Method, device and equipment for detecting abnormal light of vehicle and medium

Abstract

The invention discloses a vehicle light abnormity detection method, device and equipment and a medium. In the driving process, a first vehicle collects a first light image and a license plate image of a second vehicle; the first vehicle sends the first light image and the license plate image to a server; the server identifies the second vehicle according to the license plate image, and queries a standard light image corresponding to the second vehicle from a pre-established standard database; wherein the standard database is used for storing light images of each vehicle in a normal state; the server compares the first light image with the standard light image; and if it is determined that the first light image is abnormal, the server sends abnormal alarm information to a vehicle owner of the second vehicle. According to the invention, the stability and reliability of light anomaly detection can be effectively improved. The method can be widely applied to the technical field of vehicles.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a method, device, equipment and medium for detecting abnormal vehicle lighting. Background Art

[0002] At present, with the popularization of vehicle intelligent technology, the lighting system has gradually upgraded from traditional halogen lamps and xenon lamps to LED light sources. LED headlights achieve high-brightness lighting through the principle of semiconductor light emission, and have the advantages of low energy consumption, long life, and fast response speed. In terms of hardware structure, multiple groups of independent LED lamp beads are usually connected in parallel to form an array, and lenses or reflective bowls are used to form a standard light pattern. Some models are also equipped with a current monitoring module to detect the working status of the lamp group.

[0003] In the related technology, the health status monitoring of LED headlights mainly relies on two methods: one is to detect whether the total loop current value is abnormal through the current sensor, but when one or more lamp beads fail, the total current change may not reach the alarm threshold; the other is to use the vehicle's own optical sensor to detect the actual illumination, but if the optical sensor itself has power supply abnormalities or sensor failures, it cannot effectively detect the abnormal lighting problem. This technical defect makes some headlights "work with illness" frequently, which is prone to traffic accidents and poses a major safety hazard.

[0004] In summary, the problems existing in related technologies need to be solved urgently. Summary of the invention

[0005] The purpose of this application is to solve one of the technical problems existing in the related art to at least a certain extent.

[0006] To this end, an object of embodiments of the present application is to provide a method, device, equipment and medium for detecting abnormal vehicle lighting.

[0007] In order to achieve the above technical objectives, the technical solutions adopted by the embodiments of the present application include:

[0008] On the one hand, an embodiment of the present application provides a method for detecting abnormal vehicle lighting, the method comprising:

[0009] During driving, the first vehicle collects a first light image and a license plate image of the second vehicle;

[0010] The first vehicle sends the first light image and the license plate image to a server;

[0011] The server identifies the second vehicle according to the license plate image, and queries a pre-established standard database for a standard light image corresponding to the second vehicle; wherein the standard database is used to store light images of each vehicle in a normal state;

[0012] The server compares the first lighting image with the standard lighting image;

[0013] If it is determined that the first lighting image is abnormal, the server sends an abnormal alarm message to the owner of the second vehicle.

[0014] In addition, according to the vehicle lighting abnormality detection method of the above embodiments of the present application, the following additional technical features may also be included:

[0015] Further, in an embodiment of the present application, the first vehicle collects the first lighting image and the license plate image of the second vehicle, including:

[0016] After the first vehicle turns on the mutual assistance detection function, the first lighting image and the license plate image of the second vehicle are collected through the front camera or the rear camera on the first vehicle.

[0017] Further, in an embodiment of the present application, the step of if it is determined that the first lighting image is abnormal, the server sends an abnormal alarm message to the owner of the second vehicle includes:

[0018] If it is determined that the first lighting image is abnormal, the server detects whether the second vehicle has turned on the mutual assistance detection function;

[0019] If it is determined that the second vehicle has turned on the mutual assistance detection function, the server sends an abnormal alarm message to the owner of the second vehicle.

[0020] Further, in an embodiment of the present application, the server compares the first lighting image with the standard lighting image, including:

[0021] The server calculates a first similarity between the first lighting image and the standard lighting image;

[0022] If the first similarity is greater than or equal to a first preset threshold, the server determines that the first lighting image is not abnormal;

[0023] If the first similarity is less than the first preset threshold, the server determines that the first lighting image is abnormal.

[0024] Further, in an embodiment of the present application, the method further includes:

[0025] Before the first vehicle starts, it collects a second lighting image when the headlights are on and a reference image when the headlights are off;

[0026] The first vehicle sends the second lighting image and the reference image to the server;

[0027] The server compares the second lighting image with the reference image;

[0028] If it is determined that the second lighting image is abnormal, the server sends an abnormal alarm message to the owner of the first vehicle.

[0029] Further, in an embodiment of the present application, the server compares the second lighting image with the reference image, including:

[0030] The server calculates a second similarity between the second lighting image and the reference image;

[0031] If the second similarity is less than or equal to a second preset threshold, the server determines that the second lighting image is not abnormal;

[0032] If the second similarity is greater than the second preset threshold, the server determines that the second lighting image is abnormal.

[0033] On the other hand, in an embodiment of the present application, another method for detecting abnormal vehicle lighting is provided, which is applied to the first vehicle. The method includes:

[0034] During driving, collect a first lighting image and a license plate image of the second vehicle;

[0035] Send the first lighting image and the license plate image to the server, so that the server identifies the second vehicle according to the license plate image, queries the standard lighting image corresponding to the second vehicle from a pre-established standard database, and compares the first lighting image with the standard lighting image. If it is determined that the first lighting image is abnormal, an abnormal alarm message is sent to the owner of the second vehicle; wherein, the standard database is used to store the lighting images of each vehicle in a normal state.

[0036] On the other hand, an embodiment of the present application provides a device for detecting abnormal vehicle lighting, which is applied to the first vehicle. The device includes:

[0037] A collection unit, configured to collect a first lighting image and a license plate image of the second vehicle during driving;

[0038] A sending unit, configured to send the first light image and the license plate image to a server, so that the server identifies the second vehicle according to the license plate image, queries a standard light image corresponding to the second vehicle from a pre-established standard database, and compares the first light image with the standard light image. If it is determined that the first light image is abnormal, an abnormal warning message is sent to the owner of the second vehicle; wherein, the standard database is used to store light images of each vehicle in a normal state.

[0039] On the other hand, an embodiment of the present application provides an electronic device, including:

[0040] At least one processor;

[0041] At least one memory, configured to store at least one program;

[0042] When the at least one program is executed by the at least one processor, the at least one processor implements the above-mentioned method for detecting abnormal vehicle lights.

[0043] On the other hand, an embodiment of the present application further provides a computer-readable storage medium, in which a program executable by a processor is stored. The above-mentioned program executable by the processor is used to implement the above-mentioned method for detecting abnormal vehicle lights when executed by the processor.

[0044] The advantages and beneficial effects of the present application will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present application:

[0045] A method, device, equipment and medium for detecting abnormal vehicle lights disclosed in an embodiment of the present application. During driving, a first vehicle collects a first light image and a license plate image of a second vehicle; the first vehicle sends the first light image and the license plate image to a server; the server identifies the second vehicle according to the license plate image, and queries a standard light image corresponding to the second vehicle from a pre-established standard database; wherein, the standard database is used to store light images of each vehicle in a normal state; the server compares the first light image with the standard light image; if it is determined that the first light image is abnormal, the server sends an abnormal warning message to the owner of the second vehicle. The present application can help detect abnormal light matters of other second vehicles through the first vehicle. Compared with the mode of detecting abnormal lights by the vehicle itself, it can effectively improve the stability and reliability of detection, and help the vehicle owner quickly discover abnormal vehicle lights as much as possible, which is beneficial to improving the driving safety of the vehicle. Description of the Drawings

[0046] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following introduces the accompanying drawings of the relevant technical solutions in the embodiments of the present application or the prior art. It should be understood that the accompanying drawings in the following introduction are only for conveniently and clearly presenting some embodiments of the technical solutions in the present application. For those skilled in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0047] Figure 1 Schematic diagram of the implementation environment of a method for detecting abnormal vehicle lights provided in an embodiment of the present application;

[0048] Figure 2 Schematic flow diagram of a method for detecting abnormal vehicle lights provided in an embodiment of the present application;

[0049] Figure 3 Schematic structural diagram of a device for detecting abnormal vehicle lights provided in an embodiment of the present application;

[0050] Figure 4 Schematic structural diagram of an electronic device provided in an embodiment of the present application. Detailed implementation manners

[0051] The following further illustrates the present application in conjunction with the accompanying drawings of the specification and specific embodiments. The described embodiments should not be regarded as limitations on the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present application.

[0052] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments and can be combined with each other without conflict.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0054] Currently, with the popularization of vehicle intelligent technologies, the vehicle lighting system has gradually evolved from traditional halogen lamps and xenon lamps to LED light sources. LED vehicle lights achieve high-brightness lighting through the semiconductor light-emitting principle and have advantages such as low energy consumption, long lifespan, and fast response speed. In terms of hardware structure, multiple groups of independent LED lamp beads are usually connected in parallel to form an array, and are paired with lenses or reflectors to form a standard light pattern. Some vehicle models are also equipped with a current monitoring module to detect the working status of the lamp group.

[0055] In the related technology, the health status monitoring of LED headlights mainly relies on two methods: one is to detect whether the total loop current value is abnormal through the current sensor, but when one or more lamp beads fail, the total current change may not reach the alarm threshold; the other is to use the vehicle's own optical sensor to detect the actual illumination, but if the optical sensor itself has power supply abnormalities or sensor failures, it cannot effectively detect the abnormal lighting problem. This technical defect makes some headlights "work with illness" frequently, which is prone to traffic accidents and poses a major safety hazard.

[0056] In view of this, a method for detecting vehicle lighting anomalies is provided in an embodiment of the present application. During driving, a first vehicle collects a first lighting image and a license plate image of a second vehicle; the first vehicle sends the first lighting image and the license plate image to a server; the server identifies the second vehicle based on the license plate image, and queries the standard lighting image corresponding to the second vehicle from a pre-established standard database; wherein the standard database is used to store lighting images of each vehicle in a normal state; the server compares the first lighting image with the standard lighting image; if it is determined that the first lighting image is abnormal, the server sends an abnormality warning message to the owner of the second vehicle. The present application can help detect lighting anomalies of other second vehicles through the first vehicle. Compared with the mode of detecting lighting anomalies by the vehicle itself, it can effectively improve the stability and reliability of detection, help the owner to quickly discover the lighting anomalies of the vehicle as much as possible, and help improve the driving safety of the vehicle.

[0057] Please refer to Figure 1 , Figure 1 The schematic diagram of the implementation environment of a vehicle lighting abnormality detection method provided in the embodiment of the present application is shown. In the implementation environment, the main software and hardware entities involved include a terminal device 110 and a backend server 120. The terminal device 110 and the backend server 120 are connected in communication.

[0058] Specifically, the vehicle lighting abnormality detection method provided in the embodiment of the present application can be executed based on the data interaction between the terminal device 110 and the background server 120. The terminal device 110 can be a vehicle-mounted terminal, which is set on each vehicle; the background server 120 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0059] A communication connection can be established between the terminal device 110 and the background server 120 through a wireless network or a wired network. The wireless network or the wired network uses standard communication technologies and / or protocols. The network can be set to the Internet or any other network, such as any combination including but not limited to a Local Area Network (LAN), a Metropolitan Area Network (MAN), a Wide Area Network (WAN), a mobile, wired or wireless network, a private network or a virtual private network.

[0060] Of course, it can be understood that Figure 1 the implementation environment in Figure 1 is only some optional application scenarios of the vehicle light abnormality detection method provided in the embodiments of the present application. The actual application is not fixed to

[0061] Next, in combination with the introduction of the foregoing implementation environment, a vehicle light abnormality detection method provided in the embodiments of the present application will be introduced and described.

[0062] Please refer to Figure 2 , Figure 2 which is a schematic diagram of a vehicle light abnormality detection method provided in the embodiments of the present application. The vehicle light abnormality detection method includes but is not limited to:

[0063] Step 210: During driving, the first vehicle collects the first light image and the license plate image of the second vehicle;

[0064] Step 220: The first vehicle sends the first light image and the license plate image to the server;

[0065] Step 230: The server identifies the second vehicle according to the license plate image and queries the standard light image corresponding to the second vehicle from a pre-established standard database; wherein, the standard database is used to store the light images of each vehicle in a normal state;

[0066] Step 240: The server compares the first light image and the standard light image;

[0067] Step 250: If it is determined that the first light image is abnormal, the server sends an abnormal alarm message to the owner of the second vehicle.

[0068] In an embodiment of the present application, a method for detecting abnormal vehicle lights is provided. This method can use a first vehicle to assist in detecting abnormal lighting events of other second vehicles. Compared with the mode of detecting abnormal lights by the vehicle itself, it can effectively improve the stability and reliability of detection, and help the vehicle owner quickly discover abnormal vehicle lights as much as possible, which is beneficial to improving vehicle driving safety.

[0069] The method for detecting abnormal vehicle lights in an embodiment of the present application can be applied to any vehicle, and this method is a multi-terminal collaborative technical solution. Specifically, for example, the method in an embodiment of the present application can be applied to a first vehicle. During driving, the first vehicle can collect relevant image data of other vehicles. In an embodiment of the present application, vehicles other than the first vehicle are denoted as second vehicles. The first vehicle can collect the lighting image and license plate image of the second vehicle, and the lighting image here is denoted as the first lighting image.

[0070] Specifically, in an embodiment of the present application, to implement the collection of the lighting image and license plate image of the second vehicle by the first vehicle, computer vision, sensor technology, communication technology, and data processing algorithms need to be combined. On the first vehicle, a high-resolution camera (such as 1080p or 4K) can be installed, which supports autofocus and low-light enhancement (such as HDR, night vision mode) and can achieve image collection at night or in low-light environments. The first vehicle can collect the taillights and license plate of the second vehicle through the front camera (installed at the front of the first vehicle); or collect the headlights and license plate of the second vehicle through the rear camera (installed at the rear of the first vehicle).

[0071] For the collected images, relevant algorithms can be used to identify and detect regions in the images, and then the processed first lighting image and license plate image can be sent to the server, or directly sent to the server for processing. The present application does not limit this.

[0072] In an embodiment of the present application, for the server, after receiving the license plate image and the first lighting image, it can identify the second vehicle based on the license plate image. It can be understood that a vehicle corresponds to a unique license plate number. Therefore, the identity of the second vehicle can be uniquely determined based on the license plate image. Then, the standard lighting image corresponding to the second vehicle can be queried from a pre-established standard database. In an embodiment of the present application, the standard database is used to store the lighting images of each vehicle in a normal state. Specifically, for example, for various vehicle models, the vehicle manufacturer can pre-collect the lighting images in a normal state, bind them with the vehicle model information and store them to establish the standard database. For the second vehicle, based on the license plate image, the associated vehicle model information can be identified, and thus the standard lighting image corresponding to the second vehicle can be queried from the standard database.

[0073] After obtaining the standard lighting image corresponding to the second vehicle, the standard lighting image and the first lighting image can be compared to determine whether they are close or identical. If they are close or identical, it indicates that the lighting condition of the second vehicle is normal, and in this case, the process can end. If a significant difference is found between the two, for example, the brightness of the first lighting image is significantly lower, it indicates that there may be an abnormality with the headlights of the second vehicle. In this case, the server can send an abnormal warning message to the owner of the second vehicle. This abnormal warning message can be sent to the second vehicle, or to the mobile terminal of the vehicle owner or associated personnel (such as the owner's family members). The specific content and form of the message can be set according to actual requirements.

[0074] It can be understood that in the vehicle lighting abnormality detection method provided in the embodiments of the present application, during driving, the first vehicle collects the first lighting image and license plate image of the second vehicle; the first vehicle sends the first lighting image and the license plate image to the server; the server identifies the second vehicle based on the license plate image and queries the standard lighting image corresponding to the second vehicle from a pre-established standard database; wherein, the standard database is used to store the lighting images of each vehicle in a normal state; the server compares the first lighting image and the standard lighting image; if it is determined that the first lighting image is abnormal, the server sends an abnormal warning message to the owner of the second vehicle. The present application can use the first vehicle to help detect lighting abnormalities of other second vehicles. Compared with the mode of the vehicle itself detecting lighting abnormalities, it can effectively improve the stability and reliability of detection, and help the vehicle owner quickly discover lighting abnormalities of the vehicle as much as possible, which is beneficial to improving the driving safety of the vehicle.

[0075] Specifically, in some embodiments, the first vehicle collecting the first lighting image and license plate image of the second vehicle includes:

[0076] After the first vehicle enables the mutual assistance detection function, the first lighting image and license plate image of the second vehicle are collected through the front camera or rear camera on the first vehicle.

[0077] The step of if it is determined that the first lighting image is abnormal, the server sends an abnormal warning message to the owner of the second vehicle includes:

[0078] If it is determined that the first lighting image is abnormal, the server detects whether the second vehicle enables the mutual assistance detection function;

[0079] If it is determined that the second vehicle enables the mutual assistance detection function, the server sends an abnormal warning message to the owner of the second vehicle.

[0080] In the embodiments of the present application, the first vehicle collects images of the second vehicle and sends them to the server for anomaly detection. This itself has certain data processing requirements and cost consumption for the first vehicle. Therefore, this function can be selected to be turned on or off according to the user's needs. In the embodiments of the present application, it can be recorded as the mutual assistance detection function. After the first vehicle turns on the mutual assistance detection function, the first vehicle will collect the first light image and license plate image of the second vehicle through the front camera or the rear camera. Relatively speaking, for the second vehicle, if it does not turn on the mutual assistance detection function, the server may not send it anomaly warning information. In this way, when each vehicle turns on the mutual assistance detection function, the mutual assistance detection function can be realized. If a certain vehicle does not turn on the mutual assistance detection function, certain data processing resources and consumption can be saved, but it also cannot receive anomaly warning information. Each vehicle owner can determine whether to turn on the mutual assistance detection function according to their own driving needs, and the personalized experience is better.

[0081] Specifically, in some embodiments, the server comparing the first light image and the standard light image includes:

[0082] The server calculates a first similarity between the first light image and the standard light image;

[0083] If the first similarity is greater than or equal to a first preset threshold, the server determines that the first light image has no anomaly;

[0084] If the first similarity is less than the first preset threshold, the server determines that the first light image has an anomaly.

[0085] In the embodiments of the present application, when the server determines whether the first light image has an anomaly, the similarity between the first light image and the standard light image can be calculated. In the embodiments of the present application, it is recorded as the first similarity. For the first similarity, a threshold can be set, denoted as the first preset threshold. If the first similarity is large, for example, greater than or equal to the first preset threshold, it means that the first light image and the standard light image are very close, and the vehicle lights are probably normal. At this time, it can be determined that the first light image has no anomaly. Relatively speaking, if the first similarity is small, for example, less than the first preset threshold, it means that the first light image and the standard light image are quite different, and the vehicle lights are probably abnormal. At this time, it can be determined that the first light image has an anomaly. The specific size of the first preset threshold can be flexibly set according to actual needs, and the present application does not limit this.

[0086] Specifically, in some embodiments, the method further includes:

[0087] Before the first vehicle starts, it collects a second light image when the vehicle lights are on and a reference image when the vehicle lights are off;

[0088] The first vehicle sends the second lighting image and the reference image to the server;

[0089] The server compares the second lighting image with the reference image;

[0090] If it is determined that the second lighting image is abnormal, the server sends an abnormal warning message to the owner of the first vehicle.

[0091] In the embodiments of the present application, for the first vehicle, it can also perform self-check of lighting abnormalities based on its own image acquisition device with the help of the server. Specifically, before starting, the first vehicle can turn on the vehicle lights to collect relevant lighting images to obtain the second lighting image, and turn off the vehicle lights to collect images in front of or behind the vehicle to obtain the reference image. Then, the second lighting image and the reference image can be sent to the server for abnormality detection. If it is found that the second lighting image is abnormal, an alarm can be given to the owner of the first vehicle.

[0092] Exemplarily, in the night state, after the external vehicle lights are turned off, the front and rear cameras of the intelligent driving can be used to capture the brightness behind and compare it with the standard lighting image of the first vehicle in the database. If it becomes darker than usual, the user will be notified that there is a risk and further confirmation is required. After obtaining the user's consent, the camera can request to send a public CAN signal to the vehicle main domain controller through the private CAN to the intelligent driving domain controller. The vehicle main domain controller sends the signal to the vehicle area controller, and the vehicle area controller sends a signal to turn on the front lights (or tail lights). The camera takes a brightness photo of the front (or rear) when the lights are on; then the vehicle sends an extinguishing signal to the area controller, the front lights (or tail lights) are turned off, and the camera takes a brightness photo of the front (or rear) after the lights are turned off; by comparing the two photos, it is confirmed whether there is an abnormality in the lights. After confirmation, the user will be further reminded to replace them in time.

[0093] Specifically, in some embodiments, the server compares the second lighting image with the reference image, including:

[0094] The server calculates a second similarity between the second lighting image and the reference image;

[0095] If the second similarity is less than or equal to a second preset threshold, the server determines that the second lighting image is not abnormal;

[0096] If the second similarity is greater than the second preset threshold, the server determines that the second lighting image is abnormal.

[0097] In the embodiments of the present application, when the server compares the second lighting image with the reference image, it can also be judged by means of similarity. Specifically, the similarity between the second lighting image and the reference image can be calculated, denoted as the second similarity. For the second similarity, a threshold can also be set, denoted as the second preset threshold. If the second similarity is less than or equal to the second preset threshold, it indicates that the difference before and after turning on the vehicle lights is large, and the vehicle lights are probably okay. At this time, it can be determined that the second lighting image is normal. On the contrary, if the second similarity is greater than the second preset threshold, it indicates that the difference before and after turning on the vehicle lights is small and there is no change, and the vehicle lights are probably not working properly. At this time, it can be determined that the second lighting image is abnormal.

[0098] In the embodiments of the present application, a method for detecting abnormal vehicle lights is also provided, which is applied to the first vehicle. The method includes:

[0099] During driving, collect the first lighting image and license plate image of the second vehicle;

[0100] Send the first lighting image and the license plate image to the server, so that the server can identify the second vehicle according to the license plate image, query the standard lighting image corresponding to the second vehicle from the pre-established standard database, and compare the first lighting image with the standard lighting image. If it is determined that the first lighting image is abnormal, an abnormal alarm message is sent to the owner of the second vehicle; wherein, the standard database is used to store the lighting images of each vehicle in the normal state.

[0101] It can be understood that the content in the foregoing embodiments is applicable to the embodiments of the present application. For the various technical details in the embodiments of the present application, reference can be made to the foregoing embodiments for implementation, and details are not described herein again.

[0102] Refer to Figure 3 , in the embodiments of the present application, a device for detecting abnormal vehicle lights is also provided, including:

[0103] A collection unit 310, configured to collect the first lighting image and license plate image of the second vehicle during driving;

[0104] A sending unit 320, configured to send the first lighting image and the license plate image to the server, so that the server can identify the second vehicle according to the license plate image, query the standard lighting image corresponding to the second vehicle from the pre-established standard database, and compare the first lighting image with the standard lighting image. If it is determined that the first lighting image is abnormal, an abnormal alarm message is sent to the owner of the second vehicle; wherein, the standard database is used to store the lighting images of each vehicle in the normal state.

[0105] It can be understood that the content in the above method embodiments is applicable to the device embodiments of the present application. The functions specifically implemented in the device embodiments of the present application are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those in the above method embodiments.

[0106] Referring to Figure 4 , an embodiment of the present application provides an electronic device, including:

[0107] At least one processor 410;

[0108] At least one memory 420, configured to store at least one program;

[0109] When at least one program is executed by at least one processor 410, at least one processor 410 implements the above-mentioned method for detecting abnormal vehicle lights.

[0110] Similarly, the content in the above method embodiments is applicable to the electronic device embodiments of the present application. The functions specifically implemented in the electronic device embodiments of the present application are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those in the above method embodiments.

[0111] An embodiment of the present application further provides a computer-readable storage medium, in which a program executable by a processor 410 is stored. The program executable by the processor 410 is used to execute the above-mentioned method for detecting abnormal vehicle lights when executed by the processor 410.

[0112] Similarly, the content in the above method embodiments is applicable to the computer-readable storage medium embodiments of the present application. The functions specifically implemented in the computer-readable storage medium embodiments of the present application are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those in the above method embodiments.

[0113] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order mentioned in the operation diagrams. For example, depending on the functions / operations involved, two consecutive blocks shown may actually be executed substantially simultaneously or the blocks can sometimes be executed in the reverse order. In addition, the embodiments presented and described in the flowcharts of the present application are provided by way of example for a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logical flows presented herein. Alternative embodiments are expected, where the order of various operations is changed and the sub-operations described as part of a larger operation are executed independently.

[0114] In addition, although the present application has been described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and / or features may be integrated in a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It should also be understood that a detailed discussion of the actual implementation of each module is not necessary for understanding the present application. Rather, given the attributes, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the modules will be understood within the ordinary skills of an engineer. Thus, those skilled in the art can implement the present application as set forth in the claims without undue experimentation. It should also be understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present application, which is determined by the full scope of the appended claims and their equivalents.

[0115] If a function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0116] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a predefined sequence of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in conjunction with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0117] More specific examples (nonexhaustive list) of computer-readable media include the following: an electrical connection (electronic device) having one or more wirings, a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable media can even be paper or other suitable media on which a program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing it in a suitable manner if necessary, and then storing it in a computer memory.

[0118] It should be understood that various parts of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple 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, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having suitable combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0119] In the foregoing description of this specification, descriptions with reference to the terms "one embodiment / example", "another embodiment / example", or "certain embodiments / examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0120] Although the embodiments of the present application have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the claims and their equivalents.

[0121] The above has specifically described the preferred embodiments of the present application, but the present application is not limited to the embodiments. Those skilled in the art can make various equivalent deformations or substitutions without departing from the spirit of the present application, and these equivalent deformations or substitutions are all included within the scope defined by the claims of the present application.

Claims

1. A method for detecting abnormal vehicle lighting, characterized in that: The method comprises: During driving, the first vehicle collects a first light image and a license plate image of the second vehicle; The first vehicle sends the first light image and the license plate image to a server; The server identifies the second vehicle according to the license plate image, and queries a pre-established standard database for a standard light image corresponding to the second vehicle; wherein the standard database is used to store light images of each vehicle in a normal state; The server compares the first light image with the standard light image; If it is determined that the first light image is abnormal, the server sends abnormality warning information to the owner of the second vehicle.

2. The method for detecting abnormal vehicle lighting according to claim 1, characterized in that: The first vehicle collects a first light image and a license plate image of a second vehicle, including: When the mutual assistance detection function is turned on for the first vehicle, the first light image and license plate image of the second vehicle are collected through the front camera or the rear camera on the first vehicle.

3. A method for detecting abnormal vehicle lighting according to claim 2, characterized in that: If it is determined that the first light image is abnormal, the server sends abnormality warning information to the owner of the second vehicle, including: If it is determined that the first light image is abnormal, the server detects whether the second vehicle has a mutual assistance detection function turned on; If it is determined that the second vehicle turns on the mutual assistance detection function, the server sends an abnormal warning message to the owner of the second vehicle.

4. The method for detecting abnormal vehicle lighting according to claim 1, characterized in that: The server compares the first light image with the standard light image, including: The server calculates a first similarity between the first light image and the standard light image; If the first similarity is greater than or equal to a first preset threshold, the server determines that there is no abnormality in the first light image; If the first similarity is less than a first preset threshold, the server determines that an abnormality exists in the first light image.

5. The method for detecting abnormal vehicle lighting according to claim 1, characterized in that: The method further comprises: Before starting the first vehicle, collecting a second light image when the vehicle lights are turned on and a comparison image when the vehicle lights are turned off; The first vehicle sends the second light image and the reference image to the server; The server compares the second light image with the reference image; If it is determined that the second light image is abnormal, the server sends abnormality warning information to the owner of the first vehicle.

6. A method for detecting abnormal vehicle lighting according to claim 5, characterized in that: The server compares the second light image with the reference image, including: The server calculates a second similarity between the second light image and the reference image; If the second similarity is less than or equal to a second preset threshold, the server determines that there is no abnormality in the second light image; If the second similarity is greater than a second preset threshold, the server determines that there is an abnormality in the second light image.

7. A method for detecting abnormal vehicle lighting, characterized in that: Applied to a first vehicle, the method comprises: During the driving process, collecting a first light image and a license plate image of the second vehicle; The first light image and the license plate image are sent to a server so that the server identifies the second vehicle according to the license plate image, queries the standard light image corresponding to the second vehicle from a pre-established standard database, and compares the first light image with the standard light image. If it is determined that there is an abnormality in the first light image, an abnormality alarm message is sent to the owner of the second vehicle; wherein the standard database is used to store the light images of each vehicle in a normal state.

8. A vehicle lighting abnormality detection device, characterized in that: Applied to a first vehicle, the device comprises: A collection unit, used for collecting a first light image and a license plate image of a second vehicle during driving; A sending unit is used to send the first light image and the license plate image to a server, so that the server can identify the second vehicle according to the license plate image, query the standard light image corresponding to the second vehicle from a pre-established standard database, and compare the first light image with the standard light image. If it is determined that there is an abnormality in the first light image, an abnormality alarm message is sent to the owner of the second vehicle; wherein the standard database is used to store the light image of each vehicle in a normal state.

9. An electronic device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method for detecting abnormal vehicle lighting as described in claim 7.

10. A computer-readable storage medium storing a program executable by a processor, characterized in that: The processor-executable program is used to implement a vehicle lighting abnormality detection method as claimed in claim 7 when executed by the processor.

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