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A Genetic Algorithm Approach for Expedited Crossing of Emergency Vehicles in Connected and Autonomous Intersection Traffic

Title
A Genetic Algorithm Approach for Expedited Crossing of Emergency Vehicles in Connected and Autonomous Intersection Traffic
Author(s)
Lu, QiangKim, Kyoung Dae
Issued Date
2017
Citation
Journal of Advanced Transportation, v.2017
Type
Article
ISSN
0197-6729
Abstract
This paper proposes an intersection control algorithm which aims to determine an efficient vehicle-passing sequence that allows the emergency vehicle to cross an intersection as soon as possible while the travel times of other vehicles are minimally affected. When there are no emergency vehicles within the intersection area, the vehicles are controlled by the DICA that we proposed in our earlier work. When there are emergency vehicles entering the communication range, we prioritize emergency vehicles through optimal ordering of vehicles. Since the number of possible vehicle-passing sequences increases rapidly with the number of vehicles, finding an efficient sequence of vehicles in a short time is the main challenge of the study. A genetic algorithm is proposed to solve the optimization problem which finds the optimal vehicle sequence that gives the emergency vehicles the highest priority. The efficiency of the proposed approach for expedited crossing of emergency vehicles is validated through comparisons with DICA and a reactive traffic light algorithm through extensive simulations. The results show that the proposed genetic algorithm is able to decrease the travel times of emergency vehicles significantly in light and medium traffic volumes without causing any noticeable performance degradation of normal vehicles. © 2017 Qiang Lu and Kyoung-Dae Kim.
URI
http://hdl.handle.net/20.500.11750/5026
DOI
10.1155/2017/7318917
Publisher
WILEY-HINDAWI
Related Researcher
Files in This Item:
000412811700001.pdf

000412811700001.pdf

기타 데이터 / 2.22 MB / Adobe PDF download
Appears in Collections:
Department of Electrical Engineering and Computer Science ARC Lab 1. Journal Articles

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