Understanding and modeling route choice decisions

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Although travel behavior research in general has advanced considerably over the past decade, spearheaded by new data collection technologies and new modeling methods, one area that has seen less work is that pertaining to route choice. In part, this stems from a lack of data pertaining to observed routes - data that can now be collected via GPS technology. At the same time, in an era characterized by rising oil prices, energy conservation, traffic congestion, aging populations and climate change, there is a growing need to improve our understanding of the spatial manifestation of activity/travel behavior - that is, navigating urban transportation networks. Since travel demand forecasting is done using some form of traffic assignment algorithm, the research proposed can reveal whether the assumptions underlying such algorithms are valid. If not, then one must question the validity of predictions from such models - predictions that are used to guide development in urban areas. In other words, how can a transportation planner enhance quality of life when the model outputs are simply inaccurate?