A Study of Bending Mode Algorithm of Adaptive Front-Lighting System Based on Driver Preview Behavior

Abstract

The function of adaptive front-lighting system is to improve the lighting condition of the road ahead and driving safety at night. The current system seldom considers characteristics of the driver’s preview behavior and eye movement. To solve this problem, an AFS algorithm modeling a driver’s preview behavior was proposed. According to the vehicle’s state, the driver’s manipulating input, and the vehicle’s future state change which resulted from the driver’s input, a dynamic predictive algorithm of the vehicle’s future track was established based on an optimal preview acceleration model. Then, an experiment on the change rule of the driver’s preview distance with different speeds and different road curvatures was implemented with the eye tracker and the calibration method of the driver’s preview time was established. On the basis of these above theories and experiments, the preview time was introduced to help predict the vehicle’s future track and an AFS algorithm modeling the driver’s preview behavior was built. Finally, a simulation analysis of the AFS algorithm was carried out. By analyzing the change process of the headlamp’s lighting region while bend turning which was controlled by the algorithm, its control effect was verified to be precise.