Abstract
Traffic congestion and freeway bottlenecks continue to challenge existing transportation networks. This study presents a systematic method to evaluate freeway performance and locate and rank freeway bottlenecks while accounting for both intensity and reliability dimensions of traffic congestion. A data-driven approach is used to determine a local range of the weighting factor. Based on the vehicle probe data collected on four interstate freeways in Mecklenburg County, North Carolina, a case study is conducted to illustrate this new method. Numerical results clearly indicate that although two freeway segments have nearly identical reliability values, their intensity levels can be significantly different, and vice versa. Hence, quantifying both dimensions of traffic congestion in freeway bottleneck studies is necessary. The research results can provide insightful and objective information for decision makers and transportation professionals to systematically assess traffic conditions along freeway segments and objectively locate and rank freeway bottlenecks, competently develop congestion mitigation strategies, and thus allocate limited transportation funding in a more effective and efficient manner.
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Acknowledgments
The authors would like to thank the North Carolina Department of Transportation (NCDOT) for sponsoring this project. The content of this paper reflects the views of the authors, who are responsible for the facts and the accuracy of the data presented herein, and do not necessarily reflect the official views or policies of the sponsoring organization. The probe speed data and TMC segment information used in this paper were obtained from INRIX, Inc.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 144 • Issue 3 • March 2018
Copyright
©2017 American Society of Civil Engineers.
History
Received: Nov 18, 2016
Accepted: Aug 25, 2017
Published online: Dec 28, 2017
Published in print: Mar 1, 2018
Discussion open until: May 28, 2018
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