Abstract
With wireless communication and autonomous vehicle control capabilities, automated vehicle technology has the potential to improve the performance of an intersection. The objective of this research was to develop an intersection control algorithm that can jointly optimize the system performance and the trajectory of every single vehicle. An optimization algorithm was developed for a four-approach intersection with the consideration of turning movements and a full set of possible phases under a 100% automated vehicle environment. The intersection controller makes decisions on the vehicle passing sequence using a genetic algorithm–based optimization method, and at the same time it calculates the optimal vehicle trajectories. The optimization process repeats over a time horizon to process continually arriving vehicles. The performance of the proposed algorithm was assessed in various scenario-based simulation experiments and the results were compared with the actuated signal control. It was concluded that the proposed algorithm is able to reduce the intersection average travel time delay by 16.3% to 79.3%, depending on the demand scenario.
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Acknowledgments
This study was supported by grants from the National Science Foundation (CNS-1446813) and Florida Department of Transportation (BDV31-977-45). The authors are grateful to Econolite Group, Inc., and the City of Gainesville for their assistance during the course of this research. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of either the National Science Foundation or the Florida Department of Transportation. For further references the reader may visit http://www.avian.essie.ufl.edu.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 144 • Issue 12 • December 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: Oct 13, 2017
Accepted: Jun 15, 2018
Published online: Oct 12, 2018
Published in print: Dec 1, 2018
Discussion open until: Mar 12, 2019
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