An intelligent light control method and system for automotive interior

Abstract

The application provides a kind of car interior intelligent light control method and system, it is related to car interior intelligent light control technical field, wherein the method comprises: obtaining the influence information of car interior lamp to driver future driving car;Based on the influence information, decision influence elimination light control scheme;Based on influence elimination light control scheme, control car interior lamp.The application obtains the influence information of car interior lamp to driver future driving car, based on its decision influence elimination light control scheme, finally based on the influence elimination light control scheme of decision, control car interior lamp, realize real-time elimination of the influence of car interior lamp to driver future driving car, avoid affecting the visual comfort and sensory experience of driver, more avoid increasing driving risk.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent light control of automotive interior, and particularly relates to an intelligent light control method and system for automotive interior. BACKGROUND

[0002] Automotive interior light may have an impact on the eyes of the driver, especially at night or in complex driving environments, and too strong or inappropriate light may cause the driver's vision to be unclear, thereby affecting his judgment and reaction speed, and ultimately posing a potential threat to driving safety.

[0003] Traditional automotive interior light relies on manual adjustment by the driver, and lacks an intelligent light control solution to eliminate the impact of automotive interior light on the driver's driving of the vehicle, which not only may affect the visual comfort and sensory experience of the driver, but also may increase the driving risk in some cases.

[0004] Therefore, there is an urgent need for a solution. SUMMARY

[0005] One of the purposes of the present application is to provide an intelligent light control method and system for automotive interior to solve the problems in the background art.

[0006] The intelligent light control method for automotive interior provided by the embodiments of the present application comprises:

[0007] obtaining impact information of the automotive interior light on the driver's future driving of the vehicle;

[0008] based on the impact information, deciding an impact-eliminating light control solution;

[0009] based on the impact-eliminating light control solution, controlling the automotive interior light.

[0010] Optionally, the step of obtaining the impact information comprises:

[0011] based on the future driving route of the vehicle, determining the outside view and the inside view that the driver should have at different times in the future;

[0012] predicting the outside view and the inside view that the driver should have at different times in the future, obtaining the outside view and the inside view predicted to mutate at different times in the future;

[0013] taking the environmental lighting features of the outside view predicted to mutate at each same time and the interior light lighting features of the inside view predicted to mutate as the impact information.

[0014] Optionally, the step of determining the outside view and the inside view that the driver should have at different times in the future comprises:

[0015] determining driving positions and driving directions of the driver at different future time points based on a future driving route of the vehicle;

[0016] determining driving visual fields at different time points based on the driving visual field determination template and the driving positions and driving directions at the different time points;

[0017] dividing the driving visual fields at the different time points into in-vehicle fields and out-of-vehicle fields to obtain the out-of-vehicle fields and the in-vehicle fields that should be provided at the different time points.

[0018] Optionally, the step of mutation prediction comprises:

[0019] determining a visual field mutation cause target at the i-th time point based on the portrait of the driver and the passengers and the road features of the vehicle at the previous i-1 time points;

[0020] when the out-of-vehicle field that should be provided at the i-th time point contains the visual field mutation cause target, modifying the out-of-vehicle fields that should be provided at the i+1-th to i+j-th time points and, in the process of modification, modifying the in-vehicle fields that should be provided at the i+1-th to i+j-th time points in linkage;

[0021] based on the modified out-of-vehicle fields and the in-vehicle fields modified in linkage, replacing the out-of-vehicle fields and the in-vehicle fields that should be provided at the different time points to obtain the out-of-vehicle fields and the in-vehicle fields that should be provided at the different time points after mutation prediction;

[0022] wherein one side boundary region of the modified out-of-vehicle field in the horizontal direction completely contains the safe driving visual field that should be provided by the driver at the corresponding time point, and the other side boundary region completely contains the visual field mutation cause target;

[0023] the in-vehicle field modified in linkage can be aligned and spliced with the modified out-of-vehicle field at the same time point;

[0024] starting from the i+j+1-th time point, the visual field mutation cause target is out of the visible visual field of the vehicle, so that the value of j is unique.

[0025] Optionally, the step of determining the visual field mutation cause target at the i-th time point comprises:

[0026] based on the portrait of the driver and the passengers and the road features of the vehicle at the previous i-1 time points, constructing a first matching factor;

[0027] based on the first matching factor, matching the visual field mutation cause target at the i-th time point from a visual field mutation cause target library.

[0028] Optionally, the step of obtaining the environmental lighting features comprises:

[0029] based on the out-of-vehicle field after mutation prediction, constructing a second matching factor;

[0030] matching the environment lighting feature from the environment lighting feature big data platform based on the second matching factor.

[0031] Optionally, the decision step of the influence-eliminating lamp control scheme comprises:

[0032] constructing a third matching factor based on the influence information;

[0033] matching the influence-eliminating lamp control scheme from the influence-eliminating lamp control scheme library based on the third matching factor.

[0034] An automobile interior intelligent lamp control system is provided in the embodiment of the application, comprising:

[0035] an influence information acquisition module, configured to acquire influence information of the automobile interior lamp on future driving of the driver;

[0036] an influence-eliminating lamp control scheme decision module, configured to decide the influence-eliminating lamp control scheme based on the influence information;

[0037] an automobile interior lamp control module, configured to control the automobile interior lamp based on the influence-eliminating lamp control scheme.

[0038] Optionally, the acquisition step of the influence information comprises:

[0039] determining the outside view and the inside view that the driver should have at different times in the future based on the future driving route of the automobile;

[0040] carrying out mutation prediction on the outside view and the inside view that the driver should have at different times to obtain the outside view and the inside view that the driver should have at different times after mutation prediction;

[0041] taking the environment lighting feature of the outside view and the interior lamp lighting feature of the inside view that are predicted to mutate at each same time as the influence information.

[0042] Optionally, the determination step of the outside view and the inside view that the driver should have at different times comprises:

[0043] determining the driving position and the driving direction of the driver at different times in the future based on the future driving route of the automobile;

[0044] determining the driving view at different times according to the respective driving position and the driving direction at different times based on a driving view determination template;

[0045] dividing the inside and outside of the automobile in the driving view at different times to obtain the outside view and the inside view that the driver should have at different times.

[0046] Optionally, the mutation prediction step comprises:

[0047] determine the field-of-view mutation cause target at the i-th time point based on the images of the driver and the passengers and the road features of the vehicle at the previous i-1 time points;

[0048] When the field-of-view mutation cause target exists in the field-of-view outside the vehicle that should be possessed at the i-th time point, the field-of-view outside the vehicle that should be possessed at the i+1-th to i+j-th time points is modified, and during the modification process, the field-of-view inside the vehicle that should be possessed at the i+1-th to i+j-th time points is modified in linkage;

[0049] based on the modified field-of-view outside the vehicle and the modified field-of-view inside the vehicle in linkage, the field-of-view outside the vehicle and the field-of-view inside the vehicle that should be possessed at different time points are replaced accordingly, and the field-of-view outside the vehicle and the field-of-view inside the vehicle that should be possessed at different time points are obtained through mutation prediction;

[0050] wherein one side boundary region of the modified field-of-view outside the vehicle in the horizontal direction completely contains the safe driving field-of-view that the driver should possess at the corresponding time point, and the other side boundary region completely contains the field-of-view mutation cause target;

[0051] The modified field-of-view inside the vehicle in linkage can be aligned and spliced with the modified field-of-view outside the vehicle at the same time point;

[0052] Starting from the i+j+1-th time point, the field-of-view mutation cause target leaves the visible field-of-view of the vehicle, so that the value of j is unique.

[0053] Optionally, the determination step of the field-of-view mutation cause target at the i-th time point comprises:

[0054] based on the images of the driver and the passengers and the road features of the vehicle at the previous i-1 time points, a first matching factor is constructed;

[0055] based on the first matching factor, the field-of-view mutation cause target at the i-th time point is matched from a field-of-view mutation cause target library.

[0056] Optionally, the obtaining step of the environmental lighting features comprises:

[0057] based on the field-of-view outside the vehicle through mutation prediction, a second matching factor is constructed;

[0058] based on the second matching factor, the environmental lighting features are matched from an environmental lighting feature big data platform.

[0059] Optionally, the decision step of the influence elimination lamp control scheme comprises:

[0060] based on the influence information, a third matching factor is constructed;

[0061] based on the third matching factor, the influence elimination lamp control scheme is matched from an influence elimination lamp control scheme library.

[0062] The computer readable storage medium provided by the embodiment of the present application stores a computer program, and a processor executes the computer program to realize the method according to any one of the above.

[0063] The electronic device provided by the embodiment of the present application comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to realize the method according to any one of the above.

[0064] The present application has the following advantages:

[0065] The influence information of the automotive interior lamp on the driver's future driving of the automobile is acquired, the lamp control scheme is eliminated based on the influence of the decision, and finally the automotive interior lamp is controlled based on the lamp control scheme eliminated based on the influence of the decision, so that the influence of the automotive interior lamp on the driver's future driving of the automobile is eliminated in real time, the visual comfort and sensory experience of the driver are avoided to be affected, and the driving risk is avoided to be increased.

[0066] Other features and advantages of the present application will be described in the following description, and some will become apparent from the description, or will be learned by practice of the present application. The purpose and other advantages of the present application can be achieved and obtained by the structure specifically pointed out in the written description and the accompanying drawings.

[0067] The technical solutions of the present application will be further described in detail below with the help of the accompanying drawings and embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0068] The accompanying drawings are used to provide a further understanding of the present application, and constitute a part of the specification, and are used to explain the present application together with the embodiments of the present application, and do not constitute a limitation to the present application. In the drawings:

[0069] Figure 1 It is a schematic diagram of the automotive interior intelligent lamp control method in the embodiment of the present application.

[0070] Figure 2 It is a schematic diagram of the automotive interior intelligent lamp control system in the embodiment of the present application. DETAILED DESCRIPTION

[0071] The preferred embodiments of the present application will be described below in combination with the accompanying drawings, and it should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and do not limit the present application.

[0072] Embodiment 1:

[0073] The embodiment of the present application provides an automotive interior intelligent lamp control method, as shown in the figure, comprising: Figure 1

[0074] ​S1, acquire influence information of the automotive interior light on the driver's future driving of the vehicle;

[0075] S2, based on the influence information, decide an influence-eliminating light control scheme;

[0076] S3, based on the influence-eliminating light control scheme, control the automotive interior light.

[0077] When the automotive interior light is turned on during driving, the influence information is acquired, the influence information is the influence of the automotive interior light on the driver's future driving of the vehicle, based on which the influence-eliminating light control scheme is decided, the influence-eliminating light control scheme is a scheme of intelligently controlling the automotive interior light to eliminate its influence on the driver's future driving of the vehicle, finally, based on the influence-eliminating light control scheme, the automotive interior light is controlled.

[0078] The present application acquires the influence information of the automotive interior light on the driver's future driving of the vehicle, decides the influence-eliminating light control scheme based on the influence information, and finally controls the automotive interior light based on the decided influence-eliminating light control scheme, thereby realizing real-time elimination of the influence of the automotive interior light on the driver's future driving of the vehicle, avoiding affecting the driver's visual comfort and sensory experience, and further avoiding increasing the driving risk.

[0079] Embodiment 2:

[0080] In one embodiment, the step of acquiring the influence information comprises:

[0081] Based on the future driving route of the vehicle, determining the outside view and the inside view that the driver should have at different times in the future;

[0082] Performing mutation prediction on the outside view and the inside view that the driver should have at different times to obtain the mutation-predicted outside view and the mutation-predicted inside view at different times;

[0083] Taking the environmental lighting features of the mutation-predicted outside view and the interior light lighting features of the mutation-predicted inside view at each same time as the influence information.

[0084] Before starting the car, the driver will use the mobile phone or the car machine to navigate the destination, and then the future driving route of the car is generated. During the driving process, the driver sits in the driving seat, and the driving field of view is determined by the position and driving direction of the car. The future driving route can indicate the position and driving direction of the car at different future time points, so the driving field of view that the driver should have at different future time points can be determined, and then the inside and outside of the car are divided to obtain the outside field of view and the inside field of view that the driver should have at different future time points. However, the outside field of view and the inside field of view that the driver should have may change suddenly in the future, for example, the driver sees a building of his interest during driving, and then he will take a look at the building on the premise of ensuring driving safety, at this time, the outside field of view and the inside field of view that he should have will change suddenly. Therefore, in order to make the influence information accurate, the outside field of view and the inside field of view that should be had at different time points are predicted to change suddenly. The influence information is used for decision-making of the influence elimination lamp control scheme. The decision-making idea is to determine the suitable interior lamp lighting features of the inside field of view at the same time based on the environmental lighting features of the outside field of view, and then determine how to correct the actual interior lamp lighting features of the inside field of view based on this, and the correction result is the influence elimination lamp control scheme. Therefore, the environmental lighting features of the outside field of view and the interior lamp lighting features of the inside field of view predicted to change suddenly at the same time are taken as the influence information. Specifically, the environmental lighting features at least include external light intensity, ambient light color temperature, etc., and the interior lamp lighting features at least include interior lamp brightness, interior lamp color, etc.

[0085] The embodiment of the present application determines the outside field of view and the inside field of view that the driver should have at different future time points based on the future driving route of the car, further predicts the change of the outside field of view and the inside field of view, and thus accurately obtains the influence information, which can improve the suitability of the decision-making of the influence elimination lamp control scheme, ensure that the lighting features of the inside and outside of the car are suitable to each other after the implementation of the scheme, and improve the driving safety and comfort.

[0086] Embodiment 3:

[0087] In one embodiment, the determination step of the outside field of view and the inside field of view that should be had at different time points includes:

[0088] Based on the future driving route of the car, the driving position and driving direction of the driver at different future time points are determined;

[0089] Based on the driving field of view determination template, the driving field of view at different time points is determined according to the respective driving position and driving direction at different time points;

[0090] The inside and outside of the car at different time points are divided to obtain the outside field of view and the inside field of view that should be had at different time points.

[0091] The driving field of view determination template includes: when the automobile is located at a driving position and the automobile head direction is towards the corresponding driving direction, the sum of the field of view of the driver looking at the automobile front shield from the seat and looking at the driver seat side door window as the driving field of view. The driving field of view determination template can also be set by the technician according to the actual needs. When the inside and outside of the automobile is divided, the field of view of the outside part of the driving field of view is regarded as the outside field of view that should be possessed (such as the road range), and the field of view of the inside part is regarded as the inside field of view that should be possessed (such as the instrument panel range, the automobile machine large screen range, the center console range, the driver seat side door inside range, etc.).

[0092] The embodiment of the application introduces the driving field of view determination template, determines the driving field of view at different times based on the respective driving positions and driving directions at different times, and then divides the inside and outside of the automobile, to obtain the outside field of view and the inside field of view that should be possessed at different times, thereby improving the accuracy and efficiency of the determination of the outside field of view and the inside field of view that should be possessed at different times.

[0093] Embodiment 4:

[0094] In one embodiment, the step of mutation prediction includes:

[0095] Based on the portrait of the driver and the passenger and the road characteristics of the automobile at the previous i-1 time, the field of view mutation reason target at the i time is determined;

[0096] When the outside field of view that should be possessed at the i time exists the field of view mutation reason target, the respective outside field of view that should be possessed at the i+1 time to the i+j time is corrected, and in the correction process, the respective inside field of view that should be possessed at the i+1 time to the i+j time is corrected in linkage;

[0097] Based on the corrected outside field of view and the inside field of view corrected in linkage, the outside field of view and the inside field of view that should be possessed at different times are replaced correspondingly, to obtain the outside field of view and the inside field of view that should be possessed at different times after mutation prediction;

[0098] The corrected outside field of view is completely contained in the safe driving field of view that should be possessed by the driver at the corresponding time in the horizontal direction on one side boundary area, and the other side boundary area is completely contained in the field of view mutation reason target;

[0099] The inside field of view corrected in linkage can be aligned and spliced with the outside field of view corrected at the same time;

[0100] From the i+j+1 time, the field of view mutation reason target leaves the visible field of view of the automobile, so that the value of j is unique. i is greater than or equal to 2, j is greater than or equal to 1, and i+j+1 is less than or equal to N; N is the total number of times.

[0101] The view mutation reason target of the ith moment is a target of causing the driver to actively change the respective required view outside the vehicle and the view inside the vehicle at the ith+1th moment to the ijth moment, which is determined by the images of the driver and the passengers and the road features of the vehicle at the previous i-1th moment. For example, the images indicate that the driver and the passengers arrive at the current city for the first time, and the travel purpose is tourism. The road features indicate that the vehicle passes a sign of a certain ancient architectural scenic spot. The view mutation reason target is the ancient architectural scenic spot. For another example, the road features indicate that the vehicle is about to pass the gate of a certain school. The driver will pay special attention to the student traffic. The view mutation reason target is the student traffic channel on the road.

[0102] When the view mutation reason target exists in the required view outside the vehicle at the ith moment, it indicates that the driver will notice the view mutation reason target at the ith moment. The subsequent view will be mutated until the view mutation reason target begins to leave the visible view of the vehicle (the visible view is the entire view outside the vehicle through each window of the vehicle). Therefore, the respective required view outside the vehicle and the view inside the vehicle at the ith+1th moment to the ijth moment need to be corrected. After each correction, the respective required view outside the vehicle and the view inside the vehicle at different moments are replaced accordingly based on the corrected view outside the vehicle and the view inside the vehicle after linkage correction, to obtain the predicted view outside the vehicle and the view inside the vehicle after mutation at different moments.

[0103] When correcting the view outside the vehicle, the safe driving view is determined. When the vehicle is located at the driving position at the corresponding moment and the vehicle head direction is towards the corresponding driving direction, the driver looks at the view of a preset proportion (such as 9 / 10) of the seat direction side (such as the left side) of the vehicle front bumper from the seat to obtain the safe driving view. The safe driving view can also be set in advance by the technician according to the actual needs. When the driver views the view mutation reason target, he can view the basic road conditions to continue driving the vehicle by retaining the safe driving view, and view the view mutation reason target as much as possible. Therefore, one side boundary region of the corrected view outside the vehicle in the horizontal direction completely contains the safe driving view that the driver should have at the corresponding moment, and the other side boundary region completely contains the view mutation reason target. The sizes of the two boundary regions can be set in advance by the technician.

[0104] During the correction of the view outside the vehicle, the view inside the vehicle is corrected in linkage, so that the view inside the vehicle after linkage correction can be aligned and spliced with the view outside the vehicle at the same moment. The driving view is composed of the view outside the vehicle and the view inside the vehicle before correction. Therefore, the original can be aligned and spliced. The alignment and splicing are used as a constraint to correct the view inside the vehicle in linkage.

[0105] The embodiment of the application introduces a view mutation reason target when predicting the view outside the vehicle and the view inside the vehicle at different times, modifies the view outside the vehicle at the corresponding continuous time based on the appearance of the view mutation reason target in the view outside the vehicle at the corresponding continuous time, and modifies the view inside the vehicle at the same time, so that the modified view outside the vehicle contains the safe driving view of the driver at the corresponding time on one side in the horizontal direction, and contains the view mutation reason target on the other side, the mutation reason is accurately grasped, the view is modified according to the actual view of the driver, and the accuracy, comprehensiveness and efficiency of the mutation prediction are greatly improved, and the applicability of the system is improved; secondly, the value of j is accurately determined, and the modification pertinence is improved.

[0106] Embodiment 5:

[0107] In one embodiment, the determination step of the view mutation reason target at the i-th time point comprises:

[0108] Based on the portrait of the driver and the passenger and the road characteristics of the vehicle at the previous i-1 time points, a first matching factor is constructed;

[0109] Based on the first matching factor, the view mutation reason target at the i-th time point is matched from the view mutation reason target library.

[0110] The portrait of the driver and the passenger and the road characteristics of the vehicle at the previous i-1 time points are represented in the form of a vector to obtain the first matching factor. Different first matching factors are preset in the view mutation reason target library, and the view mutation reason target at the i-th time point is matched from the library based on the first matching factor. Specifically, for example: the portrait of the first matching factor is that the driver and the passenger arrive in the city for the first time, and the travel purpose is tourism, the road characteristics of the first matching factor is that the vehicle passes through the sign of a certain ancient architectural scenic spot, and the corresponding preset view mutation reason target is the ancient architectural scenic spot.

[0111] The embodiment of the application introduces a view mutation reason target library, and quickly matches the view mutation reason target at the i-th time point from the library based on the first matching factor, thereby improving the determination efficiency of the view mutation reason target at the i-th time point.

[0112] Embodiment 6:

[0113] In one embodiment, the acquisition step of the environmental lighting feature comprises:

[0114] Based on the view outside the vehicle predicted by the mutation, a second matching factor is constructed;

[0115] Based on the second matching factor, the environmental lighting feature is matched from the environmental lighting feature big data platform.

[0116] Correspondingly, the predicted outside view is represented in the form of a vector, and a second matching factor is obtained. The environment lighting feature big data platform has environment lighting features corresponding to different second matching factors. In the environment lighting feature big data platform, a large number of environment lighting features of different city ranges collected by different collection sources (such as a traffic monitoring system, a light pollution monitoring station, an intelligent street lamp, a public facility lighting management system, a street lighting sensor, a vehicle lighting sensor, etc.) are stored. The different collection sources publish the features to the environment lighting feature big data platform through communication sharing.

[0117] The embodiment of the present application introduces the environment lighting feature big data platform, improves the accuracy and efficiency of environment lighting feature acquisition, and improves the applicability of the system.

[0118] Embodiment 7:

[0119] In one embodiment, the decision step of the influence-eliminating lamp control scheme includes:

[0120] Based on the influence information, a third matching factor is constructed.

[0121] Based on the third matching factor, an influence-eliminating lamp control scheme is matched from the influence-eliminating lamp control scheme library.

[0122] Correspondingly, the influence information is represented in the form of a vector, and a third matching factor is obtained. Different influence-eliminating lamp control schemes corresponding to different third matching factors are preset in the influence-eliminating lamp control scheme library. After the third matching factor is determined, the influence-eliminating lamp control scheme is matched from the library based on the third matching factor. Specifically, for example: the influence information for constructing the third matching factor indicates that the car will pass through an area with strong light pollution in a future period of time, the brightness of the interior lamp should be kept as low as possible, and the color tone should be selected to be a dark warm color tone, and then the influence-eliminating lamp control scheme is to locally reduce the brightness of the interior lamp in the driver's field of view in the future period of time and adopt a dark warm color tone. The skilled person can determine the most suitable influence-eliminating lamp control scheme for different influence information through pre-experiment, so as to set the influence-eliminating lamp control scheme library.

[0123] The embodiment of the present application introduces the influence-eliminating lamp control scheme library, and matches the influence-eliminating lamp control scheme from the library based on the third matching factor, thereby improving the accuracy and efficiency of the influence-eliminating lamp control scheme decision, and improving the applicability of the system.

[0124] Embodiment 8:

[0125] The embodiment of the present application provides an automobile interior intelligent lamp control system, as shown in Figure 2 The embodiment of the present application provides an automobile interior intelligent lamp control system, as shown in

[0126] An influence information acquisition module 1 is configured to acquire influence information of the automotive interior light on the driver's future driving of the vehicle.

[0127] An influence elimination light control scheme decision module 2 is configured to decide an influence elimination light control scheme based on the influence information.

[0128] An automotive interior light control module 3 is configured to control the automotive interior light based on the influence elimination light control scheme.

[0129] The acquisition of the influence information includes:

[0130] Based on the future driving route of the vehicle, the driver's future outside view and inside view at different time points are determined.

[0131] The outside view and the inside view at different time points are predicted to obtain the outside view and the inside view at different time points.

[0132] The environmental lighting features of the outside view and the interior lighting features of the inside view at different time points are taken as the influence information.

[0133] The determination of the outside view and the inside view at different time points includes:

[0134] Based on the future driving route of the vehicle, the driving position and the driving direction of the driver at different time points are determined.

[0135] Based on the driving view determination template, the driving view at different time points is determined according to the driving position and the driving direction at different time points.

[0136] The driving view at different time points is divided into inside and outside to obtain the outside view and the inside view at different time points.

[0137] The prediction includes:

[0138] Based on the portrait of the driver and the passengers and the road features of the vehicle at the previous i-1 time points, the view mutation reason target at the i time point is determined.

[0139] When the outside view at the i time point has the view mutation reason target, the outside view at the i+1 to i+j time points is corrected, and the inside view at the i+1 to i+j time points is corrected in the correction process.

[0140] Based on the corrected outside view and the corrected inside view, the outside view and the inside view at different time points are replaced to obtain the outside view and the inside view at different time points.

[0141] wherein the one side boundary region of the corrected outside view field in horizontal direction completely contains the safe driving view field that the driver should have at the corresponding moment, and the other side boundary region completely contains the view mutation cause target;

[0142] The corrected inside view field is connected with the corrected outside view field at the same moment;

[0143] From the i+j+1 moment, the view mutation cause target leaves the visible view field of the vehicle, so that the value of j is unique.

[0144] The determination step of the view mutation cause target at the i moment comprises:

[0145] Based on the portrait of the driver and the passenger, and the road characteristics of the vehicle at the previous i-1 moment, a first matching factor is constructed;

[0146] Based on the first matching factor, the view mutation cause target at the i moment is matched from the view mutation cause target library.

[0147] The acquisition step of the environmental lighting feature comprises:

[0148] Based on the outside view field predicted by mutation, a second matching factor is constructed;

[0149] Based on the second matching factor, the environmental lighting feature is matched from the environmental lighting feature big data platform.

[0150] The decision step of the influence elimination lamp control scheme comprises:

[0151] Based on the influence information, a third matching factor is constructed;

[0152] Based on the third matching factor, the influence elimination lamp control scheme is matched from the influence elimination lamp control scheme library.

[0153] The embodiment of the present application provides a computer readable storage medium, characterized in that the computer readable storage medium stores a computer program, and a processor executes the computer program to realize the method according to any one of the above.

[0154] The embodiment of the present application provides an electronic device, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to realize the method according to any one of the above.

[0155] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. An intelligent light control method for automotive interior, characterized in that, The method comprises the following steps: acquiring influence information of the interior light on the driver's future driving of the vehicle; deciding an influence-eliminating light control scheme based on the influence information; controlling the interior light of the vehicle based on the influence-eliminating light control scheme; the acquiring step of the influence information comprises: determining the outside view and the inside view that the driver should have at different future time points based on the future driving route of the vehicle; performing mutation prediction on the outside view and the inside view that the driver should have at different time points to obtain the outside view and the inside view that the driver should have at different time points after mutation prediction; taking the environmental lighting features of the outside view and the interior light lighting features of the inside view that the driver should have at different time points after mutation prediction as the influence information; the determining step of the outside view and the inside view that the driver should have at different time points comprises: determining the driving position and the driving direction of the driver at different time points based on the future driving route of the vehicle; determining the driving view at different time points according to the driving position and the driving direction at different time points based on a driving view determination template; dividing the driving view at different time points into the outside view and the inside view to obtain the outside view and the inside view that the driver should have at different time points; the mutation prediction step comprises: determining a view mutation cause target at the i-th time point based on the portrait of the driver and the passengers and the road features of the vehicle at the previous i-1 time points; when the outside view that the driver should have at the i-th time point contains the view mutation cause target, correcting the outside view that the driver should have at the i+1-th to i+j-th time points, and in the correction process, performing linkage correction on the inside view that the driver should have at the i+1-th to i+j-th time points; replacing the outside view and the inside view that the driver should have at different time points with the corrected outside view and the linkage-corrected inside view to obtain the outside view and the inside view that the driver should have at different time points after mutation prediction; wherein one side boundary region of the corrected outside view in the horizontal direction completely contains the safe driving view that the driver should have at the corresponding time point, and the other side boundary region completely contains the view mutation cause target; the linkage-corrected inside view is aligned and spliced with the corrected outside view at the same time point; starting from the i+j+1-th time point, the view mutation cause target is out of the visible view of the vehicle, so that the value of j is unique.

2. The automotive interior smart light control method of claim 1, wherein, the determining step of the view mutation cause target at the i-th time point comprises: constructing a first matching factor based on the portrait of the driver and the passengers and the road features of the vehicle at the previous i-1 time points; matching the view mutation cause target at the i-th time point from a view mutation cause target library based on the first matching factor.

3. The intelligent light control method for automotive interior according to claim 1, wherein, the acquiring step of the environmental lighting features comprises: constructing a second matching factor based on the outside view after mutation prediction; matching the environmental lighting features from an environmental lighting feature big data platform based on the second matching factor.

4. The intelligent light control method for automotive interior according to claim 1, wherein, the deciding step of the influence-eliminating light control scheme comprises: constructing a third matching factor based on the influence information; matching the influence-eliminating light control scheme from an influence-eliminating light control scheme library based on the third matching factor.

5. An automotive interior smart light control system, characterized in that, The method comprises the following steps: an influence information acquisition module is configured to acquire influence information of the interior light of the vehicle on the driver's future driving of the vehicle; An influence elimination lamp control scheme decision module is configured to decide an influence elimination lamp control scheme based on the influence information; An automotive interior lamp control module is configured to control the automotive interior lamp based on the influence elimination lamp control scheme; The influence information is obtained by: determining the outside view and the inside view that the driver should have at different future time points based on the future driving route of the vehicle; predicting the outside view and the inside view that the driver should have at different time points based on the outside view and the inside view that the driver should have at different time points; taking the environmental lighting features of the outside view and the interior lamp lighting features of the inside view that are predicted at the same time point as the influence information; The determination of the outside view and the inside view that the driver should have at different time points includes: determining the driving position and the driving direction of the driver at different time points based on the future driving route of the vehicle; determining the driving view at different time points based on the driving view determination template and the driving position and the driving direction at different time points; dividing the inside and outside of the vehicle in the driving view at different time points to obtain the outside view and the inside view that the driver should have at different time points; The step of predicting the outside view and the inside view that the driver should have at different time points includes: determining the view mutation reason target at the i-th time point based on the portrait of the driver and the passengers and the road features of the vehicle at the previous i-1 time points; when the outside view that the driver should have at the i-th time point contains the view mutation reason target, modifying the outside view that the driver should have at the i+1-th to i+j-th time points, and in the process of modification, modifying the inside view that the driver should have at the i+1-th to i+j-th time points in linkage; replacing the outside view and the inside view that the driver should have at different time points based on the modified outside view and the inside view that the driver should have at different time points in linkage, to obtain the outside view and the inside view that the driver should have at different time points in prediction; wherein one side boundary region of the modified outside view in the horizontal direction completely contains the safe driving view that the driver should have at the corresponding time point, and the other side boundary region completely contains the view mutation reason target; the inside view that the driver should have at the corresponding time point is aligned and spliced with the modified outside view at the corresponding time point; starting from the i+j+1-th time point, the view mutation reason target is out of the visible view of the vehicle, so that the value of j is unique.

6. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the processor executes the computer program to implement the method of any one of claims 1-4.

7. An electronic device, comprising: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the method of any one of claims 1-4.

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