vehicle occupies the emergency lane is determined based on the current position of the recording vehicle. Figure 5 As shown, when the relative position of the recorded vehicle is at the preset relative position of the cooperative vehicle (i.e. Figure 5 When the right relative position in the image is recorded, it can be determined that the recorded vehicle occupies the emergency lane.

[0074] This embodiment also provides a first embodiment of an emergency lane abnormal occupancy identification device, please refer to Figure 6 , Figure 6 The diagram of the emergency lane abnormal occupation recognition device provided in this embodiment includes: A starting point identification module is used to select a vehicle to be identified from the starting point driving video shot by a camera at the starting point of the congested road section when a congested road section is detected; The end point recognition module is used to determine the end point driving video captured by the camera at the end point when the vehicle to be identified passes through the camera at the end point of the congested road section; A data acquisition module, used to determine the reference driving data of the reference vehicle and the to-be-identified driving data of the to-be-identified vehicle based on the to-be-identified vehicle, the starting point driving video and the end point driving video; An occupancy identification module, used for identifying abnormal occupancy of the emergency lane of the vehicle to be identified based on the reference driving data and the driving data to be identified; The data acquisition module is further used to determine the calibrated time point when the vehicle to be identified passes the starting point of the congested road section based on the vehicle to be identified and the starting point driving video; determine the reference vehicle according to the starting point driving video and the calibrated time point; determine the driving data of the vehicle to be identified based on the vehicle to be identified, the starting point driving video and the end point driving video; determine the reference driving data of the reference vehicle according to the reference vehicle, the starting point driving video and the end point driving video; The data acquisition module is also used to determine the remaining vehicles based on the starting point driving video and the calibrated time point; compare the vehicle appearance of the remaining vehicles with the vehicle appearance of the vehicle to be identified for similarity; and screen and obtain a reference vehicle from the remaining vehicles based on the similarity comparison result; the data acquisition module is also used to obtain the entry and exit driving videos shot by the camera at the service station in the congested road section; obtain the reference temporary stop duration of the reference vehicle based on the entry and exit driving videos, and obtain the reference total driving duration of the reference vehicle based on the reference driving data; obtain the reference driving duration of the reference vehicle according to the reference total driving duration and the reference temporary stop duration; obtain the temporary stop duration to be identified of the vehicle to be identified based on the entry and exit driving videos, and obtain the total driving duration to be identified of the vehicle to be identified based on the driving data to be identified; obtain the driving duration to be identified of the reference vehicle according to the total driving duration to be identified and the temporary stop duration to be identified.

[0075] Based on the above-mentioned first embodiment of the neural network model deployment device of the present application, a second embodiment of the neural network model deployment device of the present application is proposed.

[0076] In this embodiment, the proportion recognition module is further used to obtain a reference driving duration of the reference vehicle according to the reference driving data, and obtain a driving duration threshold according to the reference driving duration; Obtaining a driving time of the vehicle to be identified based on the driving data to be identified, and comparing the driving time to be identified with the driving time threshold; If the driving time of the vehicle to be identified reaches the driving time threshold, it is determined that the vehicle to be identified abnormally occupies the emergency lane; The occupancy recognition module is further used to determine that the vehicle to be identified does not occupy the emergency lane if the driving time of the vehicle to be identified does not reach the driving time threshold; select a cooperative vehicle from the starting driving video based on the vehicle to be identified, and obtain the driving image of the cooperative vehicle when the cooperative vehicle arrives at a preset position in the congested road section; and identify abnormal occupancy of the emergency lane for the recorded vehicle recorded in the driving image; The occupancy identification module is also used to obtain the standard driving speed of the vehicle to be identified from the driving data to be identified, and obtain the collaborative driving duration of the collaborative vehicle based on the starting point driving video; obtain the current vehicle position of the collaborative vehicle based on the standard driving speed and the collaborative driving duration; and determine whether the collaborative vehicle has arrived at a preset position in the congested road section based on the current vehicle position.

[0077] The emergency lane abnormal occupation identification device provided in this embodiment, it should be noted that the above-mentioned slicing module includes a video recording module and an audio recording module. The use of the emergency lane abnormal occupation identification method in the above-mentioned embodiment can solve the problem that the prior art cannot identify the abnormal occupation of the emergency lane on the camera-free section between two cameras in a congested section. Compared with the prior art, the beneficial effects of the emergency lane abnormal occupation identification device provided in this embodiment are the same as the beneficial effects of the emergency lane abnormal occupation identification method provided in the above-mentioned embodiment, and the other technical features of the emergency lane abnormal occupation identification device are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0078] The present embodiment provides an emergency lane abnormal occupancy identification device, the emergency lane abnormal occupancy identification device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the emergency lane abnormal occupancy identification method in the above-mentioned embodiment one.

[0079] Reference below Figure 7 , Figure 7The structure diagram of the emergency lane abnormal occupation identification device suitable for implementing the present embodiment. The emergency lane abnormal occupation identification device in the present application embodiment may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 7 The emergency lane abnormal occupancy identification device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0080] like Figure 7 As shown, the emergency lane abnormal occupation recognition device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the emergency lane abnormal occupation recognition device are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the emergency lane abnormal occupation identification device to communicate wirelessly or wired with other devices to exchange data. Although the emergency lane abnormal occupation identification device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or provided instead.

[0081] In particular, according to the present embodiment, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the present embodiment includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through a communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present embodiment are executed.

[0082] The emergency lane abnormal occupation identification device provided in this embodiment adopts the emergency lane abnormal occupation identification method in the above embodiment, which can solve the problem that the prior art cannot identify the abnormal occupation of the emergency lane on the camera-free section between two cameras in the congested section. Compared with the prior art, the beneficial effects of the emergency lane abnormal occupation identification device provided in this embodiment are the same as the beneficial effects of the emergency lane abnormal occupation identification method provided in the above embodiment, and other technical features in the emergency lane abnormal occupation identification device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0083] It should be understood that the various parts disclosed in this embodiment can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0084] The above is only a specific implementation of this embodiment, but the protection scope of this embodiment is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in this embodiment, which should be included in the protection scope of this embodiment. Therefore, the protection scope of this embodiment should be based on the protection scope of the claims.

[0085] This embodiment provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the method for identifying abnormal occupation of the emergency lane in the above-mentioned embodiment.

[0086] The computer-readable storage medium provided in this embodiment may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0087] The computer-readable storage medium may be included in the emergency lane abnormal occupation recognition device; or may exist independently without being assembled into the emergency lane abnormal occupation recognition device.

[0088] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the emergency lane abnormal occupation identification device, the emergency lane abnormal occupation identification device performs abnormal emergency lane occupation identification.

[0089] The computer program code for performing the operation of the present embodiment can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Small talk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0090] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present embodiment. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0091] The modules involved in the description of this embodiment may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0092] The readable storage medium provided in this embodiment is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned method for identifying abnormal occupation of emergency lanes, and is intended to solve the problem that the prior art cannot identify abnormal occupation of emergency lanes on a road section without cameras between two cameras on a congested road section. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this embodiment are the same as the beneficial effects of the method for identifying abnormal occupation of emergency lanes provided in the above-mentioned embodiment, and are not described in detail here.

[0093] This embodiment also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for identifying abnormal occupation of an emergency lane.

[0094] The computer program product provided in this embodiment can solve the problem that the prior art cannot identify abnormal occupation of the emergency lane on the camera-free section between two cameras on the congested road section. Compared with the prior art, the beneficial effects of the computer program product provided in this embodiment are the same as the beneficial effects of the method for identifying abnormal occupation of the emergency lane provided in the above embodiment, which will not be described in detail here.

[0095] The above descriptions are only some embodiments, and are not intended to limit the patent scope of this embodiment. All equivalent structural changes made using the contents of the specification and drawings of this application under the technical concept of this application, or directly / indirectly applied in other related technical fields are included in the patent protection scope of this application.

Claims

1. A method for identifying abnormal occupancy of an emergency lane, characterized in that: The method comprises: When a congested road section is detected, a vehicle to be identified is selected from the starting point driving video captured by a camera at the starting point of the congested road section; Determine the terminal driving video captured by the terminal camera when the vehicle to be identified passes through the terminal camera of the congested road section; Determine reference driving data of a reference vehicle and driving data to be identified of the vehicle to be identified based on the vehicle to be identified, the starting point driving video, and the end point driving video; Abnormal occupation of the emergency lane is identified for the vehicle to be identified based on the reference driving data and the driving data to be identified.

2. The method according to claim 1, characterized in that The step of determining the reference driving data of the reference vehicle and the driving data to be identified of the vehicle to be identified based on the vehicle to be identified, the starting point driving video and the end point driving video comprises: Determine, based on the vehicle to be identified and the starting point driving video, a calibration time point when the vehicle to be identified passes through the starting point of the congested road section; Determine a reference vehicle according to the starting point driving video and the calibration time point; Determine the driving data of the vehicle to be identified based on the vehicle to be identified, the starting point driving video and the end point driving video; Reference driving data of the reference vehicle is determined according to the reference vehicle, the starting point driving video and the ending point driving video.

3. The method according to claim 2, characterized in that The step of determining a reference vehicle according to the starting point driving video and the calibration time point comprises: Determine the remaining vehicles based on the starting point driving video and the calibrated time point; Comparing the vehicle appearances of the remaining vehicles with the vehicle appearance of the vehicle to be identified for similarity; A reference vehicle is obtained by screening from the remaining vehicles based on the similarity comparison result.

4. The method according to claim 1, characterized in that The step of identifying abnormal occupation of the emergency lane of the vehicle to be identified based on the reference driving data and the driving data to be identified includes: Obtaining a reference driving duration of the reference vehicle according to the reference driving data, and obtaining a driving duration threshold according to the reference driving duration; Obtaining a driving time of the vehicle to be identified based on the driving data to be identified, and comparing the driving time to be identified with the driving time threshold; If the driving time length of the vehicle to be identified reaches the driving time length threshold, it is determined that the vehicle to be identified abnormally occupies the emergency lane.

5. The method according to claim 4, characterized in that After the step of comparing the driving duration to be identified with the driving duration threshold, the method further includes: If the driving time of the vehicle to be identified does not reach the driving time threshold, it is determined that the vehicle to be identified does not occupy the emergency lane; Selecting a cooperative vehicle from the starting point driving video based on the vehicle to be identified, and acquiring a driving image of the cooperative vehicle when the cooperative vehicle arrives at a preset position in the congested road section; Abnormal occupation of the emergency lane is identified for the recorded vehicle recorded in the driving image.

6. The method according to claim 5, characterized in that Before the step of acquiring the driving image of the cooperative vehicle when the cooperative vehicle arrives at the preset position in the congested road section, the method further includes: Acquire the standard driving speed of the vehicle to be identified from the driving data to be identified, and acquire the cooperative driving duration of the cooperative vehicle based on the starting point driving video; Acquire the current vehicle position of the cooperative vehicle based on the standard driving speed and the cooperative driving duration; Based on the current vehicle position, it is determined whether the cooperative vehicle has arrived at a preset position in the congested road section.

7. The method according to claim 4, characterized in that The step of obtaining a reference driving duration of the reference vehicle according to the reference driving data comprises: Obtaining the entrance and exit driving video captured by the camera at the service station in the congested road section; Obtaining a reference temporary stop duration of the reference vehicle based on the import and export driving video, and obtaining a reference total driving duration of the reference vehicle based on the reference driving data; Obtaining a reference driving time of the reference vehicle according to the reference total driving time and the reference temporary stop time; The step of obtaining the driving time of the vehicle to be identified based on the driving data to be identified includes: Obtaining the temporary stop time of the vehicle to be identified based on the entry and exit driving video, and obtaining the total driving time of the vehicle to be identified based on the driving data to be identified; The driving time to be identified of the reference vehicle is obtained according to the total driving time to be identified and the temporary stop time to be identified.

8. A device for identifying abnormal occupation of an emergency lane, characterized in that: The device comprises: A starting point identification module is used to select a vehicle to be identified from the starting point driving video shot by a camera at the starting point of the congested road section when a congested road section is detected; The end point recognition module is used to determine the end point driving video captured by the camera at the end point when the vehicle to be identified passes through the camera at the end point of the congested road section; A data acquisition module, used to determine the reference driving data of the reference vehicle and the to-be-identified driving data of the to-be-identified vehicle based on the to-be-identified vehicle, the starting point driving video and the end point driving video; The occupancy identification module is used to identify abnormal occupancy of the emergency lane of the vehicle to be identified based on the reference driving data and the driving data to be identified.

9. An emergency lane abnormal occupancy recognition device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the method for identifying abnormal occupation of an emergency lane as claimed in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the method for identifying abnormal occupation of an emergency lane as described in any one of claims 1 to 7 are implemented.

Images