Metropolis-Hasting based Expanded Path Size Logit model for cyclists’ route choice using GPS data

Abstract

Abstract This study contributes to the field of cycling route choice by adopting the unprecedented combination of the Metropolis-Hastings (MH) path-sampling algorithm and the Expanded Path Size Logit (EPSL) model. The MH sampling approach is used to generate 15 alternative route choice sets for cyclists. The EPSL multivariate route choice framework is utilized to account for the correlation between sampled and non-sampled alternatives (joint MH-EPSL model). The data used in this paper is drawn from GPS data collected by the City of Toronto using a custom-built smartphone application in 2014–2015. The study focuses on non-work-related cycling trips (shopping, leisure, social and others) in downtown Toronto on weekdays. The estimated results indicate that the presence of bicycle lanes and road medians attractions and number of trees along the path have a positive impact on cyclist route choice. In general, cyclists prefer to take shorter routes on lower speed roads with less public transit stops especially during the evening rush hour, and less willing to take one-way streets, local roads, and steep road segments. These findings are useful to policy makers as well as transportation and urban designers when developing a cycling network aiming to attract more cyclists. Finally, our results indicate that the MH-EPSL model performance is an appropriate framework to study cyclists’ route choice decisions.