CN113420620A

CN113420620A - Method and device for detecting using state of car lamp in severe weather

Info

Publication number: CN113420620A
Application number: CN202110636795.5A
Authority: CN
Inventors: 林骏; 王亚运; 王陈业
Original assignee: Zhejiang Dahua Technology Co Ltd
Current assignee: Zhejiang Dahua Technology Co Ltd
Priority date: 2021-06-08
Filing date: 2021-06-08
Publication date: 2021-09-21

Abstract

The embodiment of the application provides a method and a device for detecting the use state of a car lamp in severe weather. The method comprises the following steps: detecting a weather state; identifying a running vehicle, and identifying the state of a lamp of the vehicle; and judging whether the vehicle meets the driving standard or not according to the state of the lamp and the weather state. By the mode, whether the vehicle lamp is used normally or not under a severe antenna can be detected, and the consciousness that a driver uses the vehicle lamp correctly (especially under severe weather) is facilitated to be normalized.

Description

Method and device for detecting using state of car lamp in severe weather

Technical Field

The invention relates to the technical field of image processing, in particular to a method and a device for detecting the use state of a car lamp in severe weather.

Background

With the continuous development of the economic level of China and the continuous improvement of the living standard of people, the number of private cars on roads is increased day by day, and the continuous increase of the number of vehicles brings great pressure to the operation of a traffic system, particularly in the aspect of safe driving of the vehicles, the number of casualties and property loss caused by traffic accidents are extremely surprised every year. Among them, traffic safety accidents due to bad weather account for a large part. When low visibility weather conditions such as heavy fog, heavy rain, heavy snow, dust, hail and the like occur, if the vehicles do not use light according to the regulations, the vehicles around are difficult to find by the front and the rear vehicles, so that traffic accidents such as rear-end collision, scratch and the like are caused, and casualties are possibly caused seriously. For this situation, it becomes important to identify those vehicles that do not have their lights turned on in bad weather.

For the detection of severe weather, most methods are implemented by meteorological sensors, which are relatively costly. After severe weather is detected, the vehicle is reminded of driving carefully through modes such as an electronic warning board, a short message and broadcasting, and whether violation behaviors exist in the vehicle or not is not detected and is not snapshoted.

Disclosure of Invention

The embodiment of the application provides a method and a device for detecting the use state of a vehicle lamp in severe weather, which are used for detecting and identifying whether a driver drives safely through the vehicle lamp.

In a first aspect, a vehicle light detection method is provided, including:

detecting whether the weather condition belongs to severe weather;

and identifying the on and/or off state of a lamp of a running vehicle to judge whether the vehicle uses the lamp according to the driving standard in the severe weather.

In one possible design, the detecting the weather condition is severe weather, including:

acquiring N frames of images through image acquisition equipment, wherein the images comprise current environment information;

and inputting the N frames of images into a preset algorithm for calculation, and determining that the weather state belongs to severe weather.

In one possible design, identifying an on or off state of a lamp of a running vehicle includes:

determining an area of interest, wherein the area of interest comprises at least one of an accident high-incidence area, a user-designated area and a default area in a driving road;

the on and/or off state of the headlights of a vehicle present in said area of interest is identified.

In one possible design, identifying the on and/or off state of the headlights of the vehicle present in the area of interest comprises:

when a vehicle enters the region of interest and the distance between the tail of the vehicle and the edge of the region of interest is greater than a preset distance, identifying the on and/or off state of the vehicle lights of the vehicle.

In one possible design, the determining whether the vehicle uses the lamp according to the driving regulation in the severe weather by recognizing the on and/or off state of the lamp of the running vehicle includes:

determining that the vehicle uses the vehicle light according to a driving party when the vehicle light satisfies at least one of the following conditions;

the conditions include:

at least one lamp on the vehicle is in an on state;

at least one of the headlights and taillights on the vehicle is in an on state;

at least one of a pair of headlights and a pair of taillights on the vehicle is in an on state;

at least one of a head fog light pair and a tail fog light pair on the vehicle is in an on state;

at least one of the pair of headlights and the pair of fog lights on the vehicle is in an on state;

at least one of the tail lamp pair and the tail fog lamp pair on the vehicle is in an on state.

In one possible design, the inclement weather includes: at least one of rain, snow, hail and sand.

In a second aspect, a device for detecting the use state of a vehicle lamp in severe weather is provided, which includes:

the detection unit is used for detecting whether the weather state belongs to severe weather;

an identification unit for identifying the on and/or off state of a lamp of a running vehicle;

and the determining unit is used for judging whether the vehicle uses the vehicle lamp according to the driving standard in the severe weather according to the identification result.

In a possible embodiment, the detection unit is specifically configured to:

In a possible embodiment, the identification unit is specifically configured to:

In a possible embodiment, the determining unit is specifically configured to:

determining that the vehicle uses the vehicle lights according to a driving specification when the vehicle lights satisfy at least one of the following conditions;

the conditions include:

at least one lamp on the vehicle is in an on state;

at least one of the headlights and taillights on the vehicle is in an on state;

In one possible embodiment, the inclement weather comprises: at least one of rain, snow, hail and sand.

In a third aspect, an electronic device is provided, including: a memory for storing program instructions;

a processor for calling the program instructions stored in said memory and for executing the method steps as provided in the first aspect above in accordance with the obtained program instructions.

In a fourth aspect, there is provided a computer readable storage medium storing a computer program comprising program instructions which, when executed by a computer, cause the computer to perform the method steps as provided in the first aspect above.

In a fifth aspect, a computer program product comprising instructions is provided, which, when run on a computer, causes the computer to perform the method steps as provided in the first aspect above.

In the embodiment of the application, the vehicle lamp detection device can detect the weather state; identifying a running vehicle, and identifying the state of a lamp of the vehicle; and judging whether the vehicle meets the driving standard or not according to the state of the vehicle lamp and the weather state. Therefore, the problem that whether the driver drives normally or not cannot be judged in the abnormal antenna state can be solved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application.

Fig. 1 is a flowchart of a vehicle lamp detection method according to an embodiment of the present disclosure;

fig. 2 is a schematic structural diagram of a weather identification network according to an embodiment of the present disclosure;

FIG. 3 is a schematic view of a vehicle light state detection scenario in an embodiment of the invention;

FIG. 4 is a schematic diagram of a method for detecting the type and status of a vehicle lamp according to an embodiment of the present invention;

fig. 5 is a configuration diagram of a vehicle lamp detecting device according to an embodiment of the present application;

fig. 6 is a schematic view of an electronic device according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application. In the present application, the embodiments and features of the embodiments may be arbitrarily combined with each other without conflict. Also, while a logical order is shown in the flow diagrams, in some cases, the steps shown or described may be performed in an order different than here.

The terms "first" and "second" in the description and claims of the present application and the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the term "comprises" and any variations thereof, which are intended to cover non-exclusive protection. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus. The "plurality" in the present application may mean at least two, for example, two, three or more, and the embodiments of the present application are not limited.

In addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" in this document generally indicates that the preceding and following related objects are in an "or" relationship unless otherwise specified.

The technical scheme provided by the embodiment of the application is described in the following with the accompanying drawings of the specification.

Referring to fig. 1, fig. 1 shows a vehicle lamp detection method according to an embodiment of the present disclosure. The method may be applied to a car light detection device, which may be a drive test unit, i.e. a detection unit arranged at the roadside. The flow chart of the method shown in fig. 1 is described as follows:

step 101: detecting that the weather condition is severe weather.

One possible implementation manner is that an image acquisition state acquires N frames of images, wherein the images comprise current environment information; and inputting the N frames of images into a preset algorithm for calculation to obtain the weather state. Then, it is identified whether the weather condition belongs to bad weather (or abnormal weather) including at least one of rain, snow, hail, sand and dust. The weather that rain, snow, haze and the like can influence normal running of the vehicle belongs to abnormal weather. Optionally, the abnormal weather can be further subdivided, for example, each abnormal weather can be divided into a mild abnormal weather and a severe weather according to the influence degree on the driving state. The light abnormal weather only suggests to turn on the vehicle lamp, and the vehicle lamp state is allowed to be a turn-off state; and the vehicle lamp is forced to be turned on in the presence of severe weather.

Illustratively, the preset algorithm may be an AI algorithm, such as a neural network, a convolutional neural network, a deep neural network, and the like. Taking a convolutional neural network (e.g., a 3D convolutional neural network) as an example, the convolutional neural network may be used to implement the detection of the weather condition through image recognition. Illustratively, the convolutional neural network includes a previously collected weather data set. The convolution neural network compares the N frames of images input into the convolution neural network with the acquired weather data, and then outputs the weather state in the output module. The pre-stored weather data set can be used for constructing a weather condition identification data set which needs to be used for identifying weather in the future through collecting short videos of normal weather conditions and abnormal weather conditions of the past traffic video scenes and analyzing, comparing and summarizing big data. The N frames of images may be images acquired by real-time monitoring through a monitoring device.

For example, referring to fig. 2, the convolutional neural network is configured as a multitask classification network, and eight categories of weather conditions can be output in the output module; for example, there are six weather conditions and two weather abnormal degrees, which respectively include normal weather, rainy weather, snowy weather, hail weather, haze weather, sand and dust weather, and mild abnormal weather and severe weather. Because the change state of the weather is in slow change all the time, the weather state can be determined once through the network at regular time intervals t, so that whether the current vehicle needs to be detected whether to turn on the lamp or not can be judged more accurately.

Step 102: whether the vehicle uses the vehicle lamp according to the driving standard in severe weather is judged by identifying the on and/or off state of the vehicle lamp of the running vehicle.

One possible implementation manner is to determine an area of interest, where the area of interest may be an area where a driving accident occurs frequently, or an area designated by a user, or a default area, and the like; the determination mode can be manually defined, or can be implemented in various modes such as computer setting and defining. And identifying the state of the lamp of the vehicle entering the region of interest after the region of interest is determined. That is to say, the method and the device can only identify the vehicle lamp states of the vehicles in the region of interest, do not need to identify all vehicle lamps, and are high in efficiency.

Optionally, before identifying the headlight state of the vehicle in the area of interest, it may be further determined that the rear of the vehicle and/or the distance between the headlight and the edge of the area of interest is greater than a preset distance. This is because visibility of the traveling vehicle and visibility of the surveillance video are low in severe weather conditions, and in order to identify the position and state of the vehicle more clearly and accurately, it is necessary to ensure that the vehicle completely enters the region of interest and then performs vehicle light identification. For example, referring to fig. 4, a detection distance d is defined, and the identification of the headlight is started when the vehicle is detected to enter the region of interest and the distance from the upper boundary or the lower boundary is greater than d.

Optionally, identifying the running vehicle includes: the vehicle location is located and then the state of the lights on the vehicle is identified. Optionally, before the vehicle position is located, other objects such as pedestrians and non-motor vehicle targets can be filtered, only the motor vehicle target to be detected is left, and accurate location and judgment of the fixed target can be achieved. For example, the application can determine a coordinate point of a specific position of a vehicle, wherein the coordinate point is a coordinate point of a minimum rectangular frame containing the vehicle; the vehicle may also be tracked for multiple frames of images. For example, the vehicles in each frame area are detected, and the detection results are related by using a tracking algorithm. The tracking algorithm tracks at a frame rate, finds a target vehicle in each image of a video sequence image in real time, and determines unique position information corresponding to the target vehicle. Alternatively, in order to facilitate identification of each vehicle, after the location of the vehicle is located, each vehicle may be assigned a unique ID, completing the location of the vehicle.

After the vehicle is located, the vehicle on-board light state is identified. The vehicle light state includes vehicle light on, and/or vehicle light off. For example, the car light state identification can be identified through a convolutional neural network CNN, please refer to fig. 3, the CNN identifies an image input to the CNN, and outputs car light center point coordinates (x, y) and a width and a height (w, h) of a car light frame; the vehicle lamp type attribute of the vehicle lamp can be output, namely a left head lamp group, a left head fog lamp, a right head lamp group, a right head fog lamp, a left tail lamp group, a left tail fog lamp, a right tail lamp group and a right tail fog lamp; the state of identifying the car lamp can also be output, and comprises an on state and an off state.

In order to save the time and resource consumption of car light identification, a multi-label detection network can be constructed to achieve the aim ofThe position, type and switch state of the vehicle lamp are detected and identified simultaneously. For example, the output end of yolov3 network is multi-label improved, and a multi-label detection network is constructed by using a sigmoid activation function + packet softmax activation function. In the multi-label detection task, the characteristic channel of the output end is defined as

Wherein

Number of vehicle lamp types, in the present application

Wherein

Number of on-off states of the vehicle lamp, in the present application

In the multiple groups of input of the multi-tag network, the confidence degree of whether an object exists in a detection frame and the characteristics corresponding to the coordinates are used as one group of input and a sigmoid grouped activation function is used, and the type of the car lamp is used as the other group of input and a softmax activation function is used, so that each detection frame can output two attributes of the type of the car lamp and the on-off state of the car lamp; in this case, the detection of the vehicle lamp and the identification of the switching state can be simultaneously accomplished via a yolov3 network.

When the weather condition detected in step 101 is normal weather or mild abnormal weather, it may not be necessary to identify the state of the lamp, and when the weather condition is severe weather (weather in which an accident is likely to occur), it may be necessary to identify the state of the lamp of the vehicle. When the weather state is weather which is easy to cause accidents, and the vehicle lamp on the vehicle meets the following conditions, determining that the vehicle meets driving regulations; the conditions include:

generally, lamps of a vehicle are paired whether to be turned on or off, and the lamps need to be paired first; the left head lamp and the right head lamp are in a pair (called a head lamp pair), the left tail lamp and the right tail lamp are in a pair (called a tail lamp pair), the left fog lamp and the right fog lamp are in a pair (called a head fog lamp pair), and the left fog lamp and the right fog lamp are in a pair (called a tail fog lamp pair); when the vehicle lamp cannot be matched, the state is set to be unknown and the vehicle lamp state is not allowed to be determined; according to the recognition results of all the lamp pairs and the recognition results of the weather conditions, when the weather conditions are severe weather, whether the vehicle is used according to the regulations or not needs to be further judged to turn on the lamps. For example, a vehicle may be determined to be in compliance with driving regulations when the vehicle satisfies at least one of the following conditions; specifically, the conditions include:

1) at least one light on the vehicle is in an on state.

Wherein the at least one vehicle light may be a lamp or a group of lamps. Wherein one lamp may be a left headlight, a right headlight, a left taillight, a right taillight, etc. The set of lights may include at least one of a left head light set, a left tail light set, a left head fog light, a left tail fog light, a right head light set, a right tail light set, a right head fog light, and a right tail fog light.

2) At least one of the headlights and the taillights of the vehicle is in an on state.

The headlight includes at least one in left headlight, left head fog lamp, right headlight and the right head fog lamp, or at least one group in left tail banks, left tail fog lamp, right tail banks and the right tail fog lamp.

3) At least one of a pair of headlights and a pair of taillights on the vehicle is in an on state.

The pair of headlights includes at least one pair (or set) of left and right headlights, and left and right fog lights. The tail light pair includes at least one pair (or set) of left and right tail lights, left and right tail fog lights.

4) At least one of the pair of head fog lights and the pair of tail fog lights on the vehicle is in an on state.

Wherein, the first fog lamp pair includes left first fog lamp and right first fog lamp. The tail fog lamp pair comprises a left tail fog lamp and a right tail fog lamp.

5) At least one pair of the head lamp pair and the fog lamp pair on the vehicle is in an opening state.

6) At least one of the tail lamp pair and the tail fog lamp pair on the vehicle is in an on state.

As an example, table 1 below is a way of determining the status of the lamp pairs on the vehicle.

TABLE 1 lamp pair State determination method

Left light state	State of right lamp	Lamp pair state
			Is opened	Is opened	Is opened
Is opened	Close off	Close off
			Close off	Is opened	Close off
Close off	Close off	Close off

As shown in table 1, when the left light state is on and the right light state is on, then the light pair state is considered on. That is, if only one of the lamps in a group is turned on, the group is turned on.

As one example, table 2 below is a manner of determining whether the vehicle is normally driven.

TABLE 2. determination of whether the vehicle is using the lights as specified

Head/tail lamp pair status	Head fog lamp pair/tail fog lamp pair status	Whether to use the vehicle lamp as specified
			Is opened	Is opened	Is that
Is opened	Close off	Is that
			Close off	Is opened	Is that
Close off	Close off	Whether or not

In order to improve the accuracy, for N frames of images, one group of image groups is taken for identification each time. For example, N frames of images are divided into g groups, each group of images comprises f frames of a single image picture, a frame number threshold t is set, and when the number of the vehicle lamp opening times obtained by multi-frame identification of each group of images exceeds the threshold t, the identification result of the group of images is judged to be that the vehicle lamp is in an opening state. And when the group number of the image groups with the recognition result of turning on the vehicle lamps in the g groups of vehicle image groups exceeds a threshold value m, judging that the vehicle turns on the vehicle lamps according to the specification. When the number of image groups of which the lamps are turned on in g groups of vehicle image groups is less than a threshold m, or the number of the turning-on times of the lamps in f-frame identification of each group is less than a threshold t, the vehicle is determined not to turn on the lamps according to the regulations, and under the condition, the vehicle violation is identified, the target motor vehicle is captured, and the captured images and the license plate number are uploaded to a traffic management department.

Based on the same inventive concept, the embodiment of the application provides a vehicle lamp detection device. The car light detection device can be a hardware structure, a software module or a hardware structure and a software module. The car light detection device can be realized by a chip system, and the chip system can be formed by a chip and can also comprise the chip and other discrete devices. Referring to fig. 5, the vehicle light detecting device includes a detecting unit 501, an identifying unit 502, and a determining unit 503. Wherein:

a detection unit 501, configured to detect that a weather state belongs to severe weather;

an identification unit 502 for identifying an on and/or off state of a lamp of a running vehicle;

the determining unit 503 is configured to determine, according to the recognition result, whether the belonging vehicle uses a vehicle lamp according to the driving standard in the severe weather.

In a possible implementation manner, the detection unit 501 is specifically configured to:

In a possible implementation manner, the identifying unit 502 is specifically configured to:

In a possible implementation, the determining unit 503 is specifically configured to:

when the vehicle lamp meets at least one of the following conditions, the determined vehicle uses the vehicle lamp according to the driving specification;

the conditions include:

at least one lamp on the vehicle is in an on state;

at least one of the headlights and taillights on the vehicle is in an on state;

A possible implementation, the inclement weather comprising: at least one of rain, snow, hail and sand.

The division of the modules in the embodiments of the present application is schematic, and only one logical function division is provided, and in actual implementation, there may be another division manner, and in addition, each functional module in each embodiment of the present application may be integrated in one processor, may also exist alone physically, or may also be integrated in one module by two or more modules. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode.

Based on the same inventive concept, the embodiment of the application provides electronic equipment. Referring to fig. 6, the electronic device includes at least one processor 601 and a memory 602 connected to the at least one processor, in this embodiment, a specific connection medium between the processor 601 and the memory 602 is not limited in this application, in fig. 6, the processor 601 and the memory 602 are connected by a bus 600 as an example, the bus 600 is represented by a thick line in fig. 6, and a connection manner between other components is only schematically illustrated and is not limited. The bus 600 may be divided into an address bus, a data bus, a control bus, etc., and is shown with only one thick line in fig. 6 for ease of illustration, but does not represent only one bus or type of bus.

In the embodiment of the present application, the memory 602 stores instructions executable by the at least one processor 601, and the at least one processor 601 may execute the steps included in the learning supervision method by executing the instructions stored in the memory 602.

The processor 601 is a control center of the electronic device, and may connect various parts of the whole electronic device by using various interfaces and lines, and perform various functions and process data of the electronic device by operating or executing instructions stored in the memory 602 and calling data stored in the memory 602, thereby performing overall monitoring on the electronic device. Alternatively, processor 601 may include one or more processing units, and processor 601 may integrate an application processor, which mainly handles operating systems and application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 601. In some embodiments, the processor 601 and the memory 602 may be implemented on the same chip, or in some embodiments, they may be implemented separately on separate chips.

The processor 601 may be a general-purpose processor, such as a Central Processing Unit (CPU), digital signal processor, application specific integrated circuit, field programmable gate array or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or the like, that may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present application. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the learning supervision method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.

The memory 602, which is a non-volatile computer-readable storage medium, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The Memory 602 may include at least one type of storage medium, and may include, for example, a flash Memory, a hard disk, a multimedia card, a card-type Memory, a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Programmable Read Only Memory (PROM), a Read Only Memory (ROM), a charge Erasable Programmable Read Only Memory (EEPROM), a magnetic Memory, a magnetic disk, an optical disk, and so on. The memory 602 is any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory 602 in the embodiments of the present application may also be circuitry or any other device capable of performing a storage function for storing program instructions and/or data.

By programming the processor 601, the code corresponding to the vehicle lamp detection method described in the foregoing embodiment may be solidified into the chip, so that the chip can execute the steps of the foregoing learning and monitoring method when running, and how to program the processor 601 is a technique known by those skilled in the art, and will not be described herein again.

Based on the same inventive concept, the present application also provides a computer-readable storage medium, which stores computer instructions, and when the computer instructions are executed on a computer, the computer is caused to execute the steps of the learning supervision method as described above.

In some possible embodiments, the aspects of the vehicle light detection method provided by the present application may also be implemented in the form of a program product, which includes program code for causing an electronic device to perform the steps in the learning supervision method according to various exemplary embodiments of the present application described above in this specification when the program product is run on the electronic device.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.

Claims

1. A method for detecting the use state of a vehicle lamp in severe weather is characterized by comprising the following steps:

detecting whether the weather condition belongs to severe weather;

the method comprises the steps of identifying the on and/or off state of a lamp of a running vehicle, and judging whether the vehicle uses the lamp according to driving regulations in severe weather.

2. The method of claim 1, wherein the detecting the weather condition is of a severe antenna, comprising:

3. The method of claim 1, wherein identifying an on or off state of a light of a traveling vehicle comprises:

4. The method of claim 3, wherein the identifying of the on and/or off state of a headlight of a vehicle present in the area of interest comprises:

5. The method of claim 1, wherein determining whether a vehicle is using lights according to driving norms in the inclement weather by identifying an on and/or off state of lights of a traveling vehicle comprises:

the conditions include:

at least one lamp on the vehicle is in an on state;

at least one of the headlights and taillights on the vehicle is in an on state;

6. The method of claim 1, wherein the inclement weather comprises: at least one of rain, snow, hail and sand.

7. The utility model provides a detection apparatus of car light service condition under bad weather which characterized in that includes:

8. The apparatus according to claim 7, wherein the detection unit is specifically configured to:

9. The apparatus according to claim 7, wherein the identification unit is specifically configured to:

10. The apparatus according to claim 9, wherein the identification unit is specifically configured to:

11. The apparatus according to claim 7, wherein the determining unit is specifically configured to:

determining that the vehicle uses the vehicle lights according to a driving specification when the vehicle lights satisfy at least one of the following conditions; the conditions include:

at least one lamp on the vehicle is in an on state;

at least one of the headlights and taillights on the vehicle is in an on state;

12. The apparatus of claim 7, wherein the inclement weather comprises: at least one of rain, snow, hail and sand.

13. An electronic device, comprising:

a memory for storing program instructions;

a processor for calling program instructions stored in said memory and for executing the steps comprised by the method of any one of claims 1 to 6 in accordance with the obtained program instructions.

14. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program comprising program instructions that, when executed by a computer, cause the computer to perform the method according to any one of claims 1-6.