Toll Plaza Lane Choice and Lane Configuration Strategy for Autonomous Vehicles in Mixed Traffic
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 12
Abstract
Toll plazas are one kind of highway node that pose a challenge to the flow of autonomous vehicles (AVs). Some toll roads have open road tolling (ORT), which makes it easier and more efficient for AVs, but most toll plazas do not have ORT. The authors developed a decision model to assist AVs in choosing the right lane that involves two main indicators, the rod speed () and the decision-making value (). The decision model was applied to a six-lane toll plaza with manual toll collection (MTC), electronic toll collection (ETC), and electronic toll collection for AVs toll types. The suitable lane configurations for the varying percentages of AVs in traffic were as follows: at 10% AV, the optimal lane configuration was 4 MTC and (4M2EA), at 30% AV it was 3M3EA, at 40%–60% AV it was 3M2EA1A, and at 70% AV it was 2M2EA2A. Thus AVs should share toll lanes with ETC manned vehicles before the population of AVs reaches 30%; after that dedicated lanes may be introduced. It was also concluded that a 10% increase in AVs reduces delays by 9% if the populations of ETC and MTC vehicles are equal.
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Data Availability Statement
References to the data used during the study appear in the published article. Some data and algorithms that were used and generated from this study are available from the corresponding author upon reasonable request. These data include vehicle arrival patterns, toll lane selection, and departure patterns, asd well as a compact algorithm based on the formulations developed in this paper.
Acknowledgments
The authors acknowledge the Chinese Scholarship Council (CSC) for academically sponsoring one of the authors.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 146 • Issue 12 • December 2020
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Nov 27, 2019
Accepted: Jul 13, 2020
Published online: Sep 17, 2020
Published in print: Dec 1, 2020
Discussion open until: Feb 17, 2021
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