Modal Preference Modeling of Transportation Demand and Supply for Strategy Portfolio Analyses-Results and Future Plans

摘要

Future demand for transportation is and will continue to be shaped by forces that have not been well accommodated in past strategic analyses; further, regression-based analytical methods are less well suited than generative methods for projecting demands for modal options that have little historical data on which to base regressions. New transportation modes, business models, consumer behaviors and vehicle capabilities are the primary factors not well managed in regressive demand projection methods. An example is the ability to study co-evolutionary effects such as a "virtual" mode or modes (i.e., interacting by telepresence as a modal option) on population dynamics or urbanization trends. The risk is that current national transportation strategies in air mobility tend to be constrained by "business as usual" considerations of a rear-view-facing nature. In addition, air transportation demand projections are frequently made in modal isolation; that is, projections for air travel demand have not typically accounted for the full context of all other existing and prospective new modal options and their improvements. Further, if the strategy development processes do not consider the prospect of vastly different characteristics of external context, including new consumer behaviors and modal options then the strategies carry inherent risks. The plausible ranges and combinations in trends or vectors in technologies, energy, environmental, and prosperity considerations comprise a wide range of future conditions s in which strategies must be evaluated. Because the ranges and combinations of vectors cannot be accurately predicted, we evaluate policy and technology investment strategies in the context of plausible ranges and combinations of these externalities. This paper describes our team's work to mitigate these risks through an approach for managing uncertainty both qualitatively and (to some extent) quantitatively. First, we describe our agent-based modal preference method for modeling national transportation system demand and supply; then we discuss the means employed to account for uncertainties about future economic, demographic, environmental, and technological conditions. The paper summarizes the projections of demands that are satisfied by conventional and alternative modes for automotive, rail, bus, airlines, telepresence, and on-demand mobility in small future transport aircraft. The results illustrate plausible levels of demand for new airspace and airport capacities and capabilities, previously not well quantified, for which new technology strategies would be needed in the National Airspace System. The plans for applying the method for continued technology portfolio analysis are described.