How to Model the Influence of In-vehicle Crowding on Travel Behavior: A Comparison Among Moderation, Independent Variable and Interaction

Abstract

Accurate modeling of travel choice behavior is crucial for effective transport demand forecasting, management and planning. This study tries to shed light on the appropriate modeling approach concerning the influences of in-vehicle crowding on mode choice behavior in the multimodal network. Stated preference surveys covering four commuting transport modes and four influencing factors are conducted to collect empirical behavior data. Three modeling methods, treating the in-vehicle crowding as a moderator of perceived travel time, as an independent variable and by incorporating interaction effect, are empirically compared. The result indicates that there is a bidirectional interaction between travel time and in-vehicle crowding. The influence of in-vehicle crowding increases with increasing travel time and vice versa. Considering crowding as an independent variable and taking the effects of travel time on the perception of in-vehicle crowding are the best ways to depict the overall influences of in-vehicle crowding. The sensitivity analysis shows that increasing the cost of using car is comparatively effective for reducing car usage. Shortening the travel time of public transit and improving service quality such as travel time reliability and in-vehicle crowding are more useful in attracting car users as compared to reduction in the cost of public transit. The results provide insights into travelers’ behavior in the multimodal network and could support scientific transport management and planning.