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.

An assessment of priorities in handling climate change impacts on infrastructures

“…Other studies pay special attention to risks generated by flooding 101 , sea level rise 102 , and avalanches 103 . Some studies also investigate challenges and opportunities for successful adaptation planning and ways to improve decision-making 104 . For this purpose, different models have been used to estimate better alternatives for highway and transit assignment 105 , as well as investment needs and options in the infrastructure's vulnerable components for safeguarding urban mobility under a potential attack scenario 106 .…”

Decision making for transformative change: exploring model use, structural uncertainty and deep leverage points for change in decision making under deep uncertainty

“…Twelve studies focus on the transport sector, with a diversity of motivations across themes of resilience, capacity management, and transitions in support of an overall transformation to a low carbon system (Table 3). Five studies relate to resilience, of road systems to flooding in Peru (Rozenberg et al, 2017b), Mozambique (Espinet et al, 2018) and the USA (Singh et al, 2020), of European ports to global economic conditions (Halim et al, 2016), and of port infrastructure to sea level rise in the USA (Sriver et al, 2018). Four studies focus on managing capacity in response to demand in diverse areas of the transport system: rail and road capacity (Legêne et al, 2020;Hadjidemetriou et al, 2021), airplane manufacturing capacity (Kotta, 2018) and airport capacity planning (Kwakkel et al, 2012).…”

“…In the second, this is associated with the finely balanced choice of routes through which goods are transported, necessitating a detailed spatial representation in the model. The final two resilience studies focus on the resilience of a single piece of infrastructure (a bridge and a port) to sea level rise, thus not requiring geographical disaggregation (Sriver et al, 2018;Singh et al, 2020). These studies uses simple cost-benefit models to evaluate appropriate reinforcement measures at different levels of sea level rise.…”

Smart Transportation Behavior through the COVID-19 Pandemic: A Ride-Hailing System in Iran

“…Combining these entities and the relationships between them creates a structure referred to in the social sciences as the social structure [21,22]. Social network analysis (SNA) has been developed aimed to find the patterns of communication between actors in network structure [15,23] and analyze them to explore the effects of such repetitive patterns in society and organizations [9,24].…”