Vehicle detecting and grading method, system and equipment for automotive intelligent headlamp

Abstract

The invention discloses a vehicle detecting and grading method, system and equipment for an automotive intelligent headlamp. The system comprises a vehicle and a target vehicle, wherein the vehicle comprises a vehicle body controller, a vehicle body electronic stabilizing system, an engine electronic fuel injection system, an intelligent headlamp controller, a lamp and vehicle-mounted short-range communication controllers; each controller exchanges data through a CAN bus, and the lamp is connected with the vehicle body controller and the intelligent headlamp controller; the target vehicle comprises a vehicle body controller, a vehicle body electronic stabilizing system, an engine electronic fuel injection system and vehicle-mounted short-range communication controllers; and each controller exchanges data through a CAN bus. The system can be applied to scenes with relatively poor sights, can be utilized for simultaneously detecting information of multiple target vehicles, and is applicable to the detection and grading under complex road conditions; and furthermore, the processing is relatively easy, the information handling capacity is low, algorithms are simple, and requirements on hardware resources of an MCU are reduced.

Description

technical field [0001] The invention belongs to automobile electronic control technology, and in particular relates to a vehicle detection and classification method, system and equipment for automobile intelligent headlights. Background technique [0002] Car headlights are of great help to the night driving process, but the uncivilized driving style of abusing the headlights in the scene of meeting cars and following, etc. causes the driver of the target car to be instantly blinded and dazzled, which has a great impact on driving safety. Therefore, more and more active smart headlights are being researched or applied to automobiles. Automobile smart headlights can automatically perform light illumination distribution, light source angle adjustment, beam shape adjustment (beam partial blocking or LED matrix on / off), large and small lamp switching / switching, etc. Optimized adjustments enhance the vehicle's vision and improve the safety of the vehicle; reduce the driver's att...

AI Technical Summary

Problems solved by technology

[0004] The autonomous detection and classification method of smart headlights based on machine vision has a low recognition rate for the detection of rain, fog, haze and other low-visibility weather conditions; since the detection method based on machine vision is usually a pair of vehicles However, it is difficult to detect when the background light is poor and the target vehicle’s lights are not on or malfunctioning; and the processing of multi-target detection is more complicated; and the image processing algorithm has higher requirements on MCU resources, hardware high cost

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