High light suppression closed-loop regulation method for intelligent self-closed-loop car light

Abstract

The application discloses a high-light suppression closed-loop adjustment method for an intelligent self-closed-loop vehicle lamp and belongs to the technical field of vehicle lamp control. The method comprises the following steps: step S1, continuously collecting a road image in front of a vehicle through an image sensor and analyzing the road image in front of the vehicle by an image processing unit; step S2, performing high-light suppression judgment according to an average illumination value of a target light source region in the road image in front of the vehicle by a self-adaptive high-light suppression control algorithm module; and step S3, calculating a self-adaptive compensation light flux after entering a high-light suppression closed-loop adjustment mode. The application provides the high-light suppression closed-loop adjustment method for the intelligent self-closed-loop vehicle lamp, so that the intelligent vehicle lamp system can actively and dynamically adjust light output of the system to suppress external high light entering a camera of the vehicle, thereby maintaining stable and reliable operation of a self-perception system of the vehicle in a severe light environment and guaranteeing normal performance of intelligent light functions.

Description

Technical Field

[0001] This invention relates to a closed-loop adjustment method for strong light suppression in intelligent self-closed-loop vehicle lights, belonging to the field of vehicle light control technology. Background Technology

[0002] Currently, with the improvement of automotive intelligence, intelligent lighting systems such as adaptive high beam (ADB) or matrix headlights have become key technologies for improving nighttime driving safety. These systems typically rely on a front-facing camera to perceive the road environment ahead (such as vehicles, pedestrians, and traffic signs) in real time, and dynamically adjust the light distribution based on the perception results to avoid dazzling other road users.

[0003] However, in nighttime oncoming traffic scenarios, when an oncoming vehicle turns on its high beams, the intense light emitted can easily cause localized or global overexposure ("glare") to the front-facing camera of the vehicle. The dynamic range of the camera's sensor is limited; under strong light interference, details of key targets in the captured image (such as the outlines of oncoming vehicles, pedestrians, and lane lines) can be severely lost or even completely obscured by the glare, causing the environmental perception algorithm to fail. Once perception fails, the intelligent headlight adjustment system, which relies on the perception results, will be unable to make correct lighting decisions, potentially maintaining an inappropriate lighting mode that neither provides adequate illumination for the vehicle itself nor continuously glares oncoming drivers, creating a safety hazard.

[0004] Therefore, how to enable intelligent vehicle lighting systems to maintain effective environmental perception and lighting adjustment capabilities under strong light interference has become a technical problem that urgently needs to be solved in this field.

[0005] In existing technologies, the main solutions to the problem of glare from oncoming traffic include: 1. Automatic switching based on simple sensors: This method uses an independent photosensor to detect ambient light intensity. When a strong light source (such as oncoming headlights) is detected ahead, the high beams are automatically switched to low beams. This solution cannot achieve precise regional light pattern control.

[0006] 2. Matrix headlight adjustment based on preset rules: Upon detecting an oncoming vehicle, the matrix headlights adjust the corresponding LEDs in the direction of the oncoming vehicle by turning off or dimming them according to preset rules, creating a "dark zone" to avoid the oncoming vehicle. This solution relies on accurate vehicle detection and positioning.

[0007] 3. Image processing anti-overexposure algorithms: These algorithms employ image processing techniques such as high dynamic range (HDR) compositing and local tone mapping at the camera or processor end to attempt to recover details from overexposed images. These algorithms are post-processing-based, and their recovery effect is limited under extreme overexposure conditions, while also introducing processing delays and noise.

[0008] However, existing technologies still have the following drawbacks. 1. Open-loop separation of perception and execution: Schemes 1 and 2 treat environmental perception (strong light detection) and execution (light adjustment) as two independent open-loop processes. When strong light causes the perception module (camera) to malfunction, the execution module cannot function properly due to the loss of effective input, and the system becomes stuck or makes incorrect decisions.

[0009] 2. Passive response to strong light interference: Existing technologies mainly avoid or compensate for strong light after it is detected, which is a passive response. Given that strong light has already caused a significant deterioration in perception quality, the reliability of all subsequent decisions and adjustments based on this perception is greatly reduced.

[0010] 3. Lack of active optical suppression mechanism: Solution 3 only attempts to repair the damaged image information from the software algorithm level, without considering the active suppression of light flux entering the camera from the optical physics level. Therefore, its effect is fundamentally limited when facing continuous and strong direct light sources.

[0011] 4. Lack of a closed-loop optimization mechanism of "perception-control-perception": The existing solution fails to construct a closed-loop system with "maintaining effective camera perception" as the direct control objective. The system's control objective is merely "avoiding oncoming vehicles" or "switching lights," rather than actively and dynamically adjusting its own light output to counteract the interference of strong external light on its own sensing unit. Summary of the Invention

[0012] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide a strong light suppression closed-loop adjustment method for intelligent self-closed-loop vehicle lights, so that the intelligent vehicle light system can actively and dynamically adjust its own light output to suppress the external strong light entering the vehicle's camera, thereby maintaining the stable and reliable operation of its own sensing system in harsh light environments and ensuring the normal functioning of intelligent lighting.

[0013] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: A method for closed-loop regulation of glare suppression in intelligent self-closed-loop vehicle lights, comprising the following steps: Step S1: Continuously acquire images of the road in front of the vehicle using an image sensor, and analyze the images of the road in front of the vehicle using an image processing unit; Step S2: The adaptive strong light suppression control algorithm module makes a strong light suppression judgment based on the average illuminance value of the target light source area in the road image in front of the vehicle. Step S3: After entering the strong light suppression closed-loop adjustment mode, calculate the adaptive compensation luminous flux; Step S4: Generate the headlight driving command based on the required adaptive compensation luminous flux calculated at time t. Then, the headlight driving actuator receives the headlight driving command and drives the headlight unit to make adjustments. Step S5: After making corresponding adjustments to the headlight unit, re-acquire images of the road in front of the vehicle and perform closed-loop feedback and iteration.

[0014] Furthermore, in step S1, images of the road ahead of the vehicle are continuously acquired by an image sensor, and the image processing unit analyzes these images; specifically, the steps include the following: Step S11: Identify the target light source region in the image and the target light source pixel region R in the image of the road in front of the vehicle. target ; Step S12: Calculate the target light source pixel region R target Average illuminance value E of the target light source area t The average illuminance value E of the target light source area t The calculation formula is as follows: ; Simultaneously, calculate the average illuminance E of the road area excluding the target light source region in the image of the road ahead of the vehicle. a As the ambient background illuminance, the average illuminance E in the road area a The calculation formula is as follows: ; Where I(x, y, t) is the gray value of pixel (x, y) or the intensity value of a specific color channel in the image of the road in front of the vehicle at time t; N t The total number of pixels in the target light source area; N a This represents the total number of pixels in the road area.

[0015] Furthermore, in step S2, the adaptive glare suppression control algorithm module performs glare suppression judgment based on the average illuminance value of the target light source area in the road image ahead of the vehicle; specifically, it includes the following steps: The adaptive strong light suppression control algorithm module will adjust the average illuminance value E of the target light source area. t With the preset overexposure threshold E th Compare, if E t > E th If the light source is detected, the vehicle camera is determined to be interfered with by the target light source, and the system enters the strong light suppression closed-loop adjustment mode.

[0016] Furthermore, in step S3, after entering the strong light suppression closed-loop adjustment mode, the adaptive compensation luminous flux is calculated; specifically, this includes the following steps: Once the glare suppression closed-loop adjustment mode is entered, the adaptive compensation luminous flux is calculated to counteract the glare interference from the target light source. Then, the local area Ω on the vehicle's headlights corresponding to the direction of oncoming vehicles is adjusted. lightIncrease adaptive compensation luminous flux Φ comp The adaptive compensation luminous flux Φ comp The calculation formula is as follows: ; in, The required adaptive compensation luminous flux is calculated at time t; E t The average illuminance value of the target light source area; E th This is the preset overexposure threshold; K p K is the proportional control coefficient. i K is the integral control coefficient. d These are the differential control coefficients; α is the ambient light adaptive coefficient.

[0017] Furthermore, in step S4, a headlight driving command is generated based on the required adaptive compensation luminous flux calculated at time t. Then, the headlight driving actuator receives the headlight driving command and drives the headlight unit to make adjustments. Specifically, this includes the following steps: The required adaptive compensation luminous flux at time t is calculated. Convert to headlight drive commands; For matrix headlights, the headlight drive command is to adjust a local area Ω. light The driving current or duty cycle of the corresponding LED beads; for adaptive high beams, the headlight driving command is to adjust the local area Ω. light The intensity of the beam; The headlight drive actuator receives headlight drive commands and drives the headlight unit to make corresponding adjustments.

[0018] Furthermore, in step S5, after the headlight unit makes corresponding adjustments, the image of the road in front of the vehicle is re-acquired, and closed-loop feedback and iteration are performed; specifically, this includes the following steps: After the headlight unit makes the corresponding adjustments, after one control cycle T, it returns to step S1 to acquire a new image of the road ahead of the vehicle and calculate the new E. t (t+T); Based on the new target light source area average illuminance value E t With overexposure threshold E th Calculate the new adaptive compensation luminous flux Φ again. comp (t+T); The adaptive compensation luminous flux is calculated iteratively, and the control objective is to maximize the average illuminance value E in the target light source region. t Stabilized at overexposure threshold E th The level.

[0019] By employing the above technical solution, this invention fundamentally solves the problem of perception failure caused by strong light. Through active optical suppression, it ensures that the camera can obtain effective input images in various oncoming traffic scenarios, providing a stable perception foundation for all subsequent intelligent driving functions. The control algorithm, combining PID feedback and feedforward (ambient light adaptive), can dynamically and smoothly adjust the compensation luminous flux to adapt to oncoming strong light of different intensities and distances, as well as changing ambient light, avoiding flickering or oscillations during the adjustment process and improving driving comfort. It only increases the light output of specific areas when strong light interference is detected and necessary, making it more energy efficient compared to traditional solutions that simply switch between high and low beams or keep high-brightness areas on throughout. Attached Figure Description

[0020] Figure 1 This is a flowchart of the intelligent self-closed-loop vehicle light strong light suppression closed-loop adjustment method of the present invention. Figure 2 This is a system principle block diagram of the intelligent self-closed-loop vehicle light strong light suppression closed-loop adjustment method of the present invention. Detailed Implementation

[0021] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0022] like Figure 1 , 2 As shown, this embodiment provides a method for closed-loop adjustment of glare suppression in intelligent self-closed-loop vehicle lights, including the following steps: Step S1: Continuously acquire images of the road ahead of the vehicle using an image sensor, and analyze these images using an image processing unit. Specifically: Step S11: Identify the target light source region in the image (such as the headlight outline region of an oncoming vehicle) and the target light source pixel region R in the image of the road in front of the vehicle. target .

[0023] Step S12: Calculate the target light source pixel region R target Average illuminance value E of the target light source area t The average illuminance value E of the target light source area t The calculation formula is as follows: ; Simultaneously, calculate the average illuminance E of the road area excluding the target light source region in the image of the road ahead of the vehicle. a As the ambient background illuminance, the average illuminance E in the road area a The calculation formula is as follows: ; Where I(x, y, t) is the gray value of pixel (x, y) or the intensity value of a specific color channel in the image of the road in front of the vehicle at time t, which is digital image data directly obtained from the image sensor; N t The total number of pixels in the target light source area; N a This represents the total number of pixels in the road area. Average illuminance value E of the target light source area t This is calculated through regional statistical analysis of image sensor data and is used to determine whether overexposure has occurred. Average illuminance E in road area a This is derived through regional statistical calculations of image sensor data.

[0024] Step S2: The adaptive glare suppression control algorithm module determines glare suppression based on the average illuminance value of the target light source area in the road image ahead of the vehicle. Specifically: The adaptive strong light suppression control algorithm module will adjust the average illuminance value E of the target light source area. t With the preset overexposure threshold E th Comparison, overexposure threshold E th It can be dynamically set according to the saturation level of the camera sensor and the requirements of the image processing algorithm. If E t > E th If the light source is detected, the vehicle camera is determined to be interfered with by the target light source, and the system enters the strong light suppression closed-loop adjustment mode.

[0025] Step S3: After entering the strong light suppression closed-loop adjustment mode, calculate the adaptive compensation luminous flux, and use the adaptive compensation luminous flux to counteract the interference from the target light source. Specifically: Once the glare suppression closed-loop adjustment mode is entered, the adaptive compensation luminous flux is calculated to counteract the glare interference from the target light source. Then, the local area Ω on the vehicle's headlights corresponding to the direction of oncoming vehicles is adjusted. light Increase adaptive compensation luminous flux Φ comp Adaptive compensation of luminous flux Φ comp The calculation formula is as follows: ; in, The required adaptive compensation luminous flux calculated at time t, in lumens (lm); E t The average illuminance value of the target light source area; E th This is the preset overexposure threshold; K p K is the proportional control coefficient. i K is the integral control coefficient. dThese are the differential control coefficients, used to achieve stable, rapid, and zero steady-state error regulation of the closed-loop system. Their specific values ​​are obtained through system identification and controller tuning to ensure the dynamic performance of the closed-loop system. α is the ambient light adaptive coefficient, used to adjust the average illuminance E in the road area. a Feedforward adjustment is performed on the adaptive compensation luminous flux. In extremely dark environments (E... a Even slight external strong light can cause overexposure, and the human eye is more sensitive to light, requiring more precise control (α can be adjusted by weight); in brighter environments (such as city roads, E...), a When α is relatively large, the weight can be reduced.

[0026] Step S4: Generate the headlight drive command based on the required adaptive compensation luminous flux calculated at time t. Then, the headlight drive actuator receives the headlight drive command and drives the headlight unit to make adjustments. Specifically: The required adaptive compensation luminous flux at time t is calculated. Converted into specific vehicle light driving commands; For matrix headlights, the headlight drive command is to adjust a local area Ω. light The driving current or duty cycle of the corresponding LED beads; for adaptive high beams, the headlight driving command is to adjust the local area Ω. light The intensity of the beam; The headlight drive actuator receives headlight drive commands and drives the headlight unit to make corresponding adjustments.

[0027] Step S5: After making corresponding adjustments to the headlight unit, re-acquire images of the road ahead of the vehicle and perform closed-loop feedback and iteration. Specifically: After the headlight unit makes the corresponding adjustments, and after a very short control cycle T (e.g., 10-50ms), the system returns to step S1 to acquire a new image of the road ahead and calculate the new E. t (t+T); Based on the new target light source area average illuminance value E t With overexposure threshold E th Calculate the new adaptive compensation luminous flux Φ again. comp (t+T); The adaptive compensation luminous flux is calculated iteratively to form a closed-loop negative feedback system. Its control objective is to maximize the average illuminance value E in the target light source area. t Stabilized at overexposure threshold E th The level (i.e., E) t Slightly less than or equal to E th This actively suppresses overexposure at the optical level, ensuring that the camera is always in an effective light-sensing state in the target area.

[0028] The specific embodiments described above further illustrate the technical problems, technical solutions, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are 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 within the protection scope of the present invention.

Claims

1. A method for closed-loop regulation of strong light suppression in intelligent self-closed-loop vehicle lights, characterized in that, Includes the following steps: Step S1: Continuously acquire images of the road in front of the vehicle using an image sensor, and analyze the images of the road in front of the vehicle using an image processing unit; Step S2: The adaptive strong light suppression control algorithm module makes a strong light suppression judgment based on the average illuminance value of the target light source area in the road image in front of the vehicle. Step S3: After entering the strong light suppression closed-loop adjustment mode, calculate the adaptive compensation luminous flux; Step S4: Generate the headlight driving command based on the required adaptive compensation luminous flux calculated at time t. Then, the headlight driving actuator receives the headlight driving command and drives the headlight unit to make adjustments. Step S5: After making corresponding adjustments to the headlight unit, re-acquire images of the road in front of the vehicle and perform closed-loop feedback and iteration.

2. The method for strong light suppression closed-loop adjustment of intelligent self-closed-loop vehicle lights according to claim 1, characterized in that, In step S1, images of the road ahead of the vehicle are continuously acquired using an image sensor, and the image processing unit analyzes these images; specifically, the steps include the following: Step S11: Identify the target light source region in the image and the target light source pixel region R in the image of the road in front of the vehicle. target ; Step S12: Calculate the target light source pixel region R target Average illuminance value E of the target light source area t The average illuminance value E of the target light source area t The calculation formula is as follows: ； Simultaneously, calculate the average illuminance E of the road area excluding the target light source region in the image of the road ahead of the vehicle. a As the ambient background illuminance, the average illuminance E in the road area a The calculation formula is as follows: ； Where I(x, y, t) is the gray value of pixel (x, y) or the intensity value of a specific color channel in the image of the road in front of the vehicle at time t; N t The total number of pixels in the target light source area; N a This represents the total number of pixels in the road area.

3. The method for strong light suppression closed-loop adjustment of intelligent self-closed-loop vehicle lights according to claim 1, characterized in that, In step S2, the adaptive glare suppression control algorithm module performs glare suppression judgment based on the average illuminance value of the target light source area in the road image ahead of the vehicle; specifically, it includes the following steps: The adaptive strong light suppression control algorithm module will adjust the average illuminance value E of the target light source area. t With the preset overexposure threshold E th Compare, if E t > E th If the light source is detected, the vehicle camera is determined to be interfered with by the target light source, and the system enters the strong light suppression closed-loop adjustment mode.

4. The method for strong light suppression closed-loop adjustment of intelligent self-closed-loop vehicle lights according to claim 1, characterized in that, In step S3, after entering the strong light suppression closed-loop adjustment mode, the adaptive compensation luminous flux is calculated; specifically, the following steps are included: Once the glare suppression closed-loop adjustment mode is entered, the adaptive compensation luminous flux is calculated to counteract the glare interference from the target light source. Then, the local area Ω on the vehicle's headlights corresponding to the direction of oncoming vehicles is adjusted. light Increase adaptive compensation luminous flux Φ comp The adaptive compensation luminous flux Φ comp The calculation formula is as follows: ； in, The required adaptive compensation luminous flux is calculated at time t; E t The average illuminance value of the target light source area; E th This is the preset overexposure threshold; K p K is the proportional control coefficient. i K is the integral control coefficient. d These are the differential control coefficients; α is the ambient light adaptive coefficient.

5. The method for strong light suppression closed-loop adjustment of intelligent self-closed-loop vehicle lights according to claim 1, characterized in that, In step S4, a headlight driving command is generated based on the required adaptive compensation luminous flux calculated at time t. Then, the headlight driving actuator receives the headlight driving command and drives the headlight unit to make adjustments. Specifically, the steps include the following: The required adaptive compensation luminous flux at time t is calculated. Convert to headlight drive commands; For matrix headlights, the headlight drive command is to adjust a local area Ω. light The driving current or duty cycle of the corresponding LED beads; for adaptive high beams, the headlight driving command is to adjust the local area Ω. light The intensity of the beam; The headlight drive actuator receives headlight drive commands and drives the headlight unit to make corresponding adjustments.

6. The method for strong light suppression closed-loop adjustment of intelligent self-closed-loop vehicle lights according to claim 1, characterized in that, In step S5, after the headlight unit makes corresponding adjustments, a new image of the road in front of the vehicle is acquired, and closed-loop feedback and iteration are performed; specifically, the following steps are included: After the headlight unit makes the corresponding adjustments, after one control cycle T, it returns to step S1 to acquire a new image of the road ahead of the vehicle and calculate the new E. t (t+T); Based on the new target light source area average illuminance value E t With overexposure threshold E th Calculate the new adaptive compensation luminous flux Φ again. comp (t+T); The adaptive compensation luminous flux is calculated iteratively, and the control objective is to maximize the average illuminance value E in the target light source region. t Stabilized at overexposure threshold E th The level.

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