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We describe the vision system for Alvin, the Autonomous Land Vehicle, addressing in particular the task of road-following. The system builds symbolic descriptions of the road and obstacle boundaries using both video and range sensors. Road segmentation methods are described for video-based road-following, along with approaches to boundary extraction and the transformation of boundaries in the image plane into a vehicle-centered three dimensional scene model. The ALV has performed public road-following demonstrations, traveling distances up to 4.5 km at speeds up to 20 km/hr along a paved road, equipped with an RGB video camera with pan/tilt control and a laser range scanner.