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Abstract

Signal control devices have been continuously evolving to make green assignments more responsive to traffic. Recent advances in connected and automated vehicles (CAVs) provide new opportunities to achieve higher performance levels for signalized intersections through an increased coordination level between vehicles and control devices. This study compares two state-of-the-art intersection management algorithms (IMAs) for CAVs and conventional vehicles (CNVs) to an actuated signal control system (ASCS). The two IMAs, the intelligent intersection control algorithm (IICA) and hybrid autonomous intersection management (H-AIM), are designed to enhance the efficiency of intersections by leveraging vehicle automation and connectivity. Our results show that the performance of both IICA and H-AIM improves as the CAV penetration rate increases. H-AIM attains lower average travel times than the state-of-the-practice ASCS only at a CAV penetration rate of 90% and greater. IICA, which jointly optimizes signal phase and timing (SPaT) and CAV trajectories, achieves the best average travel times and throughput for a wide range of CAV ratios. H-AIM yields lower average travel time and higher throughput compared to IICA at penetration rates close to 100%.

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Data Availability Statement

All data, models, and code generated or used during the study appear in the published article.

Acknowledgments

This study is supported by a grant from the National Science Foundation (CNS-1446813). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. For further references related to our work, the reader may visit http://avian.essie.ufl.edu/.

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Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 146Issue 9September 2020

History

Received: Oct 19, 2018
Accepted: Apr 7, 2020
Published online: Jun 22, 2020
Published in print: Sep 1, 2020
Discussion open until: Nov 22, 2020

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Authors

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Sr. Operations Research Scientist, Amadeus, 125 E John W Carpenter Fwy #1100, Irving, TX 75062 (corresponding author). ORCID: https://orcid.org/0000-0002-6345-0215. Email: [email protected]
Patrick Emami [email protected]
Ph.D. Student, Dept. of Computer and Information Science and Engineering, Univ. of Florida, Gainesville, FL 32611. Email: [email protected]
Ph.D. Student, Dept. of Civil and Coastal Engineering, Univ. of Florida, 365 Weil Hall, P.O. Box 116580, Gainesville, FL 32611. ORCID: https://orcid.org/0000-0001-9065-0485. Email: [email protected]
Student, Dept. of Mechanical Engineering, Univ. of Alabama, 286 Hardaway Hall, P.O. Box 870276, Tuscaloosa, AL 35401. ORCID: https://orcid.org/0000-0002-3017-9705. Email: [email protected]
Lily Elefteriadou, Ph.D. [email protected]
Professor, Dept. of Civil and Coastal Engineering, Univ. of Florida, 365 Weil Hall, P.O. Box 116580, Gainesville, FL 32611. Email: [email protected]
Sanjay Ranka, Ph.D. [email protected]
Professor, Dept. of Computer and Information Science and Engineering, Univ. of Florida, Gainesville, FL 32611. Email: [email protected]

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