Application of Dynamic Adaptive Planning and Risk-Adjusted Decision Trees to Capture the Value of Flexibility in Resilience and Transportation Planning

Abstract

Transportation infrastructure around the world is under pressure to perform with ever-changing climate scenarios, unpredictable disasters, and stress on resources stemming from rapid urbanization and population growth. Current approaches to developing resilience applied to the transportation system focus primarily on engineering resilience and do not explicitly deal with deep uncertainties arising from climate change. This paper reviews adaptation, a critical aspect of a resilient system in an uncertain and changing environment, as applied in the transportation resilience literature. It compares and contrasts the status of adaptive resiliency in transportation with that in other fields to highlight gaps and research opportunities. The paper then presents Dynamic Adaptive Planning (DAP) as a method for dealing more effectively with deep uncertainty in decision making and offers an approach that combines economic analysis with DAP to enhance decision making under external uncertainties, such as natural disasters, with financial constraints. It presents a case study of the San Francisco–Oakland Bridge to demonstrate the economic benefits of DAP. This paper provides transportation practitioners with guidance on the application of DAP and insight into the economic benefits of such an approach to decision making in various settings including emergency response planning, long-range planning, maintenance and renewal planning, and operations planning. The paper also identifies areas for possible future research combining financial theory with DAP as important in developing more robust decision-making frameworks for handling deep uncertainty.