Vehicle behavior determination method, device, electronic device and storage medium

Abstract

The present application discloses a method, device, electronic device and storage medium for determining the behavior of a whole vehicle, and relates to computer technology. The method comprises: obtaining the current driving parameters of the vehicle and the current in-vehicle image, wherein the current in-vehicle image comprises a driving area and a passenger area, wherein the driving area comprises driving pixels, and the passenger area comprises passenger pixels; determining the driving weight and the passenger weight based on the current driving parameters; processing the driving pixels using the driving weight, and processing the passenger pixels using the passenger weight, to obtain a driving and riding fusion image, so as to determine the behavior of the whole vehicle according to the driving and riding fusion image. The driving and riding fusion image in the present application combines the current driving parameters of the vehicle. When determining the behavior of the whole vehicle according to the driving and riding fusion image, it can be clear whether the passenger behavior or the driver behavior should be paid more attention to at the current moment, so as to accurately reflect the current state of the whole vehicle, and help to better serve the user according to the determined whole vehicle behavior, thereby achieving the beneficial effect of improving the driving and riding experience.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, device, electronic device and storage medium for determining whole vehicle behavior. Background Art

[0002] With the rapid development of the automobile industry, driving experience is gaining more and more attention on the basis of safe driving. When providing driving services, the focus is on the driver's driving behavior, and then providing corresponding safety tips and intelligent linkage services based on the identified driving behavior of the driver. For example, the driver's driving emotions, smoking behavior, drinking behavior, and phone call behavior can be identified.

[0003] The above approach of focusing only on the driver's driving behavior ignores the needs of passengers to a certain extent, thus reducing the passenger experience. Therefore, how to determine the overall behavior of the driver and passengers in a moving vehicle to improve the driving experience is a key issue to be studied. Summary of the invention

[0004] The present application provides a method, device, electronic device and storage medium for determining whole vehicle behavior, which can analyze the whole vehicle behavior to improve the driving experience.

[0005] In a first aspect, the present application provides a method for determining whole vehicle behavior, comprising: obtaining current driving parameters and a current in-vehicle image of the vehicle, the current in-vehicle image comprising a driving area and a passenger area, the driving area comprising driving pixel points, and the passenger area comprising passenger pixel points; determining a driving weight and a passenger weight based on the current driving parameters; processing the driving pixel points using the driving weight, and processing the passenger pixel points using the passenger weight, to obtain a driving and riding fusion image, so as to determine the whole vehicle behavior based on the driving and riding fusion image.

[0006] Optionally, the number of the current driving parameters is at least one; one current driving parameter corresponds to a threshold interval; determining the driving weight and the passenger weight based on the current driving parameters includes: judging whether each of the current driving parameters is within the corresponding threshold interval; if all the current driving parameters are within the corresponding threshold interval, determining that the value of the driving weight is not greater than the value of the passenger weight; if any of the current driving parameters is not within the corresponding threshold interval, determining that the value of the driving weight is greater than the value of the passenger weight; the sum of the value of the driving weight and the value of the passenger weight is 1.

[0007] Optionally, the using the driving weight to process the driving pixel points and the using the passenger weight to process the passenger pixel points to obtain the driving and riding fusion image includes: performing weighted calculation on the driving pixel points according to the driving weight, and performing weighted calculation on the passenger pixel points according to the passenger weight to obtain the driving and riding fusion image.

[0008] Optionally, the number of the current driving parameters is N; the driving weight includes N driving sub-weights, the passenger weight includes N passenger sub-weights, and one current driving parameter corresponds to one driving sub-weight and one passenger sub-weight; N is a positive integer greater than or equal to 2; one current driving parameter corresponds to a threshold interval; determining the driving weight and the passenger weight based on the current driving parameter includes: for any one of the current driving parameters, judging whether the current driving parameter is within the corresponding threshold interval; if the current driving parameter is within the corresponding threshold interval, determining that the value of the driving sub-weight corresponding to the current driving parameter is not greater than the value of the passenger sub-weight corresponding to the current driving parameter; if the current driving parameter is not within the corresponding threshold interval, determining that the value of the driving sub-weight corresponding to the current driving parameter is greater than the value of the passenger sub-weight corresponding to the current driving parameter; the sum of the value of the driving sub-weight corresponding to the current driving parameter and the value of the passenger sub-weight corresponding to the current driving parameter is 1.

[0009] Optionally, the using the driving weight to process the driving pixel points and the using the passenger weight to process the passenger pixel points to obtain the driving and riding fusion image includes: acquiring N feature images, wherein one feature image is obtained by weighted calculation of pixel values ​​corresponding to the driving pixel points by a driving sub-weight corresponding to a current driving parameter and by weighted calculation of pixel values ​​corresponding to the passenger pixel points by a passenger sub-weight corresponding to the current driving parameter; and performing feature calculation on the N feature images to obtain the driving and riding fusion image.

[0010] Optionally, performing feature calculation on the N feature images to obtain the driving fusion image includes: respectively calculating the pixel mean of each pixel point in each of the feature images to obtain the fusion feature corresponding to each of the feature images; and obtaining the driving fusion image according to the fusion features corresponding to all the feature images.

[0011] Optionally, after determining the whole vehicle behavior according to the driving and riding fusion image, it also includes: determining at least one target hardware information to be linked according to the whole vehicle behavior; calling at least one target hardware device corresponding to the target hardware information to provide corresponding linkage services based on at least one target hardware device.

[0012] In a second aspect, the present application provides a device for determining the behavior of a whole vehicle, the device comprising: a parameter acquisition module, for acquiring current driving parameters of the vehicle and a current in-vehicle image, the current in-vehicle image comprising a driving area and a passenger area, the driving area comprising driving pixel points, and the passenger area comprising passenger pixel points.

[0013] A weight determination module is used to determine a driving weight and a passenger weight based on the current driving parameters.

[0014] The behavior determination module is used to process the driving pixel points using the driving weights and process the passenger pixel points using the passenger weights to obtain a driving and riding fusion image, so as to determine the whole vehicle behavior according to the driving and riding fusion image.

[0015] In the third aspect, the present application also provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle behavior determination method described in any embodiment of the present application.

[0016] In a fourth aspect, the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle behavior determination method described in any embodiment of the present application when executed.

[0017] In a fifth aspect, the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the whole vehicle behavior method described in any embodiment of the present application.

[0018] The vehicle behavior determination solution provided in the embodiment of the present application obtains the current driving parameters of the vehicle to determine the corresponding driving weight and passenger weight for the driving area and the passenger area in the current in-vehicle image according to the current driving parameters, and then processes the driving pixels in the driving area by the driving weight, and processes the passenger pixels in the passenger area by the passenger weight, so as to obtain a driving and riding fusion image. The driving and riding fusion image in this embodiment combines the current driving parameters of the vehicle, so that when determining the vehicle behavior according to the driving and riding fusion image, it can be clear whether the current moment needs to pay more attention to the passenger behavior or the driver behavior, so as to accurately reflect the current vehicle status, which helps to better serve the user according to the determined vehicle behavior, thereby achieving the beneficial effect of improving the driving and riding experience.

[0019] It should be noted that the above-mentioned computer instructions may be stored in whole or in part on a computer-readable storage medium. The computer-readable storage medium may be packaged together with the processor of the vehicle behavior device, or may be packaged separately from the processor of the vehicle behavior device, and this application does not limit this.

[0020] The description of the second, third, fourth and fifth aspects of the present application can refer to the detailed description of the first aspect; and the beneficial effects of the description of the second, third, fourth and fifth aspects can refer to the beneficial effect analysis of the first aspect, which will not be repeated here.

[0021] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description.

[0022] It is understandable that before using the technical solutions disclosed in the embodiments of this application, the type, scope of use, and usage scenarios of the personal information involved in this application should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 It is a flow chart of the vehicle behavior determination method provided in an embodiment of the present application.

[0025] Figure 2 It is another flow chart of the vehicle behavior determination method provided in an embodiment of the present application.

[0026] Figure 3 It is another flow chart of the vehicle behavior determination method provided in the embodiment of the present application.

[0027] Figure 4 It is a structural schematic diagram of the vehicle behavior determination device provided in an embodiment of the present application.

[0028] Figure 5 It is a structural schematic diagram of an electronic device of a whole vehicle behavior determination method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the present application will be clearly and completely described below in conjunction with the drawings in the present embodiment. Obviously, the described embodiment is only a part of the embodiment of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present application.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] The present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for ease of description, only the parts related to the present application, rather than all structures, are shown in the accompanying drawings.

[0032] Figure 1 A flow chart of the whole vehicle behavior determination method provided in the embodiment of the present application, the present embodiment can be applied to the situation of analyzing the whole vehicle behavior in a vehicle in a driving state, the method can be executed by a whole vehicle behavior determination device, the whole vehicle behavior determination device can be implemented in the form of hardware and / or software, and integrated in the electronic device that executes the method. Preferably, the electronic device in the embodiment of the present application can be a server, or a computer device, etc.

[0033] refer to Figure 1 The vehicle behavior determination method of this embodiment includes but is not limited to the following steps:

[0034] S110, obtaining current driving parameters of the vehicle and a current in-vehicle image, where the current in-vehicle image includes a driving area and a passenger area, the driving area includes driving pixel points, and the passenger area includes passenger pixel points.

[0035] The current driving parameters of the vehicle can be obtained by connecting the vehicle terminal to the server terminal, and the vehicle terminal can upload the driving parameters of the vehicle to the server terminal in real time. Optionally, the vehicle terminal also includes an upload timestamp when sending the driving parameters to the server terminal. In this embodiment, the driving parameters include but are not limited to the vehicle's speed information, acceleration information, and / or steering wheel steering angle information at the current moment. The purpose of considering the current driving parameters of the vehicle in this embodiment is that the current driving parameters of the vehicle can reflect the dynamic changes of the current driving environment, including the vehicle's motion state, road conditions, and driver operations, etc., so as to more comprehensively understand the driving environment of the driver and passengers in the cabin, thereby helping to more accurately judge the state of the entire vehicle in subsequent steps.

[0036] The above current in-car image indicates that the cockpit contains an image of passengers and a driver. In addition to being able to capture the location area of ​​the driver and the passenger, the current in-car image can also capture the driver's behavior and the passenger's behavior, including but not limited to the following behaviors: drinking behavior, smoking behavior, making phone calls, and / or, the driver's and passengers' facial expressions, etc., which helps to provide corresponding linkage services according to the determined passenger behavior and driver behavior in subsequent steps, thereby improving the driving experience, etc.

[0037] The current in-vehicle image can be obtained by installing a high-resolution camera in the vehicle, such as a camera on the roof or in front of a reading light, to capture video surveillance footage of the driver and passengers in the vehicle. After receiving the video stream transmitted by the camera at the server, the video stream contains a timestamp. The current timestamp is used to correspond to the timestamp corresponding to the current driving parameters uploaded by the vehicle computer, so as to obtain the current driving parameters and the current in-vehicle image at the same time.

[0038] After receiving the in-car image, the server will mark the driving area and passenger area in the current in-car image based on image annotation technology. For a certain model, the type, installation position and angle of the vehicle camera are fixed, so the driver area and passenger area can be marked in a fixed way. For example, the purple area is marked as the passenger area, and the yellow area is the driver area. Among them, the marked driver area contains driving pixel points, and the marked passenger area contains corresponding passenger pixel points.

[0039] S120. Determine a driving weight and a passenger weight based on current driving parameters.

[0040] The vehicle behavior determination solution provided in this embodiment corresponds to different driving environments under different driving parameters, and different areas should be paid attention to under different driving environments. Therefore, when determining the driving weight of the driving area and the passenger weight of the passenger area, a comprehensive determination is made in combination with the current driving parameters.

[0041] Specifically, the driving weight and passenger weight can be determined based on the current driving parameters. When the vehicle is driving smoothly, the current driving parameters are relatively stable, then the focus should be on the passengers, and a higher weight value can be assigned to the passenger weight corresponding to the passenger area to improve the monitoring of the occupants' expressions and behavioral actions, which helps to enhance the members' comfort and entertainment experience; when the current driving parameters of the vehicle change drastically (such as sudden braking or sharp turns), the focus should be on the driver, and a higher weight value should be assigned to the driving weight corresponding to the driving area to focus on the monitoring of the driver's expressions and behavioral actions, to ensure that the driver's nervous or stressed expressions are captured in time, or the behaviors that affect driving safety are captured, to enhance the safety experience, wherein the driving weight and the passenger weight are summed to 1.

[0042] When determining the driving weight and passenger weight based on the current driving parameters, this embodiment can dynamically adjust the weight values ​​of the driver and passenger areas according to the changes in the vehicle driving parameters, thereby dynamically reflecting the importance of different areas under different driving parameters at different times, which helps to more accurately determine the current vehicle behavior. Optionally, conventional family vehicles include five-seat vehicles, six-seat vehicles, and seven-seat vehicles, which generally include a driver's seat and the rest are passenger seats. The driver in the driver's seat is required during the driving of the vehicle, and the number of passengers in other passengers is relatively large, that is, the passenger seats may be full or there may be no passengers. Then, when determining the driving weight and passenger weight based on the current driving parameters, this embodiment can also consider the occupancy rate of the passenger seats in the passenger area to determine the driving weight and passenger weight.

[0043] For example, when the vehicle is driving smoothly, it is necessary to focus on the needs of passengers, so a higher weight value is given to the passenger area, such as 0.8. The current 0.8 is the weight when the occupancy rate of the passenger seat is 1, so the corresponding driving weight of the driving area is 0.2; if the occupancy rate of the passenger seat is 1 / 4, then the weight value corresponding to the passenger seat can be reduced accordingly, such as 0.6, and then the driving weight corresponding to the driving area is 0.4, etc.; when the occupancy rate of the passenger seat is 0, there is no need to determine the passenger weight based on the current driving parameters, and only the behavior of the driving area needs to be fully focused. The values ​​of the passenger weight corresponding to the occupancy rate of the specific passenger area and the driving weight are not given examples one by one here.

[0044] S130, using the driving weight to process the driving pixel points, and using the passenger weight to process the passenger pixel points, to obtain a driving and riding fusion image, so as to determine the whole vehicle behavior according to the driving and riding fusion image.

[0045] The essence of determining the whole vehicle behavior in this embodiment is to use the determined driving weight and passenger weight to process the pixel points corresponding to the driving area and the passenger area respectively, so that the driving parameters of the vehicle are integrated into the processed image, so that if the passenger area needs to be focused on in the final driving and riding fusion image, the pixel values ​​corresponding to the passenger pixel points in the passenger area are brighter, and the pixel values ​​corresponding to the driving pixel points corresponding to the corresponding driving area are darker; if the driving area needs to be focused on, the pixel values ​​corresponding to the driving pixel points corresponding to the driving area are brighter, and the pixel values ​​corresponding to the passenger pixel points corresponding to the corresponding passenger area are darker, and so on.

[0046] After the current in-vehicle image is processed by the solution provided in this embodiment to obtain a driving and riding fusion image, the driving and riding fusion image can be further input into a behavior determination model, so that the behavior determination model can determine the current vehicle behavior through feature extraction and other methods.

[0047] For example, taking the determination of the driving emotion of the whole vehicle as an example, the driving mode can be adaptively adjusted according to the driving and riding fusion image. For example, when the driving and riding fusion image determines that the whole vehicle emotion is calm or happy, it can switch to a more comfortable driving mode to provide a more relaxed driving experience; when the emotion is tense, it will give priority to providing a safer driving mode. And when the determined whole vehicle emotion is different, it can also provide a corresponding music playlist, etc.

[0048] The vehicle behavior determination method provided in this embodiment obtains the current driving parameters of the vehicle to determine the corresponding driving weight and passenger weight for the driving area and the passenger area in the current in-vehicle image according to the current driving parameters, and then processes the driving pixel points in the driving area by the driving weight, and processes the passenger pixel points in the passenger area by the passenger weight, so as to obtain a driving and riding fusion image. The driving and riding fusion image in this embodiment combines the current driving parameters of the vehicle, so that when determining the vehicle behavior according to the driving and riding fusion image, it can be clear whether the passenger behavior or the driver behavior needs to be paid more attention to at the current moment, and the current vehicle state can be accurately reflected, which helps to better serve the user according to the determined vehicle behavior, thereby achieving the beneficial effect of improving the driving and riding experience.

[0049] Figure 2This is another flow chart of the vehicle behavior determination method provided by the embodiment of the present application. The embodiment of the present application is optimized on the basis of the above embodiments. Specifically, the optimization is as follows: This embodiment explains in detail the optimization process of "determining driving weight and passenger weight based on current driving parameters" and "processing driving pixels using driving weights and processing passenger pixels using passenger weights to obtain driving and riding fusion images" in the above embodiments. Specifically, please refer to Figure 2 The vehicle behavior determination method of this embodiment can be specifically implemented by the following steps S210 to S230.

[0050] S210, obtaining current driving parameters of the vehicle and a current in-vehicle image, where the current in-vehicle image includes a driving area and a passenger area, the driving area includes driving pixel points, and the passenger area includes passenger pixel points.

[0051] S220: Determine whether each current driving parameter is within a corresponding threshold range.

[0052] In this embodiment, the number of current driving parameters is at least one; one current driving parameter corresponds to one threshold interval, and the threshold interval is used to represent a value for stable operation of the vehicle under the corresponding driving parameter.

[0053] For example, the number of current driving parameters is 3, and the driving parameters include speed parameters, acceleration parameters, and steering angle parameters. For example, the threshold interval corresponding to the speed parameter is 15 km / h-60 km / h, the threshold interval corresponding to the acceleration parameter is -2 m / s2-2 m / s2, and the threshold interval corresponding to the steering angle parameter is -30°-30°. Then, the parameter value corresponding to each current driving parameter is obtained, so as to perform the relevant operation of determining whether each current driving parameter is within the corresponding threshold interval.

[0054] Specifically, if all current driving parameters are within the corresponding threshold interval, that is, when the speed parameter, acceleration parameter and steering angle parameter are all within the corresponding threshold interval, step S221 is executed. If any current driving parameter is not within the corresponding threshold interval, that is, no, any parameter of the speed parameter, acceleration parameter and steering angle parameter is not within the corresponding threshold interval, step S222 is executed.

[0055] S221. Determine that the value of the driving weight is not greater than the value of the passenger weight.

[0056] When all current driving parameters are within the corresponding threshold range, it indicates that the vehicle is running smoothly. At this time, the focus is on the passenger experience corresponding to the passenger area, so a higher value is given to the passenger weight, so that the driving weight value is not greater than the passenger weight value, and the sum of the driving weight value and the passenger weight value is 1. For example, the passenger weight is 0.7, the driving weight is 0.3, and so on.

[0057] S222. Determine that the value of the driving weight is greater than the value of the passenger weight.

[0058] When any parameter is not within the corresponding threshold range, such as sudden braking, acceleration or sudden steering, in order to ensure driving safety and prevent fatigue driving or distracted driving, a higher value is assigned to the driving weight, so that the driving weight is greater than the passenger weight. For example, the driving weight is 0.8 and the passenger weight is 0.2.

[0059] S230: Perform weighted calculation on driving pixel points according to the driving weight, and perform weighted calculation on passenger pixel points according to the passenger weight, to obtain a driving and riding fusion image.

[0060] The specific method of obtaining the driving and passenger fusion image in this embodiment is that the pixel values ​​corresponding to the driving pixel points and the passenger pixel points contained in the current in-vehicle image are all RGB color mode values ​​(RGB color mode), then the RGB of each driving pixel point can be multiplied by the corresponding driving weight, and the RGB of each passenger pixel point can be multiplied by the corresponding passenger weight, and then after weighted calculation, each pixel point in the obtained driving and passenger fusion image is a new weighted RGB value. In the driving and passenger fusion image obtained in this embodiment, the new RGB value corresponding to each pixel point can more accurately capture whether the current focus is on the driver's behavior or the passenger's behavior due to different driving parameters, provide a more accurate control basis for the intelligent linkage system, and improve the accuracy and practicality of the whole vehicle behavior judgment.

[0061] Another preferred embodiment, please refer to Figure 3 , Figure 3 This is another flow chart of the vehicle behavior determination method provided by the embodiment of the present application. The embodiment of the present application is optimized on the basis of the above embodiments. The specific optimization is as follows: This embodiment explains in detail the optimization process of "determining driving weight and passenger weight based on current driving parameters" and "using driving weight to process driving pixel points and using passenger weight to process passenger pixel points to obtain driving and riding fusion image" in the above embodiments. Specifically, please refer to Figure 3 The vehicle behavior determination method of this embodiment can be specifically implemented by the following steps S310 to S331.

[0062] It should be noted that in the embodiments of this application Figure 3 The corresponding vehicle behavior determination scheme is the same as in the above embodiment. Figure 2 The corresponding vehicle behavior determination scheme is a parallel scheme.

[0063] S310, obtaining current driving parameters of the vehicle and a current in-vehicle image, where the current in-vehicle image includes a driving area and a passenger area, where the driving area includes driving pixel points, and the passenger area includes passenger pixel points.

[0064] S320: For any current driving parameter, determine whether the current driving parameter is within a corresponding threshold range.

[0065] In this embodiment, the number of current driving parameters is N; the driving weight includes N driving sub-weights, the passenger weight includes N passenger sub-weights, one current driving parameter corresponds to one driving sub-weight and one passenger sub-weight; N is a positive integer greater than or equal to 2; one current driving parameter corresponds to one threshold interval.

[0066] Specifically, taking the value of N as 2, and taking the driving parameters including the first parameter and the second parameter, the first parameter corresponding to the first threshold interval, and the second parameter corresponding to the second threshold interval as an example; then, the first parameter corresponds to a driving sub-weight and a passenger sub-weight, and the sum of the driving sub-weight corresponding to the first parameter and the passenger sub-weight corresponding to the first parameter is 1; the second parameter corresponds to a driving sub-weight and a passenger sub-weight, and the sum of the driving sub-weight corresponding to the second parameter and the passenger sub-weight corresponding to the second parameter is 1.

[0067] If the current driving parameter is within the corresponding threshold interval, that is, yes, then step S321 is executed. If the current driving parameter is not within the corresponding threshold interval, that is, no, then step S322 is executed.

[0068] S321. Determine that the value of the driving sub-weight corresponding to the current driving parameter is not greater than the value of the passenger sub-weight corresponding to the current driving parameter.

[0069] In this embodiment, the sum of the value of the driving sub-weight corresponding to the current driving parameter and the value of the passenger sub-weight corresponding to the current driving parameter is 1.

[0070] Then, if the first parameter is within the first threshold interval, it is determined that the value of the driving sub-weight corresponding to the first parameter is not greater than the value of the passenger sub-weight corresponding to the first parameter; or, if the second parameter is within the second threshold interval, it is determined that the value of the driving sub-weight corresponding to the second parameter is not greater than the value of the passenger sub-weight corresponding to the second parameter.

[0071] Specifically, when N is 2, the driving parameters include speed parameters and steering angle parameters, the threshold interval corresponding to the speed parameters is 15 km / h-60 km / h, and the threshold interval corresponding to the steering angle parameters is -30°-30°. Then, after obtaining the parameter value corresponding to each current driving parameter and performing the operation of judging whether the speed parameter and the steering angle parameter are within the corresponding threshold interval, the value of the driving sub-weight corresponding to the speed parameter and the value of the passenger sub-weight corresponding to the speed parameter can be determined based on the following method, and the value of the driving sub-weight corresponding to the steering angle parameter and the value of the passenger sub-weight corresponding to the steering angle parameter can be determined.

[0072] If the speed parameter is within the corresponding speed range, it is determined that the value of the driving sub-weight corresponding to the speed parameter is not greater than the value of the passenger sub-weight corresponding to the speed parameter, such as the value of the driving sub-weight corresponding to the speed parameter is 0.2, and the value of the passenger sub-weight corresponding to the speed parameter is 0.8.

[0073] If the steering angle parameter is within the corresponding steering interval, it is determined that the value of the driving sub-weight corresponding to the steering angle parameter is not greater than the value of the passenger sub-weight corresponding to the steering angle parameter, such as the value of the driving sub-weight corresponding to the steering angle parameter is 0.1, and the value of the passenger sub-weight corresponding to the steering angle parameter is 0.9, etc.

[0074] The values ​​of the driving sub-weight and the passenger sub-weight corresponding to each specific driving parameter are not limited to the weight distribution methods of 0.2 and 0.8, and 0.1 and 0.9 in the above examples. The values ​​of the driving sub-weight corresponding to different driving parameters and the values ​​of the passenger sub-weight corresponding to different driving parameters can be the same, such as a distribution relationship of 0.2 and 0.8, or they can be different, as long as the relationship that the value of the driving sub-weight corresponding to the current driving parameter is not greater than the value of the passenger sub-weight corresponding to the current driving parameter when the current driving parameter is within the corresponding threshold range is satisfied.

[0075] S322. Determine whether the value of the driving sub-weight corresponding to the current driving parameter is greater than the value of the passenger sub-weight corresponding to the current driving parameter.

[0076] If the first parameter is not within the first threshold interval, it is determined that the value of the driving sub-weight corresponding to the first parameter is greater than the value of the passenger sub-weight corresponding to the first parameter; or, if the second parameter is within the second threshold interval, it is determined that the value of the driving sub-weight corresponding to the second parameter is greater than the value of the passenger sub-weight corresponding to the second parameter.

[0077] Continuing with the example of step S231 above, if the speed parameter is not within the corresponding speed range, it is determined that the value of the driving sub-weight corresponding to the speed parameter is greater than the value of the passenger sub-weight corresponding to the speed parameter, such as the value of the driving sub-weight corresponding to the speed parameter is 0.9, and the value of the passenger sub-weight corresponding to the speed parameter is 0.1.

[0078] If the steering angle parameter is not within the corresponding steering interval, it is determined that the value of the driving sub-weight corresponding to the steering angle parameter is greater than the value of the passenger sub-weight corresponding to the steering angle parameter, such as the value of the driving sub-weight corresponding to the steering angle parameter is 0.8, and the value of the passenger sub-weight corresponding to the steering angle parameter is 0.2, etc.

[0079] According to the examples of step S231 and step S232, it can be concluded that under the same driving parameters, when the current driving parameters are within the corresponding threshold interval, the corresponding values ​​of the driving sub-rights and the passenger sub-weights, and when the current driving parameters are not within the corresponding threshold interval, the corresponding values ​​of the driving sub-rights and the passenger sub-weights only need to keep the sum of the corresponding sub-weights to be 1.

[0080] It should be noted that when the number of current driving parameters is greater than or equal to 2, whether each driving parameter exceeds the corresponding threshold interval does not change synchronously. For example, when the speed parameter exceeds the corresponding threshold interval, the steering angle parameter may not exceed the corresponding threshold interval. In this case, when the driving weight and the passenger weight are determined based on the current driving parameters, it can be determined that the value of the driving sub-weight corresponding to the speed parameter is greater than the value of the passenger sub-weight corresponding to the speed parameter, and the value of the driving sub-weight corresponding to the steering angle parameter is not greater than the value of the passenger sub-weight corresponding to the steering angle parameter.

[0081] S330, obtaining N feature images.

[0082] A feature image is obtained by weighting the pixel values ​​corresponding to the driving pixel points by a driving sub-weight corresponding to the current driving parameter and by weighting the pixel values ​​corresponding to the passenger pixel points by a passenger sub-weight corresponding to the current driving parameter.

[0083] After determining the driving sub-weight and the passenger sub-weight corresponding to each driving parameter under the current driving parameters, weighted calculations are performed on the pixel values ​​corresponding to the driving pixel points according to the driving sub-weight corresponding to each driving parameter, and weighted calculations are performed on the pixel values ​​corresponding to the passenger pixel points according to the passenger sub-weight corresponding to each driving parameter, and the corresponding N feature images can be obtained.

[0084] For example, the current in-vehicle image is an RGB image, and the number of current driving parameters is 3, such as vehicle speed parameter, acceleration parameter and steering angle parameter. In the current step, the RGB value of each driving pixel point can be weighted according to the driving sub-weight corresponding to the vehicle speed parameter, and the RGB value of each passenger pixel point can be weighted according to the passenger sub-weight corresponding to the vehicle speed parameter to obtain a vehicle speed feature image; the RGB value of each driving pixel point can be weighted according to the driving sub-weight corresponding to the acceleration parameter, and the RGB value of each passenger pixel point can be weighted according to the passenger sub-weight corresponding to the acceleration parameter to obtain an acceleration feature image; the RGB value of each driving pixel point can be weighted according to the driving sub-weight corresponding to the steering angle parameter, and the RGB value of each passenger pixel point can be weighted according to the passenger sub-weight corresponding to the steering angle parameter to obtain a steering angle feature image. That is, each feature image contains features corresponding to the corresponding driving parameters.

[0085] S331. Perform feature calculation on N feature images to obtain a driving fusion image.

[0086] A preferred implementation method, in this embodiment, feature calculation is performed on N feature images to obtain a driving fusion image; the pixel mean of each pixel in each feature image is calculated separately to obtain the fusion feature corresponding to each feature image; and the driving fusion image is obtained based on the fusion features corresponding to all feature images.

[0087] That is, in the above step S330 example, after obtaining the vehicle speed feature image, the acceleration feature image and the steering angle feature image, each feature image is an RGB image containing the corresponding features of the corresponding driving parameters. In the current step, the pixel mean of each pixel in each feature image is calculated. Specifically, the pixel mean of each pixel in each feature image is calculated by adding the RGB pixel values ​​of each position and dividing by 3 to obtain the average, and the original three-layer image information (R / G / B) is converted into one layer. In the current step, after performing feature calculations on the three feature images respectively, three fused features can be obtained, and then the three fused features can be stacked to obtain a driving fusion image. Preferably, this embodiment sets the number of current driving parameters to 3, so that the number of output fused features is the same as the number of image channels (R / G / B) of the original input, so it can be migrated to various existing image feature extraction frameworks at zero cost.

[0088] Another preferred embodiment, after determining the whole vehicle behavior according to the driving and riding fusion image, further includes:

[0089] Determine at least one target hardware information to be linked according to the whole vehicle behavior; call the target hardware device corresponding to the at least one target hardware information to provide the corresponding linkage service based on the at least one target hardware device. The purpose of this is to provide the driver and passengers with corresponding in-vehicle linkage services under the whole vehicle behavior through the at least one target hardware device, so as to improve the driving experience on the basis of improving the driver's safe driving ability.

[0090] Specifically, for example, taking the identification of the emotion of the whole vehicle as an example, the expressions of happiness, calmness, sadness, anger, tension, etc. in the whole vehicle can be identified based on the driving and riding fusion image support. Then, when it is determined that the emotion of the whole vehicle is an emotion that affects driving safety, at least one target hardware information to be linked can be the information of the voice broadcast module, so as to provide a safety warning based on the voice broadcast module, and put the current vehicle in a first-level warning state on the server side, so as to obtain the vehicle position of the current vehicle, so as to provide a safe driving warning to other vehicles around the current vehicle, so as to prevent the dangerous behavior of the current vehicle from involving other vehicles, etc.; when it is determined that the emotion of the whole vehicle is happy, calm or sad, at least one target hardware information to be linked can be the information of the music broadcast module, so as to provide a corresponding music playlist based on the music broadcast module, so as to adjust the atmosphere of the whole vehicle by playing music, etc.

[0091] For another example, taking the identification of whether the vehicle is driving fatigue as an example, if the driver's driving behavior is abnormal based on the driving and riding fusion image, corresponding linkage services can be provided based on the target hardware device, such as playing refreshing music and voice prompts for fatigue driving to stop and rest, etc. If the driver's driving behavior is abnormal, then the focus is on the passenger experience, such as whether relaxing music or entertainment videos need to be played. Specifically, the type of linkage services provided after the vehicle behavior is determined based on the driving and riding fusion image in this embodiment is not limited here.

[0092] The method for determining the whole vehicle behavior provided in the embodiment of the present application combines the current driving parameters of the vehicle in the driving and riding fusion image, so that when determining the whole vehicle behavior based on the driving and riding fusion image, it is possible to clearly determine whether more attention should be paid to the passenger behavior or the driver behavior at the current moment, and it can accurately reflect the current state of the whole vehicle, which helps to better serve the user based on the determined whole vehicle behavior, thereby achieving the beneficial effect of improving the driving experience.

[0093] Figure 4 is a schematic diagram of the structure of a vehicle behavior determination device provided in an embodiment of the present application, and the device is suitable for executing the vehicle behavior determination method provided in an embodiment of the present application. Figure 4 As shown, the device may specifically include: a parameter acquisition module 410 , a weight determination module 420 and a behavior determination module 430 .

[0094] Among them, the parameter acquisition module 410 is used to obtain the current driving parameters of the vehicle and the current in-vehicle image, the current in-vehicle image includes a driving area and a passenger area, the driving area includes driving pixel points, and the passenger area includes passenger pixel points.

[0095] The weight determination module 420 is used to determine the driving weight and the passenger weight based on the current driving parameters.

[0096] The behavior determination module 430 is used to process the driving pixel points using the driving weights and process the passenger pixel points using the passenger weights to obtain a driving and riding fusion image, so as to determine the whole vehicle behavior according to the driving and riding fusion image.

[0097] The whole vehicle behavior determination device provided in the embodiment of the present application obtains the current driving parameters of the vehicle to determine the corresponding driving weight and passenger weight for the driving area and the passenger area in the current in-vehicle image according to the current driving parameters, and then processes the driving pixel points in the driving area by the driving weight, and processes the passenger pixel points in the passenger area by the passenger weight, so as to obtain a driving and riding fusion image. In this embodiment, since the current driving parameters of the vehicle are combined in the driving and riding fusion image, when determining the whole vehicle behavior according to the driving and riding fusion image, it can be clear whether the passenger behavior or the driver behavior should be paid more attention to at the current moment, and the current state of the whole vehicle can be accurately reflected, which helps to better serve the user according to the determined whole vehicle behavior, thereby achieving the beneficial effect of improving the driving and riding experience.

[0098] In one embodiment, the number of the current driving parameter is at least one; one current driving parameter corresponds to one threshold interval.

[0099] The weight determination module 420 includes a first threshold determination unit and a first weight determination unit.

[0100] The threshold judgment unit is used to judge whether each of the current driving parameters is within a corresponding threshold interval.

[0101] The first weight determination unit is used to determine that the value of the driving weight is not greater than the value of the passenger weight if all the current driving parameters are within the corresponding threshold interval; if any one of the current driving parameters is not within the corresponding threshold interval, determine that the value of the driving weight is greater than the value of the passenger weight; the sum of the value of the driving weight and the value of the passenger weight is 1.

[0102] In one embodiment, the behavior determination module 430 is specifically configured to perform weighted calculation on the driving pixel points according to the driving weight, and perform weighted calculation on the passenger pixel points according to the passenger weight, so as to obtain the driving and riding fusion image.

[0103] In one embodiment, the number of the current driving parameters is N; the driving weight includes N driving sub-weights, the passenger weight includes N passenger sub-weights, one current driving parameter corresponds to one driving sub-weight and one passenger sub-weight; N is a positive integer greater than or equal to 2; one current driving parameter corresponds to one threshold interval.

[0104] The weight determination module 420 includes a second threshold determination unit and a second weight determination unit.

[0105] The second threshold judgment unit is used to judge whether any one of the current driving parameters is within a corresponding threshold interval.

[0106] The second weight determination unit is used to determine that the value of the driving sub-weight corresponding to the current driving parameter is not greater than the value of the passenger sub-weight corresponding to the current driving parameter if the current driving parameter is within the corresponding threshold interval; if the current driving parameter is not within the corresponding threshold interval, determine that the value of the driving sub-weight corresponding to the current driving parameter is greater than the value of the passenger sub-weight corresponding to the current driving parameter; the sum of the value of the driving sub-weight corresponding to the current driving parameter and the value of the passenger sub-weight corresponding to the current driving parameter is 1.

[0107] In one embodiment, the behavior determination module 430 includes a weighted calculation unit and a feature calculation unit.

[0108] Among them, the weighted calculation unit is used to obtain N feature images, and one of the feature images is obtained by weighted calculation of the pixel value corresponding to the driving pixel point by a driving sub-weight corresponding to the current driving parameter, and weighted calculation of the pixel value corresponding to the passenger pixel point by a passenger sub-weight corresponding to the current driving parameter.

[0109] A feature calculation unit is used to perform feature calculation on the N feature images to obtain the driving fusion image.

[0110] In one embodiment, the feature calculation unit is specifically used to calculate the pixel mean of each pixel point in each of the feature images respectively to obtain the fusion feature corresponding to each of the feature images; and obtain the driving fusion image according to the fusion features corresponding to all the feature images.

[0111] In one embodiment, the device further includes an information acquisition module and a linkage service module.

[0112] Among them, the information acquisition module is used to determine at least one target hardware information to be linked according to the whole vehicle behavior.

[0113] The linkage service module is used to call at least one target hardware device corresponding to the target hardware information to provide a corresponding linkage service based on at least one target hardware device.

[0114] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the functional modules described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0115] An embodiment of the present application also provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle behavior determination method described in any embodiment of the present application.

[0116] An embodiment of the present application also provides a computer-readable medium, which stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle behavior determination method described in any embodiment of the present application when executed.

[0117] Reference below Figure 5 , Figure 5 1 is a schematic diagram of the structure of an electronic device for a vehicle behavior determination method provided in an embodiment of the present application, and shows a schematic diagram of the structure of a computer system 500 suitable for implementing the electronic device in an embodiment of the present application. Figure 5 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0118] like Figure 5 As shown, the computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage part 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the system 500 are also stored. The CPU 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0119] The following components are connected to the I / O interface 505: an input section 506 including a keyboard, a mouse, etc.; an output section 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, a modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed, so that a computer program read therefrom is installed into the storage section 508 as needed.

[0120] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 509, and / or installed from the removable medium 511. When the computer program is executed by the central processing unit (CPU) 501, the above-mentioned functions defined in the system of the present application are executed.

[0121] It should be noted that the computer-readable medium shown in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, etc., or any suitable combination of the above.

[0122] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0123] The modules and / or units involved in the embodiments described in the present application may be implemented by software or by hardware. The modules and / or units described may also be provided in a processor, for example, may be described as: a processor including a parameter acquisition module, a weight determination module, and a behavior determination module. The names of these modules do not, in some cases, constitute limitations on the modules themselves.

[0124] As another aspect, the present application also provides a computer-readable medium, which may be included in the device described in the above embodiment; or it may exist independently without being assembled into the device. The above computer-readable medium carries one or more programs. When the above one or more programs are executed by a device, the device includes: obtaining the current driving parameters and the current in-vehicle image of the vehicle, the current in-vehicle image includes a driving area and a passenger area, the driving area includes driving pixels, and the passenger area includes passenger pixels; determining the driving weight and the passenger weight based on the current driving parameters; processing the driving pixels using the driving weight and processing the passenger pixels using the passenger weight to obtain a driving and riding fusion image, so as to determine the whole vehicle behavior according to the driving and riding fusion image.

[0125] According to the technical solution of this embodiment, by obtaining the current driving parameters of the vehicle, the corresponding driving weight and passenger weight are determined for the driving area and the passenger area in the current in-vehicle image according to the current driving parameters, and then the driving pixels in the driving area are processed by the driving weight, and the passenger pixels in the passenger area are processed by the passenger weight, so as to obtain a driving and riding fusion image. In this embodiment, since the current driving parameters of the vehicle are combined in the driving and riding fusion image, when determining the whole vehicle behavior according to the driving and riding fusion image, it can be clear whether the passenger behavior or the driver behavior needs to be paid more attention at the current moment, and the current whole vehicle state can be accurately reflected, which is helpful to better serve the user according to the determined whole vehicle behavior, thereby achieving the beneficial effect of improving the driving and riding experience.

[0126] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A method for determining vehicle behavior, characterized in that: include: Acquire current driving parameters and a current in-vehicle image of the vehicle, wherein the current in-vehicle image includes a driving area and a passenger area, wherein the driving area includes driving pixel points, and the passenger area includes passenger pixel points; determining a driving weight and a passenger weight based on the current driving parameters; Processing the driving pixel points by using the driving weights and processing the passenger pixel points by using the passenger weights to obtain a driving and riding fusion image, so as to determine the whole vehicle behavior according to the driving and riding fusion image; Wherein, the number of the current driving parameters is at least one; one current driving parameter corresponds to one threshold interval; The determining of the driving weight and the passenger weight based on the current driving parameters comprises: Determining whether each of the current driving parameters is within a corresponding threshold interval; if all of the current driving parameters are within the corresponding threshold interval, determining that the value of the driving weight is not greater than the value of the passenger weight; if any of the current driving parameters is not within the corresponding threshold interval, determining that the value of the driving weight is greater than the value of the passenger weight; The sum of the driving weight and the passenger weight is 1.

2. The vehicle behavior determination method according to claim 1, characterized in that: The step of processing the driving pixel points by using the driving weights and processing the passenger pixel points by using the passenger weights to obtain a driving and riding fusion image includes: The driving pixel points are weighted calculated according to the driving weight, and the passenger pixel points are weighted calculated according to the passenger weight to obtain the driving and riding fusion image.

3. The vehicle behavior determination method according to claim 1, characterized in that: After determining the whole vehicle behavior according to the driving and riding fusion image, the method further includes: Determine at least one target hardware information to be linked according to the whole vehicle behavior; At least one target hardware device corresponding to the target hardware information is called to provide a corresponding linkage service based on the at least one target hardware device.

4. A method for determining vehicle behavior, characterized in that: include: Acquire current driving parameters and a current in-vehicle image of the vehicle, wherein the current in-vehicle image includes a driving area and a passenger area, wherein the driving area includes driving pixel points, and the passenger area includes passenger pixel points; determining a driving weight and a passenger weight based on the current driving parameters; Processing the driving pixel points by using the driving weights and processing the passenger pixel points by using the passenger weights to obtain a driving and riding fusion image, so as to determine the whole vehicle behavior according to the driving and riding fusion image; The number of the current driving parameters is N; the driving weight includes N driving sub-weights, the passenger weight includes N passenger sub-weights, one current driving parameter corresponds to one driving sub-weight and one passenger sub-weight; N is a positive integer greater than or equal to 2; one current driving parameter corresponds to one threshold interval; The determining of the driving weight and the passenger weight based on the current driving parameters comprises: For any one of the current driving parameters, determining whether the current driving parameter is within a corresponding threshold range; If the current driving parameter is within the corresponding threshold range, determining that the value of the driving sub-weight corresponding to the current driving parameter is not greater than the value of the passenger sub-weight corresponding to the current driving parameter; If the current driving parameter is not within the corresponding threshold interval, determining that the value of the driving sub-weight corresponding to the current driving parameter is greater than the value of the passenger sub-weight corresponding to the current driving parameter; The sum of the value of the driving sub-weight corresponding to the current driving parameter and the value of the passenger sub-weight corresponding to the current driving parameter is 1.

5. The vehicle behavior determination method according to claim 4, characterized in that: The step of processing the driving pixel points by using the driving weights and processing the passenger pixel points by using the passenger weights to obtain a driving and riding fusion image includes: Acquire N feature images, wherein one feature image is obtained by weighting the pixel value corresponding to the driving pixel point using a driving sub-weight corresponding to the current driving parameter and weighting the pixel value corresponding to the passenger pixel point using a passenger sub-weight corresponding to the current driving parameter; Feature calculation is performed on the N feature images to obtain the driving fusion image.

6. The vehicle behavior determination method according to claim 5, characterized in that: The performing feature calculation on the N feature images to obtain the driving fusion image includes: Calculate the pixel mean of each pixel in each of the feature images respectively to obtain the fusion feature corresponding to each of the feature images; Obtaining the driving fusion image according to the fusion features corresponding to all the feature images; The step of respectively calculating the pixel mean of each pixel in each of the feature images comprises: Acquire three layers of image information corresponding to each pixel point in each of the feature images, wherein the three layers of image information include an R pixel value, a G pixel value, and a B pixel value; The R pixel value, the G pixel value and the B pixel value are averaged to obtain a pixel mean value of each pixel point.

7. The vehicle behavior determination method according to claim 4, characterized in that: After determining the whole vehicle behavior according to the driving and riding fusion image, the method further includes: Determine at least one target hardware information to be linked according to the whole vehicle behavior; At least one target hardware device corresponding to the target hardware information is called to provide a corresponding linkage service based on the at least one target hardware device.

8. A vehicle behavior determination device, characterized in that: include: A parameter acquisition module, used to acquire current driving parameters of the vehicle and a current in-vehicle image, wherein the current in-vehicle image includes a driving area and a passenger area, wherein the driving area includes driving pixel points, and the passenger area includes passenger pixel points; A weight determination module, configured to determine a driving weight and a passenger weight based on the current driving parameters; a behavior determination module, configured to process the driving pixel points using the driving weights and process the passenger pixel points using the passenger weights to obtain a driving and riding fusion image, so as to determine the whole vehicle behavior according to the driving and riding fusion image; Wherein, the number of the current driving parameters is at least one; one current driving parameter corresponds to one threshold interval; The weight determination module has a first threshold judgment unit and a first weight determination unit; The first threshold determination unit is used to determine whether each of the current driving parameters is within a corresponding threshold interval; The first weight determination unit is used to determine that the value of the driving weight is not greater than the value of the passenger weight if all the current driving parameters are within the corresponding threshold interval; if any one of the current driving parameters is not within the corresponding threshold interval, determine that the value of the driving weight is greater than the value of the passenger weight; the sum of the value of the driving weight and the value of the passenger weight is 1.

9. A vehicle behavior determination device, characterized in that: include: A parameter acquisition module, used to acquire current driving parameters of the vehicle and a current in-vehicle image, wherein the current in-vehicle image includes a driving area and a passenger area, wherein the driving area includes driving pixel points, and the passenger area includes passenger pixel points; A weight determination module, configured to determine a driving weight and a passenger weight based on the current driving parameters; a behavior determination module, configured to process the driving pixel points using the driving weights and process the passenger pixel points using the passenger weights to obtain a driving and riding fusion image, so as to determine the whole vehicle behavior according to the driving and riding fusion image; The number of the current driving parameters is N; the driving weight includes N driving sub-weights, the passenger weight includes N passenger sub-weights, one current driving parameter corresponds to one driving sub-weight and one passenger sub-weight; N is a positive integer greater than or equal to 2; one current driving parameter corresponds to one threshold interval; The weight determination module includes a second threshold judgment unit and a second weight determination unit; The second threshold judgment unit is used to judge whether any one of the current driving parameters is within a corresponding threshold interval; The second weight determination unit is used to determine that the value of the driving sub-weight corresponding to the current driving parameter is not greater than the value of the passenger sub-weight corresponding to the current driving parameter if the current driving parameter is within the corresponding threshold interval; if the current driving parameter is not within the corresponding threshold interval, determine that the value of the driving sub-weight corresponding to the current driving parameter is greater than the value of the passenger sub-weight corresponding to the current driving parameter; The sum of the value of the driving sub-weight corresponding to the current driving parameter and the value of the passenger sub-weight corresponding to the current driving parameter is 1.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor, and a memory communicatively coupled to the at least one processor; Wherein, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle behavior determination method described in any one of claims 1-3.

11. An electronic device, characterized in that: The electronic device comprises: at least one processor, and a memory communicatively coupled to the at least one processor; Wherein, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle behavior determination method described in any one of claims 4-7.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the vehicle behavior determination method as described in any one of claims 1 to 3 is implemented.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the vehicle behavior determination method as described in any one of claims 4 to 7 is implemented.

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