Modeling the influence of structural lifecycle events on activity-travel decisions using a structure learning algorithm

This paper describes the results of a study on the impact of lifecycle events on activity-travel choice decisions of individuals. An Internet-based survey was designed to collect data concerning structural lifecycle events. In addition, respondents answered questions about personal and household characteristics, possession and availability of transport modes and their current travel behavior. In total, 710 respondents completed the online survey. The complexity of transport mode choice is modeled using a Bayesian Belief Network. Previous papers describe the conceptual framework underlying the model and the temporal effects of lifecycle events on mode choice. This paper focuses on influences of structural life trajectory events on each other and on changes in resources that impact activity-travel decisions. We investigate the extent to which causal relations exist between these events and their direct and indirect effects on changes in transport mode availability and the possession of transit passes. A structure learning algorithm is used to build a Bayesian Belief Network of interdependencies between these events from the data