Probabilistic contour extraction with model-switching for vehicle localization

Abstract

Over the past few years, global positioning systems (GPS) have been increasingly used in passenger and commercial vehicles for navigation and vehicle tracking purposes. In practice, GPS systems are prone to systematic errors and intermittent drop-outs that degrade the accuracy of the sensor. In this work, we describe an approach to localizing vehicles with respect to the road given erroneous sensor measurements using only aerial images. Our method works on both urban and rural areas, while being robust to a number of occlusions and shadows. The spatial tracker incorporates multiple measurement models with varying constraints, automatically detecting and switching to the appropriate model. We demonstrate our technique by correcting in real-time highly inaccurate GPS readings collected while driving in diverse areas.