A GPS data-based analysis of built environment influences on bicyclist route preferences

TLDR

The study investigates how built‑environment characteristics in Seattle influence bicyclists’ route choices using GPS data. Bicycle routes were extracted from CycleTracks GPS traces, a labeling‑route approach generated the choice set, and two mixed‑logit models with principal‑component‑based cost functions were estimated. Results show that bicyclists jointly weigh convenience, safety, and leisure, favoring shorter, flat, well‑planned routes with low traffic, while some prefer mixed land use, street trees, lighting, or city features.

Abstract

This study examines the effects of built environment features, including factors of land use and road network, on bicyclists' route preferences using the data from the city of Seattle. The bicycle routes are identified using a GPS dataset collected from a smartphone application named “CycleTracks.” The route choice set is generated using the labeling route approach, and the cost functions of route alternatives are based on principal component analyses. Then, two mixed logit models, focusing on random parameters and alternative-specific coefficients, respectively, are estimated to examine bicyclists' route choice. The major findings of this study are as follows: (1) the bicycle route choice involves the joint consideration of convenience, safety, and leisure; (2) most bicyclists prefer to cycle on shorter, flat, and well-planned bicycle facilities with slow road traffic; (3) some bicyclists prefer routes surrounded by mixed land use; (4) some bicyclists favor routes which are planted with street trees or installed with street lights; and (5) some bicyclists prefer routes along with city features. This analysis provides valuable insights into how well-planned land use and road network can facilitate efficient, safe, and enjoyable bicycling.