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The International Journal of Robotics Research
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A Comparative Study of Vision-Based Lateral Control Strategies for Autonomous Highway Driving

Camillo J. Taylor

Department of Computer and Information Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA

Jana Kosecká

Robert Blasi

Jitendra Malik

Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, California, USA

With the increasing speeds of modern microprocessors, it has become ever more common for computer-vision algorithms to find application in real-time control tasks. In this paper, we present an analysis of the problem of steering an autonomous vehicle along a highway based on the images obtained from a CCD camera mounted in the vehicle. We explore the effects of changing various important system parameters like the vehicle velocity, the look-ahead range of the vision sensor, and the processing delay associated with the perception and control systems.

We also present the results of a series of experiments that were designed to provide a systematic comparison of a number of control strategies. The control strategies that were explored include a lead-lag control law, a full-state linear controller, and an input-output linearizing control law. Each of these control strategies was implemented and tested at highway speeds on our experimental vehicle platform, a Honda Accord LX sedan.

Key Words: autonomous highway driving • computer vision • visual servoing

The International Journal of Robotics Research, Vol. 18, No. 5, 442-453 (1999)
DOI: 10.1177/027836499901800502
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