Fused Front Lane Trajectory Estimation Based on Current ADAS Sensor Configuration

Abstract

Intelligent driving functions, such as ACC (Adaptive Cruise Control) and ALC (Automated Lane Changes), require lane assignment for objects. It relies on an accurate traffic lane path estimation. This paper proposes a fused front lane trajectory estimation algorithm based on current common ADAS sensor configuration. This trajectory is generated by fusing information of lane markers, front object trails and host motion state. This algorithm uses a clothoid lane model and its coefficients is estimated by a Kalman Filter, which weighs predicted model state and current measurement. This approach is verified by a set of real road test data.