CALIBRATING THE INTERCITY HIGH SPEED RAIL (HSR) CHOICE MODEL FOR THE RICHMOND-WASHINGTON, D.C. CORRIDOR

Abstract

This study aims to quantitatively investigate how the introduction of high-speed rail (HSR) influences traveler’s choice behavior. The study focuses on recalibrating the Florida-based HSR choice model to fit the intercity travel northward from Richmond, Virginia to Washington, D.C. The model takes a nested logit formulation and includes a binary marginal choice submodel to project travel behavior between aggregate ground and individual air transportation modes, and a trinomial conditional mode choice model to examine the travel behavior patterns within three ground transportation submodes: auto, bus, and rail. The data collected is based upon the base year 2008 market conditions, and the recalibrated model is used to forecast the year 2014 HSR levels of service. Empirical results show that reduced travel cost and other impedance factors stand to increase utility for HSR, even though the auto will continue to be the dominant travel mode.high speed rail, nested logit model, mode choice, Richmond, Washington D.C.