This research proposes a small exploratory study to design and develop an improved set of analytical models to assess the interaction among human managers, technical infrastructure, and a dynamic population of users. Such problems create extraordinary challenges for public agencies that have responsibility for maintaining continuity of operations and security for metropolitan regions. The complexity of the interactions increases as conditions change or sudden, unanticipated events disrupt the performance of the technical systems. Human managers, responsible for the management of technical systems, need to intervene to reduce damaging consequences for the users. These are complex systems that require an integrated, interdisciplinary approach to modeling the dynamic behavior of the population of users and managers in their interaction with the infrastructure. Existing models, based on single disciplinary approaches, are inadequate for this problem.
This study will address the problem of disruption in complex transportation systems. It will make three contributions to the management of critical infrastructure at risk from extreme events. First, it explores an interdisciplinary approach to building computational models of real-time decision making that have not been done before in a workable manner. This approach draws upon knowledge and techniques in civil engineering, public policy, and computer science to develop models of rapid assessment of risk and allocation of resources and time that can inform decision processes by practicing managers who confront danger and need to take urgent action. Second, the models, when developed in detail, will yield tested metrics for characterizing sociotechnical infrastructure in reference to urban transportation and emergency management networks. Third, the theoretical approach offers a method of assessing the interaction of cascading dysfunction in damaged technical systems countered by informed adaptation in organizational emergency response systems to provide enhanced decision support in managing disaster.
