BAYESIAN UPDATING OF TRIP GENERATION DATA - COMBINING NATIONAL TRIP GENERATION RATES WITH LOCAL DATA

With traffic impact analyses and impact fee assessment becoming more p opular, the need for accurately estimating the trip generation rate of a proposed development is becoming more important. An overwhelming pe rcentage of state transportation agencies depend either partly or enti rely on the ITE Trip Generation Report to predict the traffic that wil l be attracted to and/or produced from a proposed development. However , the rates obtained from the ITE publication have been derived from d ata collected throughout the United States. They represent a national average and fail to take into account the local trip generation charac teristics that the site under consideration might have. This paper est ablishes a methodology for obtaining more reliable local trip generati on rates using Bayesian statistics. In this method, the ITE rates are assumed to be the prior information, which are updated using limited l ocal trip generation data that are available. The method also allows f or temporal updating, incorporating subjective judgment and using ''bo rrowed'' data in the updating procedure. Sample calculations in this p aper illustrate the developed methodology.