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Bay Area transportation network resilience

Graduate Researcher(s): 
Mahalia Miller
Gitanjali Bhattacharjee
Rodrigo Silva
Faculty Advisor/PI: 
Jack Baker
California Department of Transportation
Project Sponsor: 
National Science Foundation, Pacific Earthquake Engineering Research Center

The goal of this project is to build a model that links individual bridges’ earthquake-damage-induced traffic capacity loss and restoration with network-level performance over time (e.g., additional travel time and loss of critical connections). The research objectives are to quantify how individual bridge performance contributes to network-level resilience, and to understand how resilience can be improved through mitigation actions at the individual-bridge level. This work builds on our prior work to simulate regional-scale seismic hazards, bridge damage and network disruption, by adding models to characterize the restoration over time of bridge traffic capacity and network functionality. We plan to relate individual bridge risk to community resilience, and to efficiently quantify the impact of changing component performance (e.g., via retrofit) on that resilience assessment.

Community resilience is the focus of significant attention from a number of civic and research agencies. Common activities include the setting of resilience goals and the development of frameworks for describing resilience. This project aims to develop predictive models that relate individual bridge performance to those broader resilience goals. One aim of the project is thus to provide a link between PEER’s work on enhanced bridge systems and the broader world’s interest in enhanced disaster resilience. We also aim to identify key transportation network components and corridors whose functioning is deemed critical to regional resilience.

By quantifying the benefits of improved bridge technology for community resilience, this project will help make the case for investing in higher-performance bridge systems. By using performance metrics more closely aligned with those of relevance for resilience assessments, this project will also support regional resilience planning efforts, such as SPUR’s work with San Francisco and those of the region’s Chief Resilience Officers.




Gomez, C., and Baker, J. W. (2017). “Large-scale optimization strategies for risk-informed decision support in infrastructure systems: an application to transportation networks exposed to seismic hazards.” 12th International Conference on Structural Safety and Reliability (ICOSSAR), Vienna, Austria, 7p.

Miller, M., and Baker, J. W. (2016). “Coupling mode-destination accessibility with a quantitative seismic-risk assessment to identify at-risk communities.” Reliability Engineering and System Safety, 147, 60–71.

Miller, M., and Baker, J. W. (2015). “Ground-motion intensity and damage map selection for probabilistic infrastructure network risk assessment using optimization.” Earthquake Engineering & Structural Dynamics, 44(7), 1139–1156.

Gomez, C., Baker, J. W., Castiblanco, D., and Faber, M. H. (2015). “Coupled pre- and post-disaster decisions in the context of infrastructure resilience.” 8th International Forum on Engineering Decision Making, Kyoto, Japan.

Baker, J. W., Miller, M. K., and Markhvida, M. (2015). “Local Measures of Disruption for Quantifying Seismic Risk and Reliability of Complex Networks.” 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12, Vancouver, Canada, 8p.

Miller, M., Cortes, S., Ory, D., and Baker, J. W. (2015). “Estimating impacts of catastrophic network damage from earthquakes using an activity-based travel model.” Transportation Research Board 94th Annual Meeting Compendium of Papers, Washington, D.C., Paper 15–2366.