FIGURE 3-1 Generic inputs into an air transportation system performance model. Of particular note is the interconnectivity among the inputs, suggesting the need for substantial analyses at the input component level to understand sensitivities.

more detailed models into the higher-level models, so that higher-level models often cannot reflect such sensitivities, even though the more detailed models may show them to be important for problem identification and resolution. When reporting the complete results of a suite of system models, it is important to include the results of the more detailed models where they are relevant to the solution. A description of four levels of models that could be included in a suite of system models appears in Appendix E.

A particular challenge in using a suite of system models for a sociotechnical system as complex as air transportation will be to capture the nonlinear dynamics of interactions among components, which makes it difficult to combine the results from different models. Additional research is needed to overcome this challenge.

ANALYSIS AND DESIGN TO IMPROVE AIR TRANSPORTATION SYSTEM PERFORMANCE

Improving the performance of the air transportation system requires a good understanding of the operation of the current system and the ability to model and analyze the performance of new operational concepts. The air transportation system, however, is a complex, human-centered system that involves multiple technologies, organizational structures, human behaviors, and competing economic entities. Modeling such a complex system is extremely difficult and requires the ability to model interdisciplinary systems and operational concepts (including cross-functional operational concepts) in terms of system performance (comfort, convenience, costs, and societal impacts) and the ability to satisfy the often-conflicting objectives of various stakeholders. Improving the ability to model and measure systemwide performance and assess risks associated with the development, deployment, and operation of complex new systems will help avoid historical precedents in which large new system projects have been cancelled prior to completion because of delays, cost increases, and/or the inability to meet design requirements.

As system complexity increases, it becomes more difficult to guard against dysfunctional interactions. Problems may arise from unanticipated interactions among automated subsystems and from unanticipated interactions among different organizations and parts of organizations. The ability to develop complex systems while effectively managing problems at the intersections between organizations, disci-



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