2019 Volume 13 Pages 643-663
An activity-based model system is presented for the Tokyo Metropolitan Area, where the railway network has over 30 million passengers per day. The model system represents a rail passenger’s choices of activity pattern, time-of-day, and destination in response to a change in railway services. The activity-based model is designed for analysis of a change in activities after a traveler leaves the office. The paper describes the creation of the destination choice model in detail. The model system divides the Tokyo Metropolitan Area into 692 traffic analysis zones. Stratified importance sampling and a time–space constraint are adopted for the choice set formulation to predict traveler destinations. The paper discusses the requirement to introduce variables related to the origin zones of different travelers into the destination choice model to improve the predictive accuracy.