Travel demand models in the developing world: correcting for measurement errors

Abstract

While transport modelers in developed countries are accustomed to working with relatively rich datasets including transport networks and land use data, such databases are rarely available in developing countries. However, developing countries such as China with its immense rate of economic growth are, arguably, most in need of demand models. The research addressed in this paper is how to develop mode choice models for planning and policy analysis when level of service data are not available and resources are limited. The research makes use of a 1,001 household travel and activity survey from Chengdu collected in 2005. Chengdu has an urban population of over 3 million and a GDP growth rate of over 20% per year. By coding transportation networks, course estimates of level of service by mode are first developed. As these measures are assumed to have accuracy issues, particularly for transit, level of service is treated as a latent (i.e., unobservable) variable. Measurement equations (from the structural equation model paradigm) are used to infer latent level of service, and these equations are integrated with the mode choice model. Our initial results indicate that models that do not correct for measurement error may underestimate travelers' values of time. The methodological approach employed has potential for improving models estimated with higher quality network data (for example in the developed world), because it can correct for measurement error that exists, for example, in network-derived level of service variables.

Keywords:

• Travel Demand Modeling
• China
• Choice and Latent Variable Models
• Measurement Error
• Mode Choice