Resilience and Efficiency in Transportation Networks

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Description

Urban transportation systems are vulnerable to congestion, accidents, weather, special events, and other costly delays. Whereas typical policy responses prioritize reduction of delays under normal conditions to improve the efficiency of urban road systems, analytic support for investments that improve

Urban transportation systems are vulnerable to congestion, accidents, weather, special events, and other costly delays. Whereas typical policy responses prioritize reduction of delays under normal conditions to improve the efficiency of urban road systems, analytic support for investments that improve resilience (defined as system recovery from additional disruptions) is still scarce. In this effort, we represent paved roads as a transportation network by mapping intersections to nodes and road segments between the intersections to links. We built road networks for 40 of the urban areas defined by the U.S. Census Bureau. We developed and calibrated a model to evaluate traffic delays using link loads. The loads may be regarded as traffic-based centrality measures, estimating the number of individuals using corresponding road segments. Efficiency was estimated as the average annual delay per peak-period auto commuter, and modeled results were found to be close to observed data, with the notable exception of New York City. Resilience was estimated as the change in efficiency resulting from roadway disruptions and was found to vary between cities, with increased delays due to a 5% random loss of road linkages ranging from 9.5% in Los Angeles to 56.0% in San Francisco. The results demonstrate that many urban road systems that operate inefficiently under normal conditions are nevertheless resilient to disruption, whereas some more efficient cities are more fragile. The implication is that resilience, not just efficiency, should be considered explicitly in roadway project selection and justify investment opportunities related to disaster and other disruptions.

Date Created
2017-12-20
Agent

Advancing Alternative Analysis: Integration of Decision Science

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Description

Background: Decision analysis—a systematic approach to solving complex problems—offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate

Background: Decision analysis—a systematic approach to solving complex problems—offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals.

Objectives: We assessed whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics.

Methods: A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and were prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups’ findings.

Results: We concluded that the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients and would also advance the science of decision analysis.

Conclusions: We advance four recommendations: a) engaging the systematic development and evaluation of decision approaches and tools; b) using case studies to advance the integration of decision analysis into alternatives analysis; c) supporting transdisciplinary research; and d) supporting education and outreach efforts.

Date Created
2017-06-13
Agent

Robustness and Extensibility in Infrastructure Systems

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Description

Resilient infrastructure research has produced a myriad of conflicting definitions and analytic frameworks, highlighting the difficulty of creating a foundational theory that informs disciplines as diverse as business, engineering, ecology, and disaster risk reduction. Nevertheless, there is growing agreement that

Resilient infrastructure research has produced a myriad of conflicting definitions and analytic frameworks, highlighting the difficulty of creating a foundational theory that informs disciplines as diverse as business, engineering, ecology, and disaster risk reduction. Nevertheless, there is growing agreement that resilience is a desirable property for infrastructure systems – i.e., that more resilience is always better. Unfortunately, this view ignore that the fact that a single concept of resilience is insufficient to ensure effective performance under diverse and volatile stresses. Scholarship in resilience engineering has identified at least four irreducible resilience concepts, including: rebound, robustness, graceful extensibility, and sustained adaptability.

In this paper, we clarify the meaning of the word resilience and its use, explain the advantages of the pluralistic approach to advancing resilience theory, and clarify two of the four conceptual understandings: robustness and graceful extensibility. Furthermore, we draw upon examples in electric power, transportation, and water systems that illustrate positive and negative cases of resilience in infrastructure management and crisis response. The following conclusions result:

1. Robustness and graceful extensibility are different strategies for resilience that draw upon different system characteristics.
2. Neither robustness nor extensibility can prevent all hazards.
3. While systems can perform both strategies simultaneously, their drawbacks are different.

Robust infrastructure systems fail when policies and procedures become stale, or when faced with overwhelming surprise. Extensible systems fail when a lack of coordination or exhaustion of resources results from decompensation. Consequently, resilience is found neither only in robustness, nor only in extensibility, but in the capacity apply both and switch between them at will.

Date Created
2017-07-17
Agent