On-line road boundary estimation by switching multiple road models using visual features from a stereo camera

This paper describes a road boundary estimation method for autonomous navigation. We consider navigation in a campus environment, where roads (or traversable regions) are not necessarily modeled by a typical road model with a pair of parallel lines, but have a variety of shapes. We therefore use a set of flexible road models with model transition mechanisms for a robust road boundary estimation. This new modeling is incorporated into our multiple sensory feature-based road boundary estimation framework using a particle filter. The proposed method has been successfully applied to various scenes in our campus to realize autonomous navigation.