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

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Abstract

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

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Authors and Affiliations

  1. Department of Electrical Engineering and Computer Sciences, University of California at Berkeley, Berkeley, CA, 94720, USA

    Su-Nan Huang, Steven C. Chan & Wei Ren

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  1. Su-Nan Huang
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  2. Steven C. Chan
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  3. Wei Ren
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Huang, SN., Chan, S.C. & Ren, W. Mixture of Automatically- and Manually-controlled Vehicles in Intelligent Transport Systems. Journal of Intelligent and Robotic Systems 24, 175–205 (1999). https://doi.org/10.1023/A:1008002207158

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