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Uncertain population behaviors in a regional emergency could potentially harm the performance of the region's transportation system and subsequent evacuation effort. The integration of behavioral survey data with travel demand modeling enables an assessment of transportation system performance and the identification of operational and public health countermeasures. This paper analyzes transportation system demand and system performance for emergency management in three disaster scenarios. A two-step methodology first estimates the number of trips evacuating the region, thereby capturing behavioral aspects in a scientifically defensible manner based on survey results, and second, assigns these trips to a regional highway network, using geographic information systems software, thereby making the methodology transferable to other locations. Performance measures are generated for each scenario including maps of volume-to-capacity ratios, geographic contours of evacuation time from the center of the region, and link-specific metrics such as weighted average speed and traffic volume. The methods are demonstrated on a 600 segment transportation network in Washington, DC (USA) and are applied to three scenarios involving attacks from radiological dispersion devices (e.g., dirty bombs). The results suggests that: (1) a single detonation would degrade transportation system performance two to three times more than that which occurs during a typical weekday afternoon peak hour, (2) volume on several critical arterials within the network would exceed capacity in the represented scenarios, and (3) resulting travel times to reach intended destinations imply that un-aided evacuation is impractical. These results assist decisions made by two categories of emergency responders: (1) transportation managers who provide traveler information and who make operational adjustments to improve the network (e.g., signal retiming) and (2) public health officials who maintain shelters, food and water stations, or first aid centers along evacuation routes. This approach may also interest decisionmakers who are in a position to influence the allocation of emergency resources, including healthcare providers, infrastructure owners, transit providers, and regional or local planning staff., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Recent catastrophic losses because of floods require developing resilient approaches to flood risk protection. This article assesses how diversification of a system of coastal protections might decrease the probabilities of extreme flood losses. The study compares the performance of portfolios each consisting of four types of flood protection assets in a large region of dike rings. A parametric analysis suggests conditions in which diversifications of the types of included flood protection assets decrease extreme flood losses. Increased return periods of extreme losses are associated with portfolios where the asset types have low correlations of economic risk. The effort highlights the importance of understanding correlations across asset types in planning for large-scale flood protection. It allows explicit integration of climate change scenarios in developing flood mitigation strategy., (© 2012 Society for Risk Analysis.)

Considerable attention is focused on plans for sheltering or evacuating the population of the US national capital region in response to a regional emergency such as a terrorist attack or natural disaster. Such planning engages multiple disciplines spanning infrastructure engineering, emergency management, health care, mass communication, water and food supply, logistics, and others. Knowledge of population behaviors should influence the many dimensions of protection, prevention, response, and recovery. Of particular interest are the behaviors and needs of the resident and non-resident populations in the aftermath of a regional disaster, including those at home, at work, and traveling. The authors deployed a 30-min telephone survey to 2700 residents of the region to gain knowledge of their intended behaviors in the event of a variety of potential dirty bomb attacks. The survey provides a unique foundation for the current paper. The paper will identify and model the assumptions of population behaviors that most affect agency priorities for emergency planning including regional sheltering and evacuation following a radiological disaster such as a dirty bomb. The technical approach assessed several planning initiatives across performance criteria derived from strategic plans and applied combinations of behavioral assumptions to vary the relative importance of each criterion. The results reveal the behavioral scenarios that are most significant to the prioritization of planning initiatives and identify the highest and lowest priority initiatives across the criteria used., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Coordination and layering of models to identify risks in complex systems such as large-scale infrastructure of energy, water, and transportation is of current interest across application domains. Such infrastructures are increasingly vulnerable to adjacent commercial and residential land development. Land development can compromise the performance of essential infrastructure systems and increase the costs of maintaining or increasing performance. A risk-informed approach to this topic would be useful to avoid surprise, regret, and the need for costly remedies. This article develops a layering and coordination of models for risk management of land development affecting infrastructure systems. The layers are: system identification, expert elicitation, predictive modeling, comparison of investment alternatives, and implications of current decisions for future options. The modeling layers share a focus on observable factors that most contribute to volatility of land development and land use. The relevant data and expert evidence include current and forecasted growth in population and employment, conservation and preservation rules, land topography and geometries, real estate assessments, market and economic conditions, and other factors. The approach integrates to a decision framework of strategic considerations based on assessing risk, cost, and opportunity in order to prioritize needs and potential remedies that mitigate impacts of land development to the infrastructure systems. The approach is demonstrated for a 5,700-mile multimodal transportation system adjacent to 60,000 tracts of potential land development., (© 2011 Society for Risk Analysis.)

Radiological nuclear emergency responders must be able to coordinate evacuation and relief efforts following the release of radioactive material into populated areas. In order to respond quickly and effectively to a nuclear emergency, high-level coordination is needed between a number of large, independent organizations, including police, military, hazmat, and transportation authorities. Given the complexity, scale, time-pressure, and potential negative consequences inherent in radiological emergency responses, tracking and communicating information that will assist decision makers during a crisis is crucial. The emergency response team at the Angra dos Reis nuclear power facility, located outside of Rio de Janeiro, Brazil, presently conducts emergency response simulations once every two years to prepare organizational leaders for real-life emergency situations. However, current exercises are conducted without the aid of electronic or software tools, resulting in possible cognitive overload and delays in decision-making. This paper describes the development of a decision support system employing systems methodologies, including cognitive task analysis and human-machine interface design. The decision support system can aid the coordination team by automating cognitive functions and improving information sharing. A prototype of the design will be evaluated by plant officials in Brazil and incorporated to a future trial run of a response simulation.

Military and industrial facilities need secure and reliable power generation. Grid outages can result in cascading infrastructure failures as well as security breaches and should be avoided. Adding redundancy and increasing reliability can require additional environmental, financial, logistical, and other considerations and resources. Uncertain scenarios consisting of emergent environmental conditions, regulatory changes, growth of regional energy demands, and other concerns result in further complications. Decisions on selecting energy alternatives are made on an ad hoc basis. The present work integrates scenario analysis and multiple criteria decision analysis (MCDA) to identify combinations of impactful emergent conditions and to perform a preliminary benefits analysis of energy and environmental security investments for industrial and military installations. Application of a traditional MCDA approach would require significant stakeholder elicitations under multiple uncertain scenarios. The approach proposed in this study develops and iteratively adjusts a scoring function for investment alternatives to find the scenarios with the most significant impacts on installation security. A robust prioritization of investment alternatives can be achieved by integrating stakeholder preferences and focusing modeling and decision-analytical tools on a few key emergent conditions and scenarios. The approach is described and demonstrated for a campus of several dozen interconnected industrial buildings within a major installation., (Copyright © 2010 SETAC.)

This article addresses the problem of allocating devices for localized hazard protection across a region. Each identical device provides only local protection, and the devices serve localities that are exposed to nonidentical intensities of hazard. A method for seeking the optimal allocation Policy Decisions is described, highlighting the potentially competing objectives of maximizing local risk reductions and coverage risk reductions. The metric for local risk reductions is the sum of the local economic risks avoided. The metric for coverage risk reductions is adapted from the p-median problem and equal to the sum of squares of the distances from all unserved localities to their closest associated served locality. Three graphical techniques for interpreting the Policy Decisions are presented. The three linked graphical techniques are applied serially. The first technique identifies Policy Decisions that are nearly Pareto optimal. The second identifies locations where sensor placements are most justified, based on a risk-cost-benefit analysis under uncertainty. The third displays the decision space for any particular policy decision. The method is illustrated in an application to chemical, biological, and/or radiological weapon sensor placement, but has implications for disaster preparedness, transportation safety, and other arenas of public safety.

Accident analysis involves the use of both quantitative and qualitative data in decision-making. The aim of this paper is to demonstrate the synthesis of relevant quantitative and qualitative evidence for accident analysis and for planning a large and diverse portfolio of highway investment projects. The proposed analysis and visualization techniques along with traditional mathematical modeling serve as an aid to planners, engineers, and the public in comparing the benefits of current and proposed improvement projects. The analysis uses data on crash rates, average daily traffic, cost estimates from highway agency databases, and project portfolios for regions and localities. It also utilizes up to two motivations out of seven that are outlined in the Transportation Equity Act for the 21st Century (TEA-21). Three case studies demonstrate the risk-based approach to accident analysis for short- and long-range transportation plans. The approach is adaptable to other topics in accident analysis and prevention that involve the use of quantitative and qualitative evidence, risk analysis, and multi-criteria decision-making for project portfolio selection.

We address the problem of distributing safety-enhancing devices across a region, where each identical device provides for only local protection of the population. The devices protect nonidentical sectors of the population. The sectors of population are exposed to nonidentical intensities of hazard. A method for the screening and prioritizing of needs for the protective devices is described. An approach of risk-benefit-cost analysis under uncertainty is recommended as follows. Measures of hazard intensity and population exposure are identified. Exogenous parameters that influence assessments of risks, benefits, and costs are identified. Uncertainties of the exogenous parameters are propagated by interval analysis. Several tiers of the plausibility of need for protection are identified. The tiers are useful in setting priorities for the distribution of the safety devices. The method is demonstrated in an engineering application to roadway lighting, but has implications for disaster preparedness, anti-terrorism, transportation safety, and other arenas of public safety.

This article presents an approach to the problem of terrorism risk assessment and management by adapting the framework of the risk filtering, ranking, and management method. The assessment is conducted at two levels: (1) the system level, and (2) the asset-specific level. The system-level risk assessment attempts to identify and prioritize critical infrastructures from an inventory of system assets. The definition of critical infrastructures offered by Presidential Decision Directive 63 was used to determine the set of attributes to identify critical assets--categorized according to national, regional, and local impact. An example application is demonstrated using information from the Federal Highway Administration National Bridge Inventory for the State of Virginia. Conversely, the asset-specific risk assessment performs an in-depth analysis of the threats and vulnerabilities of a specific critical infrastructure. An illustration is presented to offer some insights in risk scenario identification and prioritization, multiobjective evaluation of management options, and extreme-event analysis for critical infrastructure protection.

We address the need for allocation of resources to run-off-road and fixed-object hazards on immense secondary road systems. In Virginia, there are 95,000km of roadway with uncharacterized hazards in need of guardrail upgrade, installation, or related warning signs or other protection. A decision aid is developed to assist the planner in guardrail resource allocation by accounting for the potential crash severities, traffic exposures, costs of treatment, and other factors. A premise is that no single benefit-cost ratio or selection criterion applies across all localities. The decision aid enables the planner to interpret the variety of benefits and costs in their own units, emphasizing the needs and preferences of individual localities. The paper describes: (1) archiving and comparison of protected and unprotected hazards; (2) regional screening of hazardous corridors and (3) multicriteria benefit-cost analyses of guardrail sites. A case study of guardrail selection is presented.

This paper contributes a methodological framework to identify, prioritize, assess, and manage risk scenarios of a large-scale system. Qualitative screening of scenarios and classes of scenarios is appropriate initially, while quantitative assessments may be applied once the set of all scenarios (hundreds) has been prioritized in several phases. The eight-phase methodology is described in detail and is applied to operations other than war. The eight phases are as follows: Phase I, Scenario Identification-A hierarchical holographic model (HHM) is developed to describe the system's "as planned" or "success" scenario. Phase II, Scenario Filtering-The risk scenarios identified in Phase I are filtered according to the responsibilities and interests of the current system user. Phase III, Bi-Criteria Filtering and Ranking. Phase IV, Multi-Criteria Evaluation. Phase V, Quantitative Ranking-We continue to filter and rank scenarios based on quantitative and qualitative matrix scales of likelihood and consequence; and ordinal response to system resiliency, robustness, redundancy. Phase VI, Risk Management is performed, involving identification of management options for dealing with the filtered scenarios, and estimating the cost, performance benefits, and risk reduction of each. Phase VII, Safeguarding Against Missing Critical Items--We examine the performance of the options selected in Phase VI against the scenarios previously filtered out during Phases II to V. Phase VIII, Operational Feedback-We use the experience and information gained during application to refine the scenario filtering and decision processes in earlier phases. These eight phases reflect a philosophical approach rather than a mechanical methodology. In this philosophy, the filtering and ranking of discrete scenarios is viewed as a precursor to, rather than a substitute for, consideration of the totality of all risk scenarios.