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The contents of this report reflect the views of the author(s), who is responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the Virginia Department of Transportation, the Commonwealth Transportation Board, or the Federal Highway Administration. This report does not constitute a standard, specification, or regulation. Any inclusion of manufacturer names, trade names, or trademarks is for identification purposes only and is not to be considered an endorsement.

Title:

Improving the Identification and Characterization of Arterial Congestion Bottlenecks
Authors:
Mo Zhao, Ph.D., and Ramkumar Venkatanarayana, Ph.D., P.E.
Ramkumar Venkatanarayana
Ramkumar Venkatanarayana
Mo Zhao
Mo Zhao
Year: 2019
VTRC No.: 19-R20
Abstract:


Performance-based and data-driven approaches are increasingly employed by transportation professionals to provide a strong foundation for making sound decisions and for optimizing investments. 
This study developed and evaluated one such method for identifying and ranking traffic bottlenecks.  Bottleneck analysis tools currently available to the Virginia Department of Transportation (VDOT) typically analyze links along a roadway and do not consider the conditions on the side streets at intersections.  This study proposed a new sketch planning bottleneck analysis and ranking method for arterial intersections using a node-link approach that examines all intersection approaches.  The methodology uses widely available datasets such as probe vehicle speeds and annual average daily traffic (AADT).  Impacts of different congestion threshold speeds and queue estimation methodologies were studied.  A tool was developed to summarize,visualize, and drill down the results interactively. 

 

A case study was conducted using a Northern Virginia urban arterial network with 245 nodes, and an expert panel validated the study results with their field observations. Their comments and feedback showed high confidence in the results,pointing to the success of this proof-of-concept study.  Additional feedback from VDOT, the Virginia Office of Intermodal Planning and Investment (OIPI), and localities indicated their high interest in using this methodology mainly because of the quantitative performance measures and the ability to support data-driven decision making.  Their intended use cases include improved planning, funding, and evaluation of bottleneck mitigation solutions across their region and the state.  Several lessons were learned during this study and documented, which will help to scale up this methodology for potential statewide adoption.