Metropolitan Areas In Taiwan Research Articles

Modeling the impact of pre-trip information on commuter departure time and route choice

The objective of this paper is to investigate the impact of pre-trip information on auto commuters’ choice behavior. The analysis is based on an extensive home-interview survey of commuters in the Taichung metropolitan area in Taiwan. A joint model for route and departure time decisions with and without pre-trip information is formulated. The model specifications are developed for both the systematic and random components. In particular, econometric issues associated with specifying the random error structure are addressed for parameter estimation purposes. Insights into the effects of attributes are obtained through the analysis of the model's performance and estimated parameter values. A probit model form is used for the joint model, allowing the introduction of state dependence and correlation in the model specification. The results underscore the important relationship between the different characteristics and the propensity of commuter choice behavior under two scenarios, with and without pre-trip information.

Empirical Results from Taiwan and Their Implications for Advanced Traveler Pretrip Information Systems

A statistical analysis of travelers’ behavior is presented, and a study into the effects of pretrip information on travelers’ choice behavior is addressed. The study is based on an extensive home interview survey conducted in the Taichung metropolitan area of Taiwan. The main objectives were (a) to determine which types of information are more important to travelers; (b) to examine whether the provision of information alters the travelers’ choice behavior; (c) to relate travelers’ choice behavior, including departure time, route, and mode, to personal and travel behavior characteristics; and (d) to provide a basis for the subsequent development of a pretrip information system architecture. A binary logit model of whether a traveler switches departure time, route, mode, or any combinations of the three or does not switch after receiving traffic information is estimated. The results underscore the important relationship between the different characteristics and the propensity of travelers to change behavior. Separate binary models are developed for each of the individual trip purposes. The focus is on the urban (intraregional) trips.