Abstract
This paper describes the development of a forward collision avoidance system based on driver behavior characteristics considering tail lamp information of preceding vehicle. The tail lamp information is acquired by an image processing unit or a car-to-car communication system. Focusing on today’s active safety devices, a number of vehicle dynamics control systems and driving assistance systems have been being developed for many years and some of them have been already equipped in vehicles on the market. However, the realization of fully automated driver assistance system is still far in real-world situation. In developing intelligent safety systems, it must regard the closed-loop driver-vehicle cooperative characteristics. Therefore, the design of human-machine interface has become a major issue of the driver assistance system study to obtain the satisfactory interaction in cooperative maneuver between safety system and human driver manual control. To achieve the best cooperation of human driver and the driver assistance systems, it is necessary to understand human driving behavior. First, a large amount of urban driving data is collected by on-road experiments using a continuous sensing drive recorder equipped in the micro-scale electric vehicle. Next, normal deceleration characteristics are analyzed by using the stored driving data based on time-to-collision and tail lamp state of preceding vehicle. Finally, the accelerator pedal input model is designed by analyzed normal deceleration characteristics and the validity of the model is verified.
Keywords: Automobile, Active Safety, Forward Collision, Driver Behavior, Tail Lamp State Recognition