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Nested logit models of mode and walk route choice behavior in a downtown area are developed. The models sample alternatives at the route choice level, which is a lower level of the nesting structure. Alternative routes are drawn using the random walk method, and the expanded logsum is used for the mode choice in the upper level. A structured random walk parameter based on trip distance is proposed in order to consider the heterogeneity in trip distance, and a structured scale parameter based on trip distance is also applied for the nested logit model. Dataset is obtained by using mobile phones with global positioning system (GPS) functions to track the trajectories in a downtown area at Nagoya, Japan. The results suggest that a structured random walk parameter based on trip distance provides better parameter estimates when the empirical data contains trips of various distances. Also, heteroscedasticity in the error terms for trips of various distances is found to be significant. Empirical findings include that older pedestrians prefer main shopping streets, and that roadside restaurants affect the route choice differently on weekdays and holidays.
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