Machine Vision Based Vehicle Guidance:
Lateral and Longitudinal Control



An Image of our PATH test vehicle with the stereo camera rig mounted on top, and an image of the interior recording equipement.


This project is funded by California PATH, an Advanced Technology Program that was launched 1986 by the California Department of Transportation (Caltrans) and the Institute of Transportation Studies of the University of California at Berkeley. The California PATH program is committed to finding solutions to the problems of California's current transportation systems. A major issue in this program is to investigate the applicability of advanced highway automation using advanced telecommunications, computing, sensors and actuators, and electronic technologies to traffic management and vehicle control to make automobiles "smarter". PATH is a major element of the national Intelligent Vehicle/Highway Systems (IVHS) effort.

A key role to increase traffic capacity is the platooning concept, i.e. organize the traffic in tightly spaced platoons. Automobiles in such a platoon will be controlled by computers supported by advanced sensor, actuators, and communication to other computers. The current approach is using magnetic sensors sensing magnets in the road for lateral control and doppler radar for obstacle detection and longitudinal control. We are investigating the possibility of supporting these non-visual sensors using visual sensors and suggest an integrated approach. Visual sensing becomes very important during a lane change or while merging into an already established platoon.

Our current approach consists of using stereopsis for longitudinal measurements, obstacle detection and to support longitudinal control. 3D measurements from the stereo component provide the information for finding lane markers, which we detect and track using a lane marker model in order to estimate the lateral position of the car in the lane. We consider the following three problems in vehicle control:


Related Publications:

 * Using Binocular Stereopsis for Vision-based Vehicle Control.
D. Koller, Q.-T. Luong, J. Malik. In Proc. of the Intelligent Vehicles Symposium, pp. 237-242, Paris, France, October 24-26, 1994.
 * Binocular Stereopsis and Lane Marker Flow for Vehicle Navigation: Lateral and Longitudinal Control.
D. Koller, Q.-T. Luong, J. Malik. Technical report UCB/CSD-94-804, March 1994.
Berkeley, May 26, 1994.

Last modified on Tuesday, November 20, 1996, Dieter Koller (koller@vision.caltech.edu)