by Liming Wang, Paul Waddell, and Maren L. Outwater
Recent advances in activity-based travel modeling and integrated land use and transportation modeling have significantly advanced the understanding of and the capacity to model location choices and travel behavior more realistically. These advances, however, come with greater data requirements, and the risk and the substantial cost involved with adoption of these models have slowed their move to operational use. The purpose of this research was twofold. First, the study addressed one aspect of an incremental approach that more carefully balanced the risks and benefits of moving operational models in new directions: replacement of the choice model of home-based work destination in the four-step travel model system with a pair of choice models at the level of the individual worker. The new choice models were implemented as long-term choices in the linked land use model system. Second, the models were used to provide a way to derive matches between workers and their workplace with commonly available data. These matches complemented synthetic populations and provided a key input for activity-based travel models. The models predicted whether a worker would choose to work at home on a long-term basis; if he or she did not, an out-of-home job was chosen. These models linked an individual worker to a specific job at a workplace and therefore directly predicted commuting patterns. The paper presents the model specifications, estimation results, and results of validation of the models against observed commuting data from the Census Transportation Planning Package. The model reproduced observed commuting flows well, and computational performance was fast, even though the model operated at the level of the individual worker and job.
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