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

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 1 Chief Executive Office, 205 Skimino Landing Dr., Williamsburg, VA 23188, AIAA Fellow 2 Chief Science Officer, 508 Olive St., Santa Cruz, CA 95076, AIAA Member 3 Chief Technology Officer, 784 Rosewood Dr., Palo Alto, CA 94303, AIAA Member 4 Director, Transportation Research, Old Dominion University, 5115 Hampton Blvd, Norfolk, VA 23529, AIAA 2 Chief Science Officer, 508 Olive St., Santa Cruz, CA 95076, AIAA Member 3 Chief Technology Officer, 784 Rosewood Dr., Palo Alto, CA 94303, AIAA Member 4 Director, Transportation Research, Old Dominion University, 5115 Hampton Blvd, Norfolk, VA 23529, AIAA Fellow 5 Senior Consultant, LMI, 2000 Corporate Ridge, McLean, VA 22102, AIAA Senior Member 6 Senior Fellow, LMI, 2000 Corporate Ridge, McLean, VA 22102 7 Senior Economist, GRA, Inc., 115 West Av, Suite 201, Jenkintown, PA 19046 8 Manager of Strategic Analysis, Aeronautics Research Mission Directorate, NASA HQ, Washington DC 20546