A machine learning-based method for rough roads recognition in ALS system

ALS (Automatic Headlamp Leveling System) is an intelligent headlamp control system that can adjust the distance of low beam illumination in real time, providing safer driving vision for vehicle drivers and passengers in dark environments, and improving driving comfort and safety. This paper proposes a machine learning method(Decision Tree) to assist the ALS system in deciding whether to adjust the low beam illumination distance based on the current road type by reading various sensor data of the vehicle. This solution is an attempt to implement intelligent headlamp illumination using machine learning methods, using advanced technology to make cars smarter and driving safer.