Identifying Bottlenecks in Roadway Networks in Hurricane Evacuation
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 144, Issue 9
Abstract
The existence of traffic bottlenecks limits the network capacity and leads to massive recurring and nonrecurring congestions during daily traffic peaks and in the critical event of an emergency evacuation. It is important to identify possible network bottlenecks to improve evacuation efficiency. Based on Newell’s simplified kinematic wave model, this paper presents a methodology to identify the network bottleneck links under hurricane evacuation. The methodology mainly includes three parts: (1) achieve traffic flow state updating and propagation based on the kinematic wave model; (2) estimate the evacuation demand using a hurricane evacuation response curve; and (3) identify the bottleneck links according to the mean and variance of the measurement of the degree of congestion. Hence, the proposed methodology is elaborated with a sample network, and the travel time distribution of identified bottleneck is analyzed. Furthermore, the method is applied to the bottleneck identification of a realistic network and results are obtained based on simulations using the methodology.
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Acknowledgments
The project received research funding support from the Institute for Multimodal Transportation (IMTrans) at Jackson State University. The IMTrans is member of the Maritime Transportation Research and Education Center (MarTREC) with the University of Arkansas (lead), Louisiana State University, and the University of New Orleans. MarTREC is one of the Tier I University Transportation Centers funded by the US DOT. The authors are grateful to the two anonymous reviewers for sharing their research insights and providing helpful comments to improve the quality of the paper.
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Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 144 • Issue 9 • September 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: Jun 19, 2017
Accepted: Nov 29, 2017
Published online: Jun 26, 2018
Published in print: Sep 1, 2018
Discussion open until: Nov 26, 2018
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