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Proceedings Paper

Experience of the ARGO autonomous vehicle
Author(s): Massimo Bertozzi; Alberto Broggi; Gianni Conte; Alessandra Fascioli
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Paper Abstract

This paper presents and discusses the first results obtained by the GOLD (Generic Obstacle and Lane Detection) system as an automatic driver of ARGO. ARGO is a Lancia Thema passenger car equipped with a vision-based system that allows to extract road and environmental information from the acquired scene. By means of stereo vision, obstacles on the road are detected and localized, while the processing of a single monocular image allows to extract the road geometry in front of the vehicle. The generality of the underlying approach allows to detect generic obstacles (without constraints on shape, color, or symmetry) and to detect lane markings even in dark and in strong shadow conditions. The hardware system consists of a PC Pentium 200 Mhz with MMX technology and a frame-grabber board able to acquire 3 b/w images simultaneously; the result of the processing (position of obstacles and geometry of the road) is used to drive an actuator on the steering wheel, while debug information are presented to the user on an on-board monitor and a led-based control panel.

Paper Details

Date Published: 30 July 1998
PDF: 12 pages
Proc. SPIE 3364, Enhanced and Synthetic Vision 1998, (30 July 1998); doi: 10.1117/12.317473
Show Author Affiliations
Massimo Bertozzi, Univ. degli Studi di Parma (Italy)
Alberto Broggi, Univ. degli Studi di Parma (Italy)
Gianni Conte, Univ. degli Studi di Parma (Italy)
Alessandra Fascioli, Univ. degli Studi di Parma (Italy)

Published in SPIE Proceedings Vol. 3364:
Enhanced and Synthetic Vision 1998
Jacques G. Verly, Editor(s)

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