Abstract
Recently, high-resolution data has emerged as an economical means of obtaining detailed information about signal operations. This has enabled the development of metrics to examine progression, such as cyclic flow profiles similar to those used in the TRANSYT model. Those profiles could further be used to predict changes to traffic flows under trial offset adjustments, enabling offset optimization. An algorithm to do so, called “Link Pivot,” has been used on numerous signalized arterials in Indiana and elsewhere over the past 8 years. This paper reviews the success of the predicted changes through statistical analysis. A linear regression of 569 predicted and actual percent on green values yields an of 0.90. Next, predicted and actual arrival profiles were compared for 357 approaches for which detailed data was available. This analysis finds that the prediction method was successful in about 95% of the approaches considered in this evaluation. The paper dissects the remaining cases and discusses how they could be accommodated.
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Acknowledgments
This work was supported in part by the Joint Transportation Research Program jointly led by the Indiana Department of Transportation and Purdue University. The contents of this paper reflect 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 organizations. These contents do not constitute a standard, specification, or regulation.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 146 • Issue 3 • March 2020
Copyright
©2019 American Society of Civil Engineers.
History
Received: Oct 30, 2018
Accepted: Jul 22, 2019
Published online: Dec 19, 2019
Published in print: Mar 1, 2020
Discussion open until: May 19, 2020
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