01587707

Component

https://doi.org/10.3141/2599-01

Increasingly aggressive weather events, such as hurricane-driven storm surges, threaten surface transportation systems and motivate defensive actions, including hardening. Decisions about the design and scale of hardening investments are informed by meteorological records. Historically based probabilities of severe storms are used in practice to define expected values of the intensity of weather assaults (e.g., the 100-year storm) and then to select defenses. The prospects of climate change and rising sea level suggest that assuming weather events are stationary may present added risks to surface transportation infrastructure, particularly in coastal environments. This paper proposes a dynamic, learning-based investment strategy, similar to the concept of real options, that updates estimates of storm surges on the basis of experience and recommends incremental hardening investments when observed trends indicate that additional defense is warranted. Monte Carlo simulation is used to compare and evaluate static (expected value-based) and dynamic investment strategies in the context of storm intensity patterns that are (a) known, (b) incorrectly estimated, and (c) nonstationary, with growing intensity. Results suggest that when the future is well described by past experience, the static, once-and-done decision strategy works well, but when the underlying storm generation process is unknown, or when it is changing (growing) in intensity, the learning-based dynamic strategy is especially advantageous. These results underscore the importance of flexibility in designing storm protection, of tracking weather events closely to detect emerging trends, and of data-driven decision strategies. This dynamic approach to decision making under uncertainty can be applied to other sources of uncertainty, for example, demand estimates.

01589876

16-5751

English

pp 1–8

2016

Transportation Research Record: Journal of the Transportation Research Board

9780309369749

Print

Figures (5) ; References (21)

Decision making; Infrastructure; Investments; Materials and structures protection; Monte Carlo method; Storm surges; Strategic planning; Uncertainty; Weather conditions

Planning and Forecasting; Policy; Security and Emergencies; Transportation (General)

TRIS, TRB, ATRI

Jan 12 2016 6:32PM

• Adaptive Planning for Transportation Corridors Threatened by Sea Level Rise
• Emergency Exit Guidance for U.S. Highway Tunnels
• Feature Selection for Ranking of Most Influential Variables for Evacuation Behavior Modeling Across Disasters
• Flood-Resilient Deployment of Fueling Stations: Extension of Facility Location Problem
• Integrated Optimization Model for Shelter Allocation and Evacuation Routing with Consideration of Reliability
• Modeling Evacuation Behavior Under Hurricane Conditions
• Modeling Shadow Evacuation for Hurricanes with Random-Parameter Logit Model
• Unconventional Intersection Control Strategies for Urban Evacuation
• Using Big Data to Study Resilience of Taxi and Subway Trips for Hurricanes Sandy and Irene