Citation

Basu R, Sevtsuk A. Transp. Res. A Policy Pract. 2022; 163: 1-19.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.tra.2022.06.007

PMID

unavailable

Abstract

This study adds to the nascent but growing literature on the use of big data for pedestrian route choice analysis. We explore behavioral preferences for various route attributes in Boston, MA using a large dataset of GPS trajectories (n = 11,165) sourced from a third-party smartphone app. Although the data are anonymized and limit our exploration of user heterogeneity, the sample size and area coverage are both much larger than seen in most previous studies. We estimate route choice preferences using a path size logit model, and operationalize the coefficients for policy-making through 'willingness-to-walk' measures. The value of these measures is demonstrated through an application of computing pedestrian accessibility to transit stations. Additionally, we compare our findings to a previous study in San Francisco, CA using similar data and methods, and previous literature to explore similarities and differences in pedestrian route choice behavior across major metropolitan areas more generally. While our findings can inform walkability policy and practice on several counts, we recommend future efforts to focus on supplementing this study by surveying hard-to-reach populations for more equitable policy-making.

Language: en

Keywords

Discrete choice model; GPS trajectories; Pedestrian route choice; Sustainable mobility; Travel behavior; Walkability