SGER: Modeling Fragility of Sociotechnical Systems: A Transportation Study

本研究提出了一个小的探索性研究，设计和开发一套改进的分析模型，以评估人类管理人员，技术基础设施和用户的动态人口之间的相互作用。这些问题给负责维持大都市地区业务连续性和安全的公共机构带来了极大的挑战。随着条件的变化或突然的、不可预见的事件破坏技术系统的性能，交互的复杂性会增加。负责管理技术系统的人类管理者需要进行干预，以减少对用户的破坏性后果。这些都是复杂的系统，需要一个集成的，跨学科的方法来建模的动态行为的人口的用户和管理人员在他们的互动与基础设施。现有的模型，基于单一学科的方法，是不足以解决这个问题，本研究将解决这个问题的中断在复杂的运输系统。它将为管理面临极端事件风险的关键基础设施做出三项贡献。 首先，它探索了一种跨学科的方法来建立实时决策的计算模型，以前没有以可行的方式进行。 这种方法借鉴了土木工程，公共政策和计算机科学的知识和技术，以开发快速评估风险和分配资源和时间的模型，这些模型可以为面临危险并需要采取紧急行动的实践管理人员的决策过程提供信息。 第二，模型，详细开发时，将产生测试的指标，以表征社会技术基础设施的参考城市交通和应急管理网络。 第三，理论方法提供了一种方法来评估级联功能障碍的相互作用，在受损的技术系统反对知情的适应组织的应急响应系统，以提供更强的决策支持，在管理灾害。

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.