Intelligent vehicle light control method and system

Abstract

The present invention discloses an intelligent vehicle light control method and system, and specifically relates to the field of intelligent control technology. The present invention uses a 4K high-resolution high-definition camera to collect images of the environment in front of a vehicle to ensure coverage of lanes, road markings and traffic signs; then, the interfering light source is eliminated, and the lane line elements are processed using a fitting algorithm to identify the effective data of the target vehicle light source; then, the road conditions are analyzed, including straight and turning roads, and the current driving conditions are judged by calculating the road curvature index; next, the vehicle light deflection angle is calculated according to the curvature index and the vehicle wheelbase, and the angle is transmitted to a controller; at the same time, based on the driving speed and the ambient light brightness, the illumination value of the vehicle light is controlled to achieve intelligent adjustment of different brightness levels; finally, the controller dynamically adjusts the brightness and illumination direction of the vehicle light according to real-time data.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and more particularly, to an intelligent vehicle light control method and system. Background Art

[0002] With the rapid development of the automotive industry and advancements in technology, improving vehicle safety has become a common focus for manufacturers and consumers. Among the many safety factors, the function of the vehicle lighting system is crucial. It not only provides the necessary vision for nighttime driving but also ensures the accurate transmission and use of vehicle signals.

[0003] However, in actual use, there are still some shortcomings. For example, existing lighting systems, such as halogen lamps and xenon lamps, although they provide basic lighting functions, lack flexibility and intelligence; for example, they cannot automatically adjust the distribution and intensity of light according to the curvature of the road and the turning of the vehicle. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide an intelligent vehicle light control method and system to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] Step S1: using a high-definition camera to collect image data of the vehicle headlight's external environment;

[0007] Step S2: removing interfering light sources from the collected image data of the vehicle headlight's external environment;

[0008] Step S3: Analyzing the road conditions of the processed vehicle headlight external environment image data;

[0009] Step S4: Analyzing the analyzed road curvature index and the vehicle wheelbase to obtain a headlight deflection angle, and transmitting the headlight deflection angle to the controller;

[0010] Step S5: Calculating the headlight brightness based on the driving speed and the ambient light brightness of the vehicle;

[0011] Step S6: The controller receives the headlight deflection angle and the road type, and performs intelligent control of the headlight.

[0012] Preferably, in step S1, the high-definition camera selects a camera with 4K high resolution, 30fps frame rate and excellent low-light performance, and is installed in the center of the front of the vehicle and connected to the user interface; the camera's field of view covers the main area in front of the headlights, including lanes, road markings and traffic signs.

[0013] Preferably, in step S2, any lane in the collected vehicle headlight external environment image data is divided into m parts, and the lane line element set on the left side of the lane area in the ath lane section of this lane is represented as , the right lane line element set is represented as ;

[0014] The calculation method for fitting the left element set is as follows:

[0015] ,in, Expressed as the left-side fitted value, Expressed as the fitted slope of the left lane of lane a, It is represented as the slope of the left lane line in the left lane element set, Indicates the starting position of the left lane;

[0016] The calculation method for fitting the element set on the right is as follows:

[0017] ,in, Expressed as the right-side fitted value, It is represented as the slope of the right lane line in the right lane element set, It is expressed as the fitting slope of the right lane of lane a, Indicates the starting position of the right lane;

[0018] According to the fitting formula and The headlight data of the target headlight source is not in the same lane as the target headlight source. If a headlight source is in a different lane, it will not be considered as data related to the target headlight source.

[0019] Preferably, in step S3, the vehicle headlight external environment image data excluding the lights of vehicles not in the same lane is subjected to road condition analysis. The road conditions are divided into straight roads and turning roads. The calculation method for calculating the road conditions of the vehicle is specifically as follows:

[0020] , where E represents the road curvature index, Indicates the starting position of the left lane, Indicates the starting position of the right lane, It is represented by the width of the left lane in the left lane element set, It is represented as the slope of the left lane line in the left lane element set, It is expressed as the fitting slope of the right lane of lane a, It is expressed as the fitted slope of the left lane of lane segment a;

[0021] The calculated road curvature index is compared with a preset road curvature index threshold. If the calculated road curvature index is greater than the preset road curvature index threshold, the road condition is a curved road; if the calculated road curvature index is less than the preset road curvature index threshold, the road condition is a straight road.

[0022] Preferably, in step S4, the method for calculating the vehicle deflection angle is specifically as follows:

[0023] Among them, P represents the vehicle's deflection angle, F represents the vehicle's wheelbase, and g represents the vehicle's mass. Expressed as the rear wheel cornering stiffness, is the front wheel cornering stiffness, Expressed as the distance from the center of the vehicle to the rear wheels, Expressed as the distance from the center of the vehicle to the front wheel, It is expressed as the front wheel turning radius, and E is expressed as the road curvature index.

[0024] Preferably, in step S5, the method for calculating the vehicle light illumination value is specifically as follows:

[0025] Among them, H represents the illumination value of the car lights, T represents the brightness index of the surrounding environment when the car is driving, and V represents the speed of the vehicle. 、 、 Expressed as the headlight brightness impact factor;

[0026] The brightness of the headlights is divided into three levels. , then the headlight brightness is level three;

[0027] when , then the headlight brightness is level 2;

[0028] when , then the headlight brightness is level one;

[0029] Among them, H represents the illumination value of the vehicle headlight, f, h, j represent constants, and .

[0030] Preferably, in step S6, the vehicle light control system includes: a vehicle light controller, a photosensor, a Hall effect vehicle speed sensor, and a direction sensor;

[0031] The controller includes one or more microprocessors that can quickly process data and send precise control signals to the headlight adjustment mechanism. The headlight adjustment mechanism includes servo motors or stepper motors that can precisely control the rotation angle of the headlights. When the vehicle is traveling on a straight road, the headlights generally maintain a standard illumination direction to ensure an adequate lighting range. When turning, the headlights will rotate outward to a certain angle based on the angle of the turn and the vehicle's speed to illuminate the curve the vehicle is about to enter.

[0032] The controller receives the headlight deflection angle data and road type from step S4. These data provide the controller with detailed information about the current vehicle driving condition and external environment; the controller performs comprehensive analysis based on these data.

[0033] Technical effects and advantages of the present invention:

[0034] A high-definition camera captures images of the vehicle's external environment, accurately removes interfering light sources, and analyzes road types. The system calculates the headlight deflection angle based on the road curvature index and vehicle wheelbase, and automatically adjusts the headlight brightness based on vehicle speed and ambient light levels. The control unit receives the deflection angle and road type data and intelligently adjusts the headlights. This method can automatically adjust the distribution and intensity of light based on the curvature of the road and the steering of the vehicle, enhancing flexibility and intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 Schematic diagram of the method of the present invention.

[0036] Figure 2 Schematic diagram of module connection of the present invention. DETAILED DESCRIPTION

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0038] See also Figure 1 As shown, the present invention provides an intelligent vehicle light control method, which is as follows:

[0039] Step S1: using a high-definition camera to collect image data of the vehicle headlight's external environment;

[0040] In step S1, the high-definition camera selects a camera with 4K high resolution, 30fps frame rate and excellent low-light performance, and is installed in the center of the front of the vehicle and connected to the user interface; the camera's field of view covers the main area in front of the headlights, including lanes, road markings and traffic signs.

[0041] Step S2: removing interfering light sources from the collected image data of the vehicle headlight's external environment;

[0042] In step S2, any lane in the collected vehicle headlight environment image data is divided into m parts, and the lane line element set on the left side of the lane area in the ath lane section of this lane is represented as , the right lane line element set is represented as ;

[0043] Use median filtering to remove image noise and improve edge detection. Establish a coordinate system for the road, with the front of the vehicle as the x-axis, the road height as the y-axis, and the front of the vehicle as the coordinate system. , the last position of the vehicle is recorded as coordinate , the calculation method of the slope of the left lane is as follows: , The element is the slope of the left lane line;

[0044] The calculation method of the slope of the right lane is as follows: , The element is the slope of the right lane line;

[0045] Use the Canny edge detection algorithm to identify the lane line edge and extract the coordinates of the two edge points of the left lane line from the edge detection results. 、 , the coordinates of the two edge points of the right lane line 、 Calculate the horizontal distance between two edge points. The lane width is calculated as follows:

[0046] ,in, The element is represented as the lane width of the left lane;

[0047] ,in, The element is represented as the lane width of the right lane;

[0048] The calculation method for fitting the left element set is as follows:

[0049] ,in, Expressed as the left-side fitted value, Expressed as the fitted slope of the left lane of lane a, It is represented as the slope of the left lane line in the left lane element set, Indicates the starting position of the left lane;

[0050] The calculation method for fitting the element set on the right is as follows:

[0051] ,in, Expressed as the right-side fitted value, It is represented as the slope of the right lane line in the right lane element set, It is expressed as the fitting slope of the right lane of lane a, Indicates the starting position of the right lane;

[0052] The calculation method of the fitting slope of the left lane of lane a is as follows:

[0053] ,in, It is expressed as the fitting slope of the left lane of the a-th lane, and n is the number of elements. It is represented as the slope of the left lane line in the left lane element set, It is represented as the left lane width in the left lane element set;

[0054] The calculation method of the fitting slope of the right lane of lane a is as follows:

[0055] ,in, It is expressed as the fitting slope of the right lane of the a-th lane, and n is the number of elements. It is represented as the slope of the right lane line in the right lane element set, It is represented by the width of the right lane in the right lane element set;

[0056] The calculation method of the first parameter is:

[0057] ,in, Indicates the starting position of the left lane, It is represented as the slope of the left lane line in the left lane element set, It is represented by the width of the left lane in the left lane element set, and n is the number of elements;

[0058] The calculation method of the second parameter is as follows:

[0059] ,in, Indicates the starting position of the right lane, It is represented as the slope of the right lane line in the right lane element set, It is represented by the width of the right lane in the right lane element set, and n is the number of elements;

[0060] Extract the elements of each detected headlight source in the image 、 、 、 , bring the extracted elements into the fitting formula 、 If the calculated 、 The difference from the preset fitting value is ], then the headlight source is not in this lane and is removed; p represents the fitting threshold;

[0061] In the present invention, the preset value and the threshold value are defined by people in this professional field, and the present invention does not make any specific limitations here.

[0062] According to the fitting formula and The headlight data of the target headlight source is not in the same lane as the target headlight source. If a headlight source is in a different lane, it will not be considered as data related to the target headlight source.

[0063] Step S3: Analyzing the road conditions of the processed vehicle headlight external environment image data;

[0064] In step S3, the road condition analysis is performed on the image data of the external environment of the vehicle headlights, excluding the lights of vehicles not in the same lane. The road condition is divided into straight roads and turning roads. The calculation method for calculating the road condition of the vehicle is as follows:

[0065] , where E represents the road curvature index, Indicates the starting position of the left lane, Indicates the starting position of the right lane, It is represented by the width of the left lane in the left lane element set, It is expressed as the slope of the left lane line in the left lane element set, It is expressed as the fitting slope of the right lane of lane a, It is expressed as the fitted slope of the left lane of lane segment a;

[0066] The calculated road curvature index is compared with a preset road curvature index threshold. If the calculated road curvature index is greater than the preset road curvature index threshold, the road condition is a curved road; if the calculated road curvature index is less than the preset road curvature index threshold, the road condition is a straight road.

[0067] Step S4: Analyzing the analyzed road curvature index and the vehicle wheelbase to obtain a headlight deflection angle, and transmitting the headlight deflection angle to the controller;

[0068] In step S4, the method for calculating the vehicle deflection angle is specifically as follows:

[0069] Among them, P represents the vehicle's deflection angle, F represents the vehicle's wheelbase, and g represents the vehicle's mass. Expressed as the rear wheel cornering stiffness, is the front wheel cornering stiffness, Expressed as the distance from the center of the vehicle to the rear wheels, Expressed as the distance from the center of the vehicle to the front wheel, It is expressed as the front wheel turning radius, and E is expressed as the road curvature index;

[0070] The calculated vehicle deflection angle is transmitted to step S5 for headlight control.

[0071] Step S5: Calculating the headlight brightness based on the driving speed and the ambient light brightness of the vehicle;

[0072] In step S5, the method for calculating the headlight illumination value is specifically as follows:

[0073] Among them, H represents the illumination value of the car lights, T represents the brightness index of the surrounding environment when the car is driving, and V represents the speed of the vehicle. 、 、 Expressed as the headlight brightness impact factor;

[0074] in, 、 、 are three factors that affect the illumination value of the headlights. Expressed as headlight power, Expressed as the beam angle of the headlight; the beam angle of the headlight is the shape and direction of the light beam emitted by the headlight itself; It is expressed as a weather index. When it is foggy, the weather index is 0; when it is rainy, the weather index is 1; when there is no rain or fog, the weather index is 2.

[0075] The brightness of the headlights is divided into three levels. , then the headlight brightness is level three;

[0076] when , then the headlight brightness is level 2;

[0077] when , then the headlight brightness is level one;

[0078] Among them, H represents the illumination value of the vehicle headlight, f, h, j represent constants, and ;

[0079] The constants f, h, and j are defined by professionals in this field and are not specifically defined here;

[0080] When the ambient light brightness is low, the ambient light index is 4 when the car is driving;

[0081] When the ambient light brightness is medium, the ambient light index is 3 when the car is driving;

[0082] When the ambient light brightness is strong, the ambient light index is 2 when the car is driving;

[0083] When the ambient light brightness is very strong, the ambient light index is 1 when the car is driving;

[0084] Low light: Usually below 1000 Lux, suitable for situations that require careful reading, writing or delicate work, such as reading, writing, and drawing.

[0085] Medium light: between 1000-2000 Lux, suitable for general reading, writing and work, such as office lighting and general reading.

[0086] Strong light: between 2000-4000 Lux, suitable for occasions requiring high clarity and high recognition, such as TV broadcasting, performances, and movie projection.

[0087] Very strong light: above 4000 Lux, suitable for occasions requiring extremely high brightness, such as operating rooms and studios;

[0088] A Hall effect sensor is installed on the vehicle's transmission output shaft to detect wheel or drive shaft speed. As the wheel rotates, the sensor generates an AC signal corresponding to the wheel speed. This AC signal is transmitted to the electronic control unit. During transmission, the signal undergoes a signal conditioning stage, where it is converted into a voltage signal. Voltage signals are more suitable for long-distance transmission and are easier to process in the ECU. The amplitude of the voltage signal is generally proportional to the wheel speed; that is, the faster the wheel speed, the larger the amplitude of the voltage signal generated.

[0089] The specific calculation method of vehicle speed is:

[0090] , where V represents the vehicle speed, N represents the number of pulses generated by the sensor per unit time, R represents the wheel radius, K represents the pulse sampling period, Y represents the number of signal teeth, and U represents the main transmission ratio.

[0091] Step S6: The controller receives the headlight deflection angle and the road type, and performs intelligent control of the headlight;

[0092] In step S6, the vehicle light control system includes: a vehicle light controller, a light sensor, a Hall effect vehicle speed sensor, and a direction sensor;

[0093] The controller includes one or more microprocessors that can quickly process data and send precise control signals to the headlight adjustment mechanism. The headlight adjustment mechanism includes servo motors or stepper motors that can precisely control the rotation angle of the headlights. When the vehicle is traveling on a straight road, the headlights generally maintain a standard illumination direction to ensure an adequate lighting range. When turning, the headlights will rotate outward to a certain angle based on the angle of the turn and the vehicle's speed to illuminate the curve the vehicle is about to enter.

[0094] The controller receives the headlight deflection angle data and road type from step S4, which provide the controller with detailed information about the current vehicle driving condition and external environment; the controller performs a comprehensive analysis based on the data;

[0095] If the headlight deflection angle data indicates that the vehicle is turning and the light sensor detects low ambient light, the controller will instruct the headlight system to increase the brightness and adjust the light angle to ensure sufficient lighting in the turning area without causing glare to oncoming vehicles;

[0096] The headlight controller automatically turns on the headlights according to preset conditions;

[0097] When the sensor detects that the ambient light is weak, the headlight controller automatically adjusts the headlight brightness to level three;

[0098] When the sensor detects that the ambient light is medium, the headlight controller automatically adjusts the headlight brightness to the secondary level;

[0099] When the sensor detects that the ambient light is strong or very strong, the headlight controller automatically adjusts the headlight brightness to the first level;

[0100] When the sensor detects that the vehicle's driving direction has changed, the headlight controller automatically adjusts the direction of the headlights;

[0101] When the sensor detects that the vehicle is traveling on a curved road, the headlight controller automatically adjusts the headlight angle to illuminate the curved road ahead;

[0102] The control system automatically adjusts the brightness and deflection angle of the headlights according to vehicle speed and road type.

[0103] See also Figure 2As shown, in this embodiment, it should be specifically explained that the present invention provides an intelligent vehicle light control system, including the following modules:

[0104] Image data acquisition module: used to collect image data of the external environment of vehicle headlights using a high-definition camera;

[0105] Image data processing module: used to remove interfering light sources from the collected image data of the vehicle headlight's external environment;

[0106] Road condition analysis module: used to analyze the road condition of the processed vehicle headlight external environment image data;

[0107] Headlight deflection angle analysis module: used to analyze the analyzed road curvature index and vehicle wheelbase to obtain the headlight deflection angle, and transmit the headlight deflection angle to the controller;

[0108] Headlight brightness calculation module: used to calculate the headlight brightness based on the driving speed and the ambient light brightness of the vehicle;

[0109] Intelligent control module: The controller receives the headlight deflection angle and road type, and performs intelligent control of the headlights.

[0110] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An intelligent vehicle light control method, characterized in that: include: Step S1: using a high-definition camera to collect image data of the external environment of the vehicle headlight; Step S2: Eliminate interference light sources from the collected image data of the vehicle headlight's external environment; In step S2, any lane in the collected vehicle headlight environment image data is divided into m parts, and the lane line element set on the left side of the lane area in the ath lane section of this lane is represented as , the right lane line element set is represented as ; The calculation method for fitting the left element set is as follows: ,in, is represented as the left-side fitted value, It is expressed as the fitted slope of the left lane of the a-th lane. It is represented as the slope of the left lane line in the left lane element set, Indicates the starting position of the left lane; The calculation method for fitting the right element set is as follows: ,in, is represented as the right-hand side fitted value, It is represented as the slope of the right lane line in the right lane element set, It is expressed as the fitted slope of the right lane of the a-th lane. Indicates the starting position of the right lane; The calculation method of the fitting slope of the left lane of the a-th lane is as follows: ,in, It is represented as the fitted slope of the left lane of the a-th lane, and n is represented as the number of elements. It is represented as the slope of the left lane line in the left lane element set, It is represented as the left lane width in the left lane element set; The calculation method of the fitting slope of the right lane of lane a is as follows: ,in, It is represented as the fitted slope of the right lane of the a-th lane, and n is represented as the number of elements. It is represented as the slope of the right lane line in the right lane element set, It is represented as the width of the right lane in the right lane element set; According to the fitting formula and Eliminate the headlight data that are not in the same lane as the target headlight; Step S3: analyzing the road condition of the processed vehicle headlight external environment image data; In step S3, the vehicle headlight external environment image data excluding the vehicle lights not in the same lane is subjected to road condition analysis. The road conditions are divided into straight roads and turning roads. The specific method for calculating the road conditions of the vehicle is as follows: , where E represents the road curvature index, Represents the starting position of the left lane, Indicates the starting position of the right lane, It is represented by the width of the left lane in the left lane element set, It is represented as the slope of the left lane line in the left lane element set, It is expressed as the fitted slope of the right lane of the a-th lane. Expressed as the fitted slope of the left lane of lane a Step S4: Analyze the analyzed road curvature index and the vehicle wheelbase to obtain a headlight deflection angle, and transmit the headlight deflection angle to the controller; Step S5: Calculate the headlight brightness according to the driving speed and the ambient light brightness of the vehicle when it is driving; Step S6: The controller receives the headlight deflection angle and the road type, and performs intelligent control of the headlight.

2. The intelligent vehicle light control method according to claim 1, characterized in that: In step S1, the high-definition camera selects a camera with 4K high resolution, 30fps frame rate and excellent low-light performance, and installs the high-definition camera in the center of the front of the vehicle, and connects the high-definition camera to the user interface; the camera's field of view covers the main area in front of the headlights, including lanes, road markings and traffic signs.

3. The intelligent vehicle light control method according to claim 1, characterized in that: In step S4, the method for calculating the vehicle deflection angle is specifically as follows: Among them, P represents the vehicle's deflection angle, F represents the vehicle's wheelbase, and g represents the vehicle's mass. is the rear wheel cornering stiffness, is the front wheel cornering stiffness, It is expressed as the distance from the center of the vehicle to the rear wheel. It is expressed as the distance from the center of the vehicle to the front wheel. It is expressed as the front wheel turning radius and E is expressed as the road curvature index.

4. The intelligent vehicle light control method according to claim 1, characterized in that: In step S5, the method for calculating the vehicle light illumination value is specifically as follows: Among them, H represents the illumination value of the car lights, T represents the ambient light index when the car is driving, and V represents the vehicle speed. , , It is expressed as the factor affecting the brightness of the headlights; in, , , are three factors that affect the illumination value of the headlights. Expressed as the headlight power, It is expressed as the beam angle of the headlight; the beam angle of the headlight is the shape and direction of the light beam emitted by the headlight; It is expressed as a weather index. When it is foggy, the weather index is 0; when it is rainy, the weather index is 1; when there is no rain or fog, the weather index is 2.

5. The intelligent vehicle light control method according to claim 4, characterized in that: The specific calculation method of vehicle speed is: , where V represents the vehicle speed, N represents the number of pulses generated by the sensor per unit time, R represents the wheel radius, K represents the pulse sampling period, Y represents the number of signal teeth, and U represents the main transmission ratio.

6. The intelligent vehicle light control method according to claim 1, characterized in that: In step S6, the vehicle light control system includes: a vehicle light controller, a photosensitive sensor, a Hall speed sensor, and a direction sensor; The controller includes one or more microprocessors that can quickly process data and send precise control signals to the headlight adjustment mechanism; the headlight adjustment mechanism includes a servo motor or a stepper motor that can precisely control the rotation angle of the headlight; when the vehicle is traveling on a straight road, the headlight usually maintains a standard illumination direction to ensure a sufficient lighting range; when turning, the headlight will turn outward at a certain angle according to the turning angle and the speed of the vehicle to illuminate the curved road section that the vehicle is about to enter; The controller receives the headlight deflection angle data and the road type from step S4, which provide the controller with detailed information about the current vehicle driving condition and external environment; the controller performs a comprehensive analysis based on the data.

7. An intelligent vehicle light control system, using an intelligent vehicle light control method as claimed in any one of claims 1 to 6, characterized in that: Image data acquisition module: used to collect image data of the external environment of vehicle headlights using a high-definition camera; Image data processing module: used to remove interfering light sources from the collected image data of the external environment of vehicle headlights; Road condition analysis module: used to analyze the road condition of the processed vehicle headlight external environment image data; Headlight deflection angle analysis module: used to analyze the analyzed road curvature index and vehicle wheelbase to obtain the headlight deflection angle, and transmit the headlight deflection angle to the controller; Headlight brightness calculation module: used to calculate the headlight brightness based on the driving speed and the ambient light brightness when the vehicle is driving; Intelligent control module: used for the controller to receive the deflection angle of the headlights and the road type, and to perform intelligent control of the headlights.

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