Quantifying Operational Disruptions as Measured by Transportation Network Reliability
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 6, Issue 4
Abstract
There is global interest by transportation planners and enterprise operators to monitor the inherent uncertainty of transportation networks. Traditional performance metrics may erroneously prioritize project initiatives based on disruptions measured from ideal driving speeds; however, commuters and enterprise operators have demonstrated the ability to accommodate recurrent highway congestion by adjusting departure times, transportation modes, origins, or destinations in logistics planning. Recent performance metrics of transportation network reliability have demonstrated the importance of measuring disruptions from normal operating conditions. Using disaggregate speed data, typical conditions are assessed by mean and median speeds across disparate hours of the day and days of the week. In this paper, we establish a quantitative multicriteria framework for measuring operational disruptions based on the intensity and duration of observed deviations from normal conditions. Advances in data collection provide the disaggregated data that can be used to identify when disruptions occur and the extent of affected volume. This approach influences the prioritization of infrastructure improvements based on deviations from typical conditions and informs appropriate mitigation strategies based on the category and time of disruption. A demonstration of the approach to a geographically diverse region is provided, with implications for several agency-planning horizons.
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Data Availability Statement
Some or all data, models, or code used during the study were provided by a third party
1.
Volume data from count station from Virginia Department of Transportation.
2.
Speed data associated with count stations from INRIX.
Direct requests for these materials may be made to the provider as indicated in the Acknowledgments.
Acknowledgments
This effort has been supported in part by the Virginia Department of Transportation (VDOT), the Virginia Transportation Research Council (VTRC), and the Commonwealth Center for Advanced Logistics Systems (CCALS).
Data used in this work may be issued based on the decision of the third-party providers.
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Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 6 • Issue 4 • December 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Sep 12, 2019
Accepted: Apr 1, 2020
Published online: Jul 28, 2020
Published in print: Dec 1, 2020
Discussion open until: Dec 28, 2020
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