Chapter 9 - An empirical assessment of the impact of incorporating attitudinal variables on model transferability

Abstract

This chapter focuses on assessing the benefits of incorporating attitudinal and perception variables for the spatial transferability of travel forecasting models. Specifically, this study compares the spatial transferability, in an empirical setting, for three model structures: 1) multinomial logit (MNL), 2) integrated choice and latent variable (ICLV) models and 3) MNL with factor scores. Transferability is assessed by applying the models estimated in one spatial context to another spatial context. The data utilized for assessing the spatial transferability in the three contexts comes from a survey conducted among 1148 respondents across the United States – primarily the Midwest and Southeast. In the survey, respondents were asked about their preferred intended use of autonomous vehicles, along with personal and household characteristics, current travel characteristics, and perceptions about benefits and concerns related to autonomous vehicles. The study found that the ICLV models estimated had similar transferability to fixed coefficient MNL models with no improvement in transferability observed. But it was found that additional information that could lead to improvement of transferability was found when factor scores were directly incorporated into a MNL model. The chapter concludes with a discussion of possible transferability implications for ICLV model use.