Vehicle management method and system based on intelligent high-speed rail

Abstract

The invention provides a vehicle management method and system based on an intelligent high-speed rail, and the method comprises the steps: collecting a target image corresponding to a vehicle entering a station in real time through a first camera when the first camera located in a station entering region detects the vehicle entering the station in real time, and judging whether the vehicle entering the station is a small bus or not in real time according to the target image; if yes, collecting a target license plate corresponding to the small passenger car in the target image in real time, and judging whether the small passenger car is a normal operation vehicle or not in real time according to the target license plate based on a preset rule; if not, a monitoring video corresponding to the small passenger car is collected in real time through a second camera arranged in the passenger receiving area, and whether the small passenger car has an illegal behavior or not is judged in real time according to the monitoring video; and if the violation behavior of the small passenger car is judged in real time according to the monitoring video, corresponding alarm information is immediately sent out in the passenger receiving area. According to the invention, the management of online car-hailing can be effectively completed, and the working efficiency is correspondingly and greatly improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a vehicle management method and system based on smart high-speed rail. Background Art

[0002] With the advancement of technology and the rapid development of the times, online ride-hailing has become popular in people's daily lives, providing people with more options for travel and correspondingly improving people's travel efficiency.

[0003] Among them, due to the large flow of passengers at the existing high-speed rail stations, the existing online car-hailing drivers will choose to pick up passengers at the high-speed rail stations. Specifically, the existing online car-hailing drivers need to have the corresponding certificates before they can carry out subsequent operations. Therefore, it is necessary to manage the online car-hailing vehicles entering the high-speed rail stations to prevent illegal pickup of passengers.

[0004] Furthermore, in the process of managing online ride-hailing vehicles, most of the existing technologies will install cameras at the entrance of the high-speed railway station, and use the cameras to collect images of vehicles entering the high-speed railway station in real time, and directly judge whether the vehicle is qualified to pick up passengers based on the images of the vehicles. However, since this management method is based on relatively single factors, it is prone to missed judgments and misjudgments, resulting in low vehicle management accuracy and reduced vehicle management efficiency. Summary of the invention

[0005] Based on this, the purpose of the present invention is to provide a vehicle management method and system based on smart high-speed rail to solve the problem that the existing technology is based on relatively single factors in the process of managing vehicles, and is prone to missed judgments and misjudgments.

[0006] The first aspect of the embodiment of the present invention proposes:

[0007] A vehicle management method based on smart high-speed rail, wherein the method is applied to a high-speed rail station, wherein the high-speed rail station includes an entry area and a passenger pick-up area, and the method includes:

[0008] When the first camera located in the station entrance area detects an incoming vehicle in real time, the first camera collects a target image corresponding to the incoming vehicle in real time, and determines in real time based on the target image whether the incoming vehicle is a small passenger car, which includes a sedan and an off-road vehicle;

[0009] If it is determined in real time based on the target image that the incoming vehicle is a small passenger car, a target license plate corresponding to the small passenger car is collected in real time from the target image, and based on a preset rule, it is determined in real time based on the target license plate whether the small passenger car is a normal operating vehicle;

[0010] If it is determined in real time based on the preset rules and the target license plate that the small passenger car is not a normal operating vehicle, a monitoring video corresponding to the small passenger car is collected in real time by a second camera arranged in the passenger pickup area, and it is determined in real time based on the monitoring video whether the small passenger car has any violation;

[0011] If it is determined in real time based on the monitoring video that the small passenger car has violated the regulations, a corresponding alarm message will be immediately issued in the passenger pickup area, and the alarm message includes sound information and text information.

[0012] The beneficial effect of the present invention is that by collecting the target image of the incoming vehicle in real time through the first camera, a corresponding screening can be completed, so as to screen out the small passenger cars that need further judgment in real time. Based on this, the target license plate of the current small passenger car can be further detected according to the target image, and it can be further judged whether it is a normal operating vehicle, that is, whether it is an online-hailing car. Specifically, if so, no subsequent processing is performed; if not, it is necessary to further judge whether there is any violation, and after judging that a violation has occurred, an alarm message can be issued in time, so that the management of online-hailing cars inside the high-speed rail station can be completed quickly and effectively, thereby correspondingly improving work efficiency.

[0013] Furthermore, the step of determining in real time whether the small passenger car is a normal operating vehicle based on the target license plate based on a preset rule includes:

[0014] When the target license plate is acquired in real time, the binding information corresponding to the target license plate is matched in real time in the preset vehicle database;

[0015] Extracting the owner information corresponding to the small passenger car in real time from the binding information, and extracting the owner's facial image corresponding to the small passenger car in real time from the owner information;

[0016] Whether the small passenger car is a normal operating vehicle is determined in real time based on the vehicle owner's facial image and the target image.

[0017] Furthermore, the step of determining in real time whether the small passenger car is a normal operating vehicle based on the vehicle owner's facial image and the target image comprises:

[0018] The target image is fully scanned to detect the real-time face image of the driver's seat of the small passenger car, and a two-dimensional image space is created in real time through a preset program, and a reference plane is correspondingly created in the two-dimensional image space;

[0019] Overlaying the vehicle owner's facial image and the real-time facial image on the reference plane, and calculating the similarity between the vehicle owner's facial image and the real-time facial image in real time based on the reference plane;

[0020] Determine in real time whether the calculated similarity is greater than a preset similarity threshold;

[0021] If it is determined in real time that the calculated similarity is greater than the preset similarity threshold, it is determined that the small passenger car is driven by the owner, and it is determined in real time in the preset vehicle database whether there is operating certificate information corresponding to the owner;

[0022] If it is determined in real time in the preset vehicle database that there is operating certificate information corresponding to the vehicle owner, then the small passenger car is correspondingly determined to be a normal operating vehicle.

[0023] Furthermore, the step of calculating the similarity between the vehicle owner's face image and the real-time face image in real time based on the reference plane includes:

[0024] In the reference plane, a first facial feature included in the face image of the vehicle owner is detected in real time, and a second facial feature included in the real-time face image is detected in real time;

[0025] The first facial feature and the second facial feature are highlighted, and a first feature outline corresponding to the first facial feature and a second feature outline corresponding to the second facial feature are depicted accordingly;

[0026] The degree of overlap between the first characteristic contour and the second characteristic contour is calculated in real time, and the degree of overlap is set to correspond to the similarity between the vehicle owner's face image and the real-time face image, and the degree of overlap is unique.

[0027] Furthermore, the step of determining in real time based on the monitoring video whether the small passenger car has violated the regulations includes:

[0028] When the monitoring video is acquired in real time, the start time and the end time corresponding to the monitoring video are detected in real time;

[0029] Creating a corresponding target time axis in real time according to the start time and the end time, wherein the target time axis includes a number of moments;

[0030] The target image frames corresponding to each of the moments are detected in the monitoring video, and it is determined in real time based on the target time axis and the target image frames whether the small passenger car has committed any violation.

[0031] Furthermore, the step of determining in real time according to the target time axis and the target image frame whether the small passenger car has violated the regulations comprises:

[0032] According to the sequence of the target time axis, each target image frame is analyzed and processed in turn to detect the parking location of the small passenger car in the passenger pick-up area in real time;

[0033] The corresponding violation signs contained in the passenger pickup area are detected in real time, and it is determined in real time whether the small passenger car has committed any violation according to the parking location and the violation signs.

[0034] Furthermore, the step of determining in real time whether the small passenger car has committed any violation according to the parking location and the violation mark comprises:

[0035] Determine in real time whether the parking location of the small passenger car is within the management scope of the violation sign;

[0036] If it is determined in real time that the parking location of the small passenger car is not within the management scope of the violation sign, then determining in real time whether the small passenger car is picking up passengers at the parking location;

[0037] If it is determined in real time that the small passenger car is picking up passengers at the parking location, it is determined that the small passenger car has violated the regulations, and the parking location is unique.

[0038] The second aspect of the embodiment of the present invention proposes:

[0039] A vehicle management system based on smart high-speed rail, wherein the system is applied to a high-speed rail station, wherein the high-speed rail station includes an entry area and a passenger pick-up area, and the system includes:

[0040] A collection module, for collecting a target image corresponding to the incoming vehicle in real time through the first camera when the first camera located in the station entry area detects an incoming vehicle in real time, and judging in real time whether the incoming vehicle is a small passenger car according to the target image, wherein the small passenger car includes a sedan and an off-road vehicle;

[0041] A first judgment module is used for, if it is judged in real time according to the target image that the incoming vehicle is a small passenger car, collecting a target license plate corresponding to the small passenger car in the target image in real time, and judging in real time whether the small passenger car is a normal operating vehicle according to the target license plate based on a preset rule;

[0042] A second judgment module is used for, if it is determined in real time based on the preset rules according to the target license plate that the small passenger car is not a normal operating vehicle, to collect a monitoring video corresponding to the small passenger car in real time through a second camera arranged in the passenger pickup area, and to judge in real time based on the monitoring video whether the small passenger car has violated the regulations;

[0043] The prompt module is used to immediately issue a corresponding alarm message in the passenger pickup area if it is determined in real time based on the monitoring video that the small passenger car has violated the regulations. The alarm message includes sound information and text information.

[0044] Furthermore, the first determination module is specifically used for:

[0045] When the target license plate is acquired in real time, the binding information corresponding to the target license plate is matched in real time in the preset vehicle database;

[0046] Extracting the owner information corresponding to the small passenger car in real time from the binding information, and extracting the owner's facial image corresponding to the small passenger car in real time from the owner information;

[0047] Whether the small passenger car is a normal operating vehicle is determined in real time based on the vehicle owner's facial image and the target image.

[0048] Furthermore, the first determination module is specifically used for:

[0049] The target image is fully scanned to detect the real-time face image of the driver's seat of the small passenger car, and a two-dimensional image space is created in real time through a preset program, and a reference plane is correspondingly created in the two-dimensional image space;

[0050] Overlaying the vehicle owner's facial image and the real-time facial image on the reference plane, and calculating the similarity between the vehicle owner's facial image and the real-time facial image in real time based on the reference plane;

[0051] Determine in real time whether the calculated similarity is greater than a preset similarity threshold;

[0052] If it is determined in real time that the calculated similarity is greater than the preset similarity threshold, it is determined that the small passenger car is driven by the owner, and it is determined in real time in the preset vehicle database whether there is operating certificate information corresponding to the owner;

[0053] If it is determined in real time in the preset vehicle database that there is operating certificate information corresponding to the vehicle owner, then the small passenger car is correspondingly determined to be a normal operating vehicle.

[0054] Furthermore, the first determination module is specifically used for:

[0055] In the reference plane, a first facial feature included in the face image of the vehicle owner is detected in real time, and a second facial feature included in the real-time face image is detected in real time;

[0056] The first facial feature and the second facial feature are highlighted, and a first feature outline corresponding to the first facial feature and a second feature outline corresponding to the second facial feature are depicted accordingly;

[0057] The degree of overlap between the first characteristic contour and the second characteristic contour is calculated in real time, and the degree of overlap is set to correspond to the similarity between the vehicle owner's face image and the real-time face image, and the degree of overlap is unique.

[0058] Furthermore, the second judgment module is specifically used for:

[0059] When the monitoring video is acquired in real time, the start time and the end time corresponding to the monitoring video are detected in real time;

[0060] Creating a corresponding target time axis in real time according to the start time and the end time, wherein the target time axis includes a number of moments;

[0061] The target image frames corresponding to each of the moments are detected in the monitoring video, and it is determined in real time based on the target time axis and the target image frames whether the small passenger car has committed any violation.

[0062] Furthermore, the second judgment module is specifically used for:

[0063] According to the sequence of the target time axis, each target image frame is analyzed and processed in turn to detect the parking location of the small passenger car in the passenger pick-up area in real time;

[0064] The corresponding violation signs contained in the passenger pickup area are detected in real time, and it is determined in real time whether the small passenger car has committed any violation according to the parking location and the violation signs.

[0065] Furthermore, the second judgment module is specifically used for:

[0066] Determine in real time whether the parking location of the small passenger car is within the management scope of the violation sign;

[0067] If it is determined in real time that the parking location of the small passenger car is not within the management scope of the violation sign, then determining in real time whether the small passenger car is picking up passengers at the parking location;

[0068] If it is determined in real time that the small passenger car is picking up passengers at the parking location, it is determined that the small passenger car has violated the regulations, and the parking location is unique.

[0069] The third aspect of the embodiment of the present invention proposes:

[0070] A computer comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the vehicle management method based on the smart high-speed rail as described above is implemented.

[0071] The fourth aspect of the embodiments of the present invention proposes:

[0072] A readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the vehicle management method based on the smart high-speed rail as described above.

[0073] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 A flow chart of a vehicle management method based on smart high-speed rail provided in the first embodiment of the present invention;

[0075] Figure 2 This is a structural block diagram of a vehicle management system based on smart high-speed rail provided in the third embodiment of the present invention.

[0076] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0077] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0078] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0079] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0080] See also Figure 1 , shown is a vehicle management method based on smart high-speed rail provided by the first embodiment of the present invention. The vehicle management method based on smart high-speed rail provided in this embodiment can quickly and effectively complete the management of vehicles inside the high-speed rail station, thereby correspondingly improving work efficiency.

[0081] Specifically, this embodiment provides:

[0082] A vehicle management method based on smart high-speed rail is applied to a high-speed rail station, wherein the high-speed rail station includes an entry area and a passenger pick-up area, and the method includes:

[0083] Step S10, when the first camera located in the station entry area detects an incoming vehicle in real time, the first camera collects a target image corresponding to the incoming vehicle in real time, and determines in real time based on the target image whether the incoming vehicle is a small passenger car, wherein the small passenger car includes a sedan and an off-road vehicle;

[0084] Step S20, if it is determined in real time according to the target image that the incoming vehicle is a small passenger car, a target license plate corresponding to the small passenger car is collected in real time in the target image, and based on a preset rule, it is determined in real time according to the target license plate whether the small passenger car is a normal operating vehicle;

[0085] Step S30, if it is determined in real time based on the preset rule and the target license plate that the small passenger car is not a normal operating vehicle, a monitoring video corresponding to the small passenger car is collected in real time by a second camera arranged in the passenger pickup area, and it is determined in real time based on the monitoring video whether the small passenger car has any violation;

[0086] Step S40: If it is determined in real time based on the monitoring video that the small passenger car has violated the regulations, a corresponding alarm message is immediately issued in the passenger pickup area, and the alarm message includes sound information and text information.

[0087] Specifically, in this embodiment, it should be noted that in order to quickly and effectively complete the management of vehicles inside the high-speed railway station, in order to eliminate the phenomenon of vehicle violations, it is necessary to obtain the information corresponding to each vehicle in real time. Since there are many vehicles circulating in the high-speed railway station every day, in order to effectively reduce the amount of data processing, it is necessary to perform corresponding screening processing. Preferably, the present invention will pre-set the corresponding first camera and second camera in the entrance area and the passenger pick-up area of ​​the high-speed railway station, and the first camera and the second camera are connected to the server arranged in the background. Among them, the image of each vehicle entering the high-speed railway station can be collected in real time through the above-mentioned first camera, that is, the required target image, and specifically, the target image is the front image of each vehicle. Based on this, the above-mentioned server can further make an initial judgment based on the target image, that is, first judge whether the vehicle currently entering the high-speed railway station is a small passenger car, wherein it should be pointed out that the vehicle management method provided by the present invention is only for existing online car-hailing, and the existing online car-hailing is a small passenger car. Based on this, the present invention only needs to judge whether the vehicle entering the high-speed railway station is a small passenger car in real time, and it can judge whether it is an online car-hailing. Specifically, if it is detected that it is a small passenger car, subsequent processing is required. Correspondingly, if it is detected that it is not a small passenger car, it is determined that it is not an online-hailing car, and no subsequent identification and processing are required. This allows for effective screening of vehicles entering the high-speed rail station for subsequent processing.

[0088] Furthermore, after the above steps determine that the incoming vehicle is a small passenger car, subsequent tracking processing will be performed. Preferably, the present invention will first collect the target license plate of the current small passenger car, and can determine in real time according to pre-set rules whether the current small passenger car is a normal operating vehicle, that is, whether it is a vehicle with passenger-carrying qualifications. Specifically, if so, no subsequent processing is required, that is, the current incoming vehicle can reasonably pick up passengers. Correspondingly, if not, it can be explained that the current small passenger car is not a normal operating vehicle, that is, it cannot pick up passengers. Based on this, further tracking processing is required. Preferably, after the above-mentioned incoming vehicle enters the above-mentioned passenger pickup area, the current incoming vehicle will be monitored in real time, and a corresponding monitoring video can be generated. Based on this, it can be finally determined in real time according to the monitoring video whether the current small passenger car has any violations, that is, whether it has violated traffic signs and whether it has illegally picked up passengers. Specifically, if yes, a corresponding alarm message will be immediately issued in the current passenger pickup area and corresponding management measures will be taken. Correspondingly, if no, the current small passenger car will not be processed, thereby enabling the management of vehicles inside the high-speed railway station to be completed quickly and effectively, thereby correspondingly improving work efficiency.

[0089] Second embodiment

[0090] Furthermore, the step of determining in real time whether the small passenger car is a normal operating vehicle based on the target license plate based on a preset rule includes:

[0091] When the target license plate is acquired in real time, the binding information corresponding to the target license plate is matched in real time in the preset vehicle database;

[0092] Extracting the owner information corresponding to the small passenger car in real time from the binding information, and extracting the owner's facial image corresponding to the small passenger car in real time from the owner information;

[0093] Whether the small passenger car is a normal operating vehicle is determined in real time based on the vehicle owner's facial image and the target image.

[0094] Furthermore, the step of determining in real time whether the small passenger car is a normal operating vehicle based on the vehicle owner's facial image and the target image comprises:

[0095] The target image is fully scanned to detect the real-time face image of the driver's seat of the small passenger car, and a two-dimensional image space is created in real time through a preset program, and a reference plane is correspondingly created in the two-dimensional image space;

[0096] Overlaying the vehicle owner's facial image and the real-time facial image on the reference plane, and calculating the similarity between the vehicle owner's facial image and the real-time facial image in real time based on the reference plane;

[0097] Determine in real time whether the calculated similarity is greater than a preset similarity threshold;

[0098] If it is determined in real time that the calculated similarity is greater than the preset similarity threshold, it is determined that the small passenger car is driven by the owner, and it is determined in real time in the preset vehicle database whether there is operating certificate information corresponding to the owner;

[0099] If it is determined in real time in the preset vehicle database that there is operating certificate information corresponding to the vehicle owner, then the small passenger car is correspondingly determined to be a normal operating vehicle.

[0100] Furthermore, the step of calculating the similarity between the vehicle owner's face image and the real-time face image in real time based on the reference plane includes:

[0101] In the reference plane, a first facial feature included in the face image of the vehicle owner is detected in real time, and a second facial feature included in the real-time face image is detected in real time;

[0102] The first facial feature and the second facial feature are highlighted, and a first feature outline corresponding to the first facial feature and a second feature outline corresponding to the second facial feature are depicted accordingly;

[0103] The degree of overlap between the first characteristic contour and the second characteristic contour is calculated in real time, and the degree of overlap is set to correspond to the similarity between the vehicle owner's face image and the real-time face image, and the degree of overlap is unique.

[0104] Furthermore, the step of determining in real time based on the monitoring video whether the small passenger car has violated the regulations includes:

[0105] When the monitoring video is acquired in real time, the start time and the end time corresponding to the monitoring video are detected in real time;

[0106] Creating a corresponding target time axis in real time according to the start time and the end time, wherein the target time axis includes a number of moments;

[0107] The target image frames corresponding to each of the moments are detected in the monitoring video, and it is determined in real time based on the target time axis and the target image frames whether the small passenger car has committed any violation.

[0108] Furthermore, the step of determining in real time according to the target time axis and the target image frame whether the small passenger car has violated the regulations comprises:

[0109] According to the sequence of the target time axis, each target image frame is analyzed and processed in turn to detect the parking location of the small passenger car in the passenger pick-up area in real time;

[0110] The corresponding violation signs contained in the passenger pickup area are detected in real time, and it is determined in real time whether the small passenger car has committed any violation according to the parking location and the violation signs.

[0111] Furthermore, the step of determining in real time whether the small passenger car has committed any violation according to the parking location and the violation mark comprises:

[0112] Determine in real time whether the parking location of the small passenger car is within the management scope of the violation sign;

[0113] If it is determined in real time that the parking location of the small passenger car is not within the management scope of the violation sign, then determining in real time whether the small passenger car is picking up passengers at the parking location;

[0114] If it is determined in real time that the small passenger car is picking up passengers at the parking location, it is determined that the small passenger car has violated the regulations, and the parking location is unique.

[0115] In addition, in the present embodiment, it is also necessary to explain that after the required target license plate is detected in real time through the above steps, a deeper judgment is required at this time. Preferably, in order to be able to quickly and simply determine whether the current small passenger car is a normal operating vehicle, so as to shorten the data processing time accordingly, preferably, the present invention will further call out a pre-set vehicle database, and be able to match the binding information corresponding to the current target license plate in real time through the vehicle database, that is, the owner information bound to the current target license plate. Among them, it should be pointed out that the existing car owners need to store the owner's facial image in the process of binding the vehicle. Based on this, the present invention can further extract the facial image corresponding to the current small passenger car from the current owner information. The facial image of the owner of the small passenger car corresponding to the small passenger car can be obtained based on this. Further subsequent judgments can be made based on this. Specifically, in order to objectively and accurately complete the subsequent judgments, the current target image will be fully scanned first, and the real-time facial image of the driver of the current small passenger car can be detected from the current target image in real time, that is, the facial image of the driver currently driving the current small passenger car. Based on this, in order to facilitate subsequent comparison, a two-dimensional image space will be further created through the existing three-dimensional software such as UG and Solidworks. At the same time, a reference surface is further created inside the current two-dimensional image space. Based on this, in the actual comparison process, the current owner's facial image can be directly compared with the current The real-time facial image is overlapped on the current reference plane. At the same time, the current reference plane is used as a calculation platform to calculate the similarity between the current vehicle owner's facial image and the current real-time facial image in real time. It should be noted that in the process of real-time calculation of the similarity, the present invention will respectively detect the first facial features corresponding to the current vehicle owner's facial image. Similarly, the second facial features corresponding to the current real-time facial image are detected in real time. Based on this, the corresponding highlighting is performed. After the highlighting, the first feature contour corresponding to the current first facial feature and the second feature contour corresponding to the current second facial feature can be depicted in real time in the above-mentioned reference plane. It should be noted that since the feature contours are composed of some lines, and the lines There are corresponding entities. Based on this, the similarity between the above-mentioned owner's face image and the above-mentioned real-time face image can be calculated in real time according to the overlap of the lines between the current first feature contour and the current second feature contour, and it can be judged in real time whether the calculated similarity is greater than the preset similarity threshold. Specifically, if so, it corresponds to that the two current face images are of the same person. If not, it corresponds to that the two current face images are not of the same person. It should also be pointed out that if it is determined that the two current face images are of the same person, it can be determined that the current small passenger car is driven by the owner, and it will be further determined in real time in the above-mentioned preset vehicle database whether there is operating certificate information corresponding to the current owner. Specifically, if so,If the vehicle is not in normal operation, it can be directly determined as a normal operating vehicle, which is convenient for subsequent processing.

[0116] Furthermore, if it is determined in real time through the above steps that the current small passenger car is not a normal operating vehicle, corresponding supervision and processing are required at this time. If the current small passenger car enters the passenger pick-up area inside the high-speed railway station, corresponding real-time monitoring is required at this time. After obtaining the corresponding monitoring video, in order to be able to objectively and accurately determine whether the current small passenger car has violated the regulations, preferably, the present invention will further detect the start time and end time corresponding to the current monitoring video, and can synchronously create a corresponding target time axis. Similarly, the target time axis contains several corresponding moments. It should be pointed out that since the existing videos are composed of a series of image frames, and each moment has a corresponding image frame, based on this, the present invention will further detect the target image frames corresponding to each current moment in the above monitoring video, based on this, each current target image frame can be directly mapped to the above target time axis. Specifically, in order to shorten the judgment time, each current target image frame will be further analyzed and processed in sequence according to the sequence of the target time axis, so that the actual parking location of the current small passenger car in the above-mentioned passenger pick-up area can be detected. It should be pointed out that the passenger pick-up area inside the existing high-speed railway station is equipped with certain violation signs to facilitate the management of vehicles. Based on this, in order to accurately determine whether the current small passenger car has any violation, it should be pointed out that at this time, it will first be determined whether the parking location of the current small passenger car is within the violation signs inside the above-mentioned passenger pick-up area. It is within the management scope of the recognition, that is, whether the current violation mark is triggered. Specifically, if so, it can be directly determined that the current small passenger car has violated the rules and a corresponding alarm message needs to be issued. Correspondingly, if not, a secondary judgment is required, that is, it is necessary to further determine whether the current small passenger car has picked up passengers at the current parking location. Specifically, if so, it can be directly determined that the current small passenger car has violated the rules. Correspondingly, if not, it can be directly determined that the current small passenger car has not violated the rules. This can quickly and effectively determine whether the online car-hailing vehicle entering the high-speed rail station has violated the rules, thereby improving work efficiency accordingly.

[0117] See also Figure 2 , the third embodiment of the present invention provides:

[0118] A vehicle management system based on smart high-speed rail, wherein the system is applied to a high-speed rail station, wherein the high-speed rail station includes an entry area and a passenger pick-up area, and the system includes:

[0119] A collection module, for collecting a target image corresponding to the incoming vehicle in real time through the first camera when the first camera located in the station entry area detects an incoming vehicle in real time, and judging in real time whether the incoming vehicle is a small passenger car according to the target image, wherein the small passenger car includes a sedan and an off-road vehicle;

[0120] A first judgment module is used for, if it is judged in real time according to the target image that the incoming vehicle is a small passenger car, collecting a target license plate corresponding to the small passenger car in the target image in real time, and judging in real time whether the small passenger car is a normal operating vehicle according to the target license plate based on a preset rule;

[0121] A second judgment module is used for, if it is determined in real time based on the preset rules according to the target license plate that the small passenger car is not a normal operating vehicle, to collect a monitoring video corresponding to the small passenger car in real time through a second camera arranged in the passenger pickup area, and to judge in real time based on the monitoring video whether the small passenger car has violated the regulations;

[0122] The prompt module is used to immediately issue a corresponding alarm message in the passenger pickup area if it is determined in real time based on the monitoring video that the small passenger car has violated the regulations. The alarm message includes sound information and text information.

[0123] Furthermore, the first determination module is specifically used for:

[0124] When the target license plate is acquired in real time, the binding information corresponding to the target license plate is matched in real time in the preset vehicle database;

[0125] Extracting the owner information corresponding to the small passenger car in real time from the binding information, and extracting the owner's facial image corresponding to the small passenger car in real time from the owner information;

[0126] Whether the small passenger car is a normal operating vehicle is determined in real time based on the vehicle owner's facial image and the target image.

[0127] Furthermore, the first determination module is specifically used for:

[0128] The target image is fully scanned to detect the real-time face image of the driver's seat of the small passenger car, and a two-dimensional image space is created in real time through a preset program, and a reference plane is correspondingly created in the two-dimensional image space;

[0129] Overlaying the vehicle owner's facial image and the real-time facial image on the reference plane, and calculating the similarity between the vehicle owner's facial image and the real-time facial image in real time based on the reference plane;

[0130] Determine in real time whether the calculated similarity is greater than a preset similarity threshold;

[0131] If it is determined in real time that the calculated similarity is greater than the preset similarity threshold, it is determined that the small passenger car is driven by the owner, and it is determined in real time in the preset vehicle database whether there is operating certificate information corresponding to the owner;

[0132] If it is determined in real time in the preset vehicle database that there is operating certificate information corresponding to the vehicle owner, then the small passenger car is correspondingly determined to be a normal operating vehicle.

[0133] Furthermore, the first determination module is specifically used for:

[0134] In the reference plane, a first facial feature included in the face image of the vehicle owner is detected in real time, and a second facial feature included in the real-time face image is detected in real time;

[0135] The first facial feature and the second facial feature are highlighted, and a first feature outline corresponding to the first facial feature and a second feature outline corresponding to the second facial feature are depicted accordingly;

[0136] The degree of overlap between the first characteristic contour and the second characteristic contour is calculated in real time, and the degree of overlap is set to correspond to the similarity between the vehicle owner's face image and the real-time face image, and the degree of overlap is unique.

[0137] Furthermore, the second judgment module is specifically used for:

[0138] When the monitoring video is acquired in real time, the start time and the end time corresponding to the monitoring video are detected in real time;

[0139] Creating a corresponding target time axis in real time according to the start time and the end time, wherein the target time axis includes a number of moments;

[0140] The target image frames corresponding to each of the moments are detected in the monitoring video, and it is determined in real time based on the target time axis and the target image frames whether the small passenger car has committed any violation.

[0141] Furthermore, the second judgment module is specifically used for:

[0142] According to the sequence of the target time axis, each target image frame is analyzed and processed in turn to detect the parking location of the small passenger car in the passenger pick-up area in real time;

[0143] The corresponding violation signs contained in the passenger pickup area are detected in real time, and it is determined in real time whether the small passenger car has committed any violation according to the parking location and the violation signs.

[0144] Furthermore, the second judgment module is specifically used for:

[0145] Determine in real time whether the parking location of the small passenger car is within the management scope of the violation sign;

[0146] If it is determined in real time that the parking location of the small passenger car is not within the management scope of the violation sign, then determining in real time whether the small passenger car is picking up passengers at the parking location;

[0147] If it is determined in real time that the small passenger car is picking up passengers at the parking location, it is determined that the small passenger car has violated the regulations, and the parking location is unique.

[0148] The fourth embodiment of the present invention provides a computer, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the vehicle management method based on the smart high-speed rail as described above is implemented.

[0149] The fifth embodiment of the present invention provides a readable storage medium on which a computer program is stored, wherein when the program is executed by a processor, the vehicle management method based on the smart high-speed rail as described above is implemented.

[0150] To sum up, the vehicle management method and system based on smart high-speed rail provided by the above embodiments of the present invention can quickly and effectively complete the management of vehicles inside the high-speed rail station, thereby correspondingly improving work efficiency.

[0151] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0152] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0153] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0154] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0155] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0156] The above-described embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A vehicle management method based on smart high-speed rail, characterized in that: Applied to a high-speed railway station, the high-speed railway station includes an entry area and a passenger reception area, and the method includes: When the first camera located in the station entrance area detects an incoming vehicle in real time, the first camera collects a target image corresponding to the incoming vehicle in real time, and determines in real time based on the target image whether the incoming vehicle is a small passenger car, which includes a sedan and an off-road vehicle; If it is determined in real time based on the target image that the incoming vehicle is a small passenger car, a target license plate corresponding to the small passenger car is collected in real time from the target image, and based on a preset rule, it is determined in real time based on the target license plate whether the small passenger car is a normal operating vehicle; If it is determined in real time based on the preset rules and the target license plate that the small passenger car is not a normal operating vehicle, a monitoring video corresponding to the small passenger car is collected in real time by a second camera arranged in the passenger pickup area, and it is determined in real time based on the monitoring video whether the small passenger car has any violation; If it is determined in real time based on the monitoring video that the small passenger car has violated the regulations, a corresponding alarm message will be immediately issued in the passenger pickup area, and the alarm message includes sound information and text information.

2. The vehicle management method based on smart high-speed rail according to claim 1 is characterized in that: The step of judging in real time whether the small passenger car is a normal operating vehicle based on the target license plate based on a preset rule comprises: When the target license plate is acquired in real time, the binding information corresponding to the target license plate is matched in real time in the preset vehicle database; Extracting the owner information corresponding to the small passenger car in real time from the binding information, and extracting the owner's facial image corresponding to the small passenger car in real time from the owner information; Whether the small passenger car is a normal operating vehicle is determined in real time based on the vehicle owner's facial image and the target image.

3. The vehicle management method based on smart high-speed rail according to claim 2 is characterized in that: The step of determining in real time whether the small passenger car is a normal operating vehicle based on the vehicle owner's facial image and the target image comprises: The target image is fully scanned to detect the real-time face image of the driver's seat of the small passenger car, and a two-dimensional image space is created in real time through a preset program, and a reference plane is correspondingly created in the two-dimensional image space; Overlaying the vehicle owner's facial image and the real-time facial image on the reference plane, and calculating the similarity between the vehicle owner's facial image and the real-time facial image in real time based on the reference plane; Determine in real time whether the calculated similarity is greater than a preset similarity threshold; If it is determined in real time that the calculated similarity is greater than the preset similarity threshold, it is determined that the small passenger car is driven by the owner, and it is determined in real time in the preset vehicle database whether there is operating certificate information corresponding to the owner; If it is determined in real time in the preset vehicle database that there is operating certificate information corresponding to the vehicle owner, then the small passenger car is correspondingly determined to be a normal operating vehicle.

4. The vehicle management method based on smart high-speed rail according to claim 3 is characterized in that: The step of calculating the similarity between the vehicle owner's face image and the real-time face image in real time based on the reference plane comprises: In the reference plane, a first facial feature included in the face image of the vehicle owner is detected in real time, and a second facial feature included in the real-time face image is detected in real time; The first facial feature and the second facial feature are highlighted, and a first feature outline corresponding to the first facial feature and a second feature outline corresponding to the second facial feature are depicted accordingly; The degree of overlap between the first characteristic contour and the second characteristic contour is calculated in real time, and the degree of overlap is set to correspond to the similarity between the vehicle owner's face image and the real-time face image, and the degree of overlap is unique.

5. The vehicle management method based on smart high-speed rail according to claim 1 is characterized in that: The step of determining in real time whether the small passenger car has violated the regulations based on the monitoring video comprises: When the monitoring video is acquired in real time, the start time and the end time corresponding to the monitoring video are detected in real time; Creating a corresponding target time axis in real time according to the start time and the end time, wherein the target time axis includes a number of moments; The target image frames corresponding to each of the moments are detected in the monitoring video, and it is determined in real time based on the target time axis and the target image frames whether the small passenger car has committed any violation.

6. The vehicle management method based on smart high-speed rail according to claim 5 is characterized in that: The step of judging whether the small passenger car has violated the regulations in real time according to the target time axis and the target image frame comprises: According to the sequence of the target time axis, each target image frame is analyzed and processed in turn to detect the parking location of the small passenger car in the passenger pick-up area in real time; The corresponding violation signs contained in the passenger pickup area are detected in real time, and it is determined in real time whether the small passenger car has committed any violation according to the parking location and the violation signs.

7. The vehicle management method based on smart high-speed rail according to claim 6 is characterized in that: The step of determining in real time whether the small passenger car has violated the regulations based on the parking location and the violation mark comprises: Determine in real time whether the parking location of the small passenger car is within the management scope of the violation sign; If it is determined in real time that the parking location of the small passenger car is not within the management scope of the violation sign, then determining in real time whether the small passenger car is picking up passengers at the parking location; If it is determined in real time that the small passenger car is picking up passengers at the parking location, it is determined that the small passenger car has violated the regulations, and the parking location is unique.

8. A vehicle management system based on smart high-speed rail, characterized in that: Applied to a high-speed railway station, the high-speed railway station includes an entry area and a passenger reception area, and the system includes: A collection module, for collecting a target image corresponding to the incoming vehicle in real time through the first camera when the first camera located in the station entry area detects an incoming vehicle in real time, and judging in real time whether the incoming vehicle is a small passenger car according to the target image, wherein the small passenger car includes a sedan and an off-road vehicle; A first judgment module is used for, if it is judged in real time according to the target image that the incoming vehicle is a small passenger car, collecting a target license plate corresponding to the small passenger car in the target image in real time, and judging in real time whether the small passenger car is a normal operating vehicle according to the target license plate based on a preset rule; A second judgment module is used for, if it is determined in real time based on the preset rules according to the target license plate that the small passenger car is not a normal operating vehicle, to collect a monitoring video corresponding to the small passenger car in real time through a second camera arranged in the passenger pickup area, and to judge in real time based on the monitoring video whether the small passenger car has violated the regulations; The prompt module is used to immediately issue a corresponding alarm message in the passenger pickup area if it is determined in real time based on the monitoring video that the small passenger car has violated the regulations. The alarm message includes sound information and text information.

9. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the vehicle management method based on smart high-speed rail as described in any one of claims 1 to 7.

10. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, it implements the vehicle management method based on smart high-speed rail as described in any one of claims 1 to 7.

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