Assessing and Improving the Operational Resilience of a Large Highway Infrastructure System to Worst-Case Losses
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Authors
Alderson, David L.
Brown, Gerald G.
Carlyle, W. Matthew
Wood, R. Kevin
Subjects
infrastructure
operational model
resilience
traffic congestion
defender-attacker-defender
game theory
optimization
operational model
resilience
traffic congestion
defender-attacker-defender
game theory
optimization
Advisors
Date of Issue
2017-07-19
Date
July 19, 2017
Publisher
INFORMS
Language
Abstract
This paper studies the resilience of the regional highway transportation system of the San Francisco Bay Area. Focusing on peak periods for commuter traffic, traffic patterns are computed from a model that includes nonlinear increases in travel times due to congestion and reflects actual travel demands as captured by U.S. Census demographic data. We consider the consequences associated with loss of one or more road, bridge, and/or tunnel segments, where travelers are allowed to reroute to avoid congestion or potentially not travel at all if traffic is bad. We use a sequential game to identify sets of road, bridge, or tunnel segments whose loss results in worst-case travel times. We also demonstrate how the model can be used to quantify the operational resilience of the system, as well as to characterize trade-offs in resilience for different defensive investments, thus providing concise information to guide planners and decision makers.
Type
Article
Description
The article of record as published may be found at http://dx.doi.org/10.1287/trsc.2017.0749
Series/Report No
Department
Operations Research (OR)
Organization
Identifiers
NPS Report Number
Sponsors
Defense Threat Reduction Agency
Office of Naval Research and the Air Force Office of Scientific Research
Office of Naval Research and the Air Force Office of Scientific Research
Funding
Grant HDTRA1-10- 1-0087
Format
23 p.
Citation
Alderson, David L., et al. "Assessing and Improving the Operational Resilience of a Large Highway Infrastructure System to Worst-Case Losses." Transportation Science (2017).
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.