Mixture of Automatically- and Manually-controlled Vehicles in Intelligent Transport Systems

Authors:
Su-Nan Huang;Steven C. Chan;Wei Ren
Affiliations:
Department of Electrical Engineering and Computer Sciences, University of California at Berkeley, Berkeley, CA 94720, USA;Department of Electrical Engineering and Computer Sciences, University of California at Berkeley, Berkeley, CA 94720, USA;Department of Electrical Engineering and Computer Sciences, University of California at Berkeley, Berkeley, CA 94720, USA
Venue:
Journal of Intelligent and Robotic Systems
Year:
1999

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Abstract

This paper presents a technology which allows for the existence of mixed traffic, as a first step towardsintelligent transport systems. We begin by designing an automatic driving controller called the intelligent vehicle drivingsystem (IVDS). This is a two-layer system: the higher layer analyzes the current scenario and infers the control objective thatassociates with a certain index function; the lower layer optimizes the function provided by the upper layer. IVDS only usesthe measurement of a vehicle’s speed and distance relative to the vehicle in front, together with measurements of thevehicle’s own state. Consequently, the vehicles equipped with the IVDS can operate together with manually-controlledvehicles. Next, a mathematical rule-based model for human drivers is developed. This model attempts to mimic humandriver’s behavior in vehicle following and lane-changing. Finally, we examine the control performance of the proposedcontroller and the potential benefits of mixed traffic by implementing the human driver model and IVDS on an automatedhighway simulator.