Track detection for autonomous trains

Abstract

This paper presents a way to efficiently use lane detection techniques - known from driver assistance systems - to assist in obstacle detection for autonomous trains. On the one hand, there are several properties that can be exploited to improve conventional lane detection algorithms when used for railway applications. The heavily changing visual appearance of the tracks is compensated by very effective geometric constraints. On the other hand there are additional challenges that are less problematic in classical lane detection applications. This work is part of a sensor system for an autonmous train application that aims at creating an environmentally friendly public transportation system. © 2010 Springer-Verlag.