Foundational Knowledge to Support a Long Distance Passenger Travel Demand Modeling Framework
Federal Highway Administration, Exploratory Advanced Research Program, Project DTFH61-11-C-00015

(PI: Maren Outwater, RSG Inc.)

Methods for modeling long-distance passenger movements are in their infancy in the U.S. There is recent interest at the state and federal levels for highway infrastructure planning, and among agencies studying high‐speed rail and/or airport planning, all of which depend on long-distance travel markets. There is an intersection of policy needs for long-distance passenger modeling and a stronger interest at the state and federal levels. In practice, there have been some recent interest in long-distance passenger modeling for statewide models (e.g., California, Ohio, Arizona) and for high‐speed rail ridership studies (e.g., Florida, California, and the Northeast Corridor) but these models are based primarily on traditional travel demand forecasting methods rather than on a robust understanding of the underlying behavior and how and why it is different than other passenger travel. In contrast, long-distance freight modeling has been studied in research and in practice for many years and a national Freight Analysis Framework (FAF) has been developed and supported by the Federal Highway Administration (FHWA) for many years. This research marks the development of a national passenger framework based on exploring new ways to simulate behavior of long-distance passenger movements.

Advanced modeling methods being used in regional and statewide modeling have created opportunities for planning and policy analysis that were not possible with more conventional methods. The contractor will explore methods to modeling long-distance passenger modeling in the U.S. The core aspects of the approach will focus on the exploration of long-distance travel behavior to establish a model structure and model components that are sensitive to the needed policy variables and also representative of the population, based on empirical evidence.