Understanding Transportation as a System-of-Systems Design Problem

*The purposes of this paper are to introduce an emerging class of problems called systemof-systems, present the primary traits of the class, and then described the relevant implications for the aerospace design community. Two primary traits, evolutionary and emergent behavior, are highlighted since they call attention to a network-of-systems, dynamic-behavior focus as opposed to an individual system, static-behavior focus. Further, methodological needs for investigation of these traits lie outside present capability in the community. To explore these implications in depth, the casting of future transportation concepts as a system-of-systems is described. A recently developed “proto-method” for this class of problems is presented and explored in the context of the transportation domain, including promising approaches for building effective modeling and simulation. The casting of civil transportation as a system-of-systems problem is important as much of the literature on system-of-systems (limited as it is) resides primarily in the defense systems domain. I. Introduction ROBLEMS of significant complexity are facing decision-makers within government and industry, and the moniker of “system-of-systems” (heretofore shortened to SoS) is increasingly being applied to problems of this type. Effective system analysis for decision-support quickly becomes unmanageable in this context, with multiple, heterogeneous, distributed systems involved and couched in networks at multiple levels. The situation is exacerbated by the fact that most organizations (and their processes) remain in the “stovepipe” mode- their people and tools are configured to study within narrow bins with little or no analysis across those bins. Current frames of reference, thought processes, analysis, and design methods are not complete for these SoS problems, exemplified in this paper by future national transportation system realizations. A holistic framework is needed that enables decision makers to discern whether related infrastructure, policy, and/or technology considerations together are good, bad (or indifferent) over time. 1 And this need is urgent, for the SoS type almost always involves decisions that commit large amounts of money, for which ultimate failure or success carries heavy consequences over several generations, and that impact large segments of the public. The costs associated with a chosen path may still be high, but the intent is to maximize the probability that these costs result in good consequences rather than bad. P