Enhancement of global vehicle localization using navigable road maps and dead-reckoning

Abstract

This paper presents a data fusion strategy for the global localization of car-like vehicles. The system uses raw GNSS measurements, dead-reckoning sensors and road map data. We present a new method to use the map information as a heading observation in a Kalman filter. Experimental results show the benefit of such a method when the GPS information is not available. Then, we propose a conservative localization strategy that relies mainly on dead-reckoned navigation. The GNSS measurements and the map information are not used when consistency tests are doubtful. Experimental tests indicate that the performance is effectively better when using only the available consistent information.