Predictive virtual lane using relative motions between a vehicle and lanes

In this paper, we propose a new lane estimation method to resolve poor detection performance of a camera system using the relative movement between a vehicle and lanes. In implementation of lane keep system (LKS) or lane change control (LXC), it is necessary to build a robust sensing system in obtaining the road information. When reliable road information is not available, we need virtual lane information to control the steering system. Thus we propose a predictive virtual lane (PVL) method to improve lane detection performance using the relative movement between a vehicle and lanes. The proposed PVL enhances the control performance of LKS/LXC for a while even for the detection failures of one side and/or both side lane marks. The performance of the proposed method was evaluated via simulations implemented with CarSim and Matlab/Simulink. Its performance was also validated with a test vehicle on highway system.