Prediction of the Deviation between Alternative Routes and Actual Trajectories for Bicyclists

This study estimates a panel regression model to predict bicyclist route choice. Using GPS trajectories of 600 trips from 49 participants in spring 2006 Minneapolis, we calculate deviation, the average distance between alternative routes and actual trajectories, as dependent variable. Trip attributes, including trip length, Vehicle Kilometres Travelled (VKT), number traffic lights per kilometer, percentage bike trails separated lane, are included independent variables. F-tests indicate that both fixed entity time effect models offer better fits than intercept-only model. According our results, with shorter length higher share tend have less deviation their trajectories. Traffic km, VKT, lane not significant at 95% confidence level this data set.