On-Line Road Boundary Tracking with Multiple Sensory Features and a Flexible Road Model

Abstract

This paper describes a method of robustly detecting and tracking road boundaries for autonomous navigation. Since sensory evidence for detecting road boundaries might change from place to place, multiple sensory features should be utilized. It is also necessary to cope with various road shapes. We develop a particle filter-based boundary tracking method. It makes use of various sensory evidence in the filter via respective likelihood functions and adopts flexible road models which are naturally generated in the particle filter framework. The proposed method has been successfully applied to various road scenes.