Most recent route choice models, following either the random utility maximizationor rule-based paradigm, require explicit enumeration of feasible routes. The quality ofmodel estimation and prediction is sensitive to the appropriateness of the considerationset. However, few empirical studies of revealed route characteristics have been reportedin the literature. This study evaluates widely applied shortest path assumption byevaluating morning commute routes followed by residents of the Minneapolis - St. Paulmetropolitan area. Accurate GPS and GIS data were employed to reveal routes peopleused over an eight to thirteen week period. Most people do not choose the shortestpath. Using three weeks of that data, we nd that current route choice set generationalgorithms do not reveal the majority of paths that individuals took. Findings from thisstudy may provide guidance for future eorts in building better route choice models.
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