Structured random walk parameter for heterogeneity in trip distance on modeling pedestrian route choice behavior at downtown area

A nested logit model of mode and walk route choice behavior in a downtown area is developed. The model samples alternatives at the route choice level, which is a lower level of the nesting structure. Alternative routes are drawn using the random walk method. 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 GPS functions to track the trajectories in a downtown area at Nagoya, Japan. The results suggest that the proposed structured random walk parameter provides more efficient parameter estimates. 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. The different effects of the roadside environments according to the pedestrian's attributes and the day of the week may indicate a need for more appropriate policies for specific pedestrian categories and days of the week.