An Adaptive High Beam Control System and Image Processing Algorithm

Abstract

The invention discloses an adaptive high beam control system and an image processing algorithm. The control system includes a front-view camera, a headlight controller, a light source module driver, and an LED light source module, wherein: the front-view camera uses Collect the color image information of other vehicles in front while the vehicle is running, and output it to the headlight controller; the headlight controller is used to process the image information collected by the front-view camera, and calculate the position and distance information of the vehicle in front, Determine the control strategy of the high beam, and output the control signal to the light source module driver; the light source module driver is used to receive the control signal output by the headlight controller, and drive the high beam LED light source module according to the control signal to realize Adaptive high beam control. The invention detects the vehicle position based on images collected by a low-cost forward-looking color camera, and has the advantages of low cost, easy installation, strong versatility, and no dependence on specific equipment.

Description

technical field [0001] The invention belongs to the technical field of automotive electronic control, and relates to an adaptive high-beam control system and an image processing algorithm, in particular to a system and a system for realizing adaptive control of high-beam lights by actively detecting and tracking vehicles ahead during night driving of a vehicle. method. Background technique [0002] According to the statistics of traffic accidents in recent years, the accident rate of vehicles driving at night is higher than that during the day, and improper use of high beams is one of the main reasons for night traffic accidents. The adaptive high beam control system composed of front-view camera module, headlight controller, light source module driver, LED light source module, etc. is an effective solution to this safety problem. The system can actively adjust the high-beam light type of the vehicle by detecting and tracking the vehicle in front. It can avoid dazzling othe...

AI Technical Summary

Problems solved by technology

[0005] CN110084111A discloses a nighttime vehicle detection method applied to self-adaptive high beams, using image processing technologies such as network clustering and corrosion algorithms to judge headlights and taillights, and calculate vehicle positions. This method can only detect the position of vehicles ahead at night , the vehicle cannot be tracked during travel

CN106845453A discloses an image-based taillight detection and recognition method, using the real-time image of the front vehicle collected by the camera, and using color information to filter and extract the taillight information. Adapt to the control basis of the high beam

CN109447093A discloses a taillight detection method based on YUV coded images, which processes the acquired video image, extracts the red area, and determines the current taillight position. This method only detects the taillight information of the vehicle in front, and does not make a calculation on the position and distance of the vehicle. estimated, it cannot be used as the control basis for the adaptive high beam module

CN103453890A discloses a nighttime vehicle ranging method based on taillight detection, which uses the RGB coded image R channel to extract the red area in the image and marks it as the taillight area, and estimates the distance between the center of the red area and the road plane by measuring the distance between the center of the red area and the road plane Distance, the red area segmentation method used in this method cannot effectively distinguish the red tail light area from other red interference signals, the distance measurement method is based on the road plane, and errors will occur on undulating roads

CN101727748A discloses a vehicle monitoring method based on vehicle taillight detection. The method uses color information and motion information to detect taillights, and then recognizes a single vehicle in front. It cannot estimate the distance of the vehicle in front, and cannot monitor multiple vehicles in motion. location tracking

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