A Rough Road Identification Method for the Automotive Headlight Leveling System

To improve the driving experience at night, the Automatic Leveling System (ALS) is applied to the automotive headlight to maintain a stable lighting range. The ALS calculates the vehicle pitching attitude according to the difference of the front and rear height sensors fixed between the suspension and the vehicle body. The change of the vehicle attitude will affect the lighting range of the headlight. To neutralize the effect, a compensation angle is output by ALS to modify the illumination angle of the headlight. However, it is not appropriate to use ALS when vehicle is moving on roughroad, because the high frequency jolts of vehicle body will cause intensive headlight adjustments and result in visual fatigue. In this paper, a rough road identification method is proposed based on the characteristic extraction of the height sensor difference and vehicle acceleration. A weighted Mean Absolute Error (MAE) is introduced to evaluate the road characteristics. When the value of MAE exceeds the preset threshold, the road is identified as the rough road section. By the help of this identification method, the ALS can prevent redundant adjustments of the headlight by locking the output, and avoid causing visual fatigue to the driver.