Metrics, Models and Data for Assessment of Resilience of Urban Infrastructure Systems

Over the past century, our nation has experienced dramatic changes in demographics, and existing socio-technical systems have become more complex and increasingly networked. To complicate matters, our cyber-physical infrastructure has not been maintained, causing unexpected vulnerabilities and cascading failures (ASCE, 2009; AWWA, 2001). As extreme events frequency and magnitude of resulting disasters have increased, emergent behavior, unexpected performance response, and lack of resilience have been noted (Sanford Bernhardt and McNeil, 2008). While there is success in modeling complex response and predicting behaviors of our urban socio-technical networks under stress, the models have grown so complex that data is not available to validate the model predictions (NRC 2009). It is clear that we need to understand our socio-technical system dynamics and resilience at a fundamental level. Resilience is defined as the ability (sufficient capacity and/or flexibility) of a system to experience unexpected shocks or perturbations, and to respond and recover functionality at some acceptable level of performance or action. There is an urgent need for improved understanding of the genesis and evolution of resilience, in particular in urban transportation systems. This will allow the building and enhancement of social and ecological capital and community resilience, as well as to increase system adaptive capacity (including self-organization) and improve the cost-effectiveness of investments in infrastructure systems. An interdisciplinary approach is needed that captures attributes of the complex systems in a region. This requires assembling varied and deep information reflecting current and future conditions, response and usage so that we can expand our knowledge and validate the discoveries and predictions for system performance response. There is a to assemble and create information and modeling resources, develop a framework of variables and relationships that will support a cross-disciplinary and cross-sector exploration of resilience, and build knowledge as test theory and models are developed. In the long term, this will allow the answer to important questions including: What observations (evidence) can we make (identify) to indicate qualitatively whether a specific system or network will demonstrate resiliency? What metrics can be used to evaluate the capacity of a system or network for resilient response? How does resilience response develop, and what factors control or influence the development? Is it a process with thresholds, tipping points, state changes, or is it a continuous function? What can we understand about when investment or adaptive management is warranted to improve resiliency of a system or networks of interdependent systems? The research proposed here will focus on identifying the basic metrics and models that can be used to develop representations of performance response that can be used to define resilience in urban environments, and to bring together data resources that can be investigated to understand and validate the interactive behavior of our complex transportation infrastructure systems.


  • English


  • Status: Active
  • Contract Numbers:


  • Sponsor Organizations:

    Research and Innovative Technology Administration

    University Transportation Centers Program
    Washington, DC  USA  20590
  • Project Managers:

    Crichton-Summers, Camille

  • Performing Organizations:

    New Jersey Institute of Technology (NJIT)

    Department of Civil & Environmental Engineering
    University Heights
    Newark, NJ  USA  07102-1982
  • Principal Investigators:

    Nelson, Priscilla P.

  • Start Date: 20120301
  • Actual Completion Date: 20130630
  • Source Data: RiP Project 29302

Subject/Index Terms

Filing Info

  • Accession Number: 01467832
  • Record Type: Research project
  • Source Agency: University Transportation Research Center
  • Contract Numbers: 49111-33-23
  • Files: UTC, RiP, USDOT
  • Created Date: Jan 3 2013 3:40PM