行人
情感(语言学)
大数据
运输工程
区域科学
心理学
地理
计算机科学
工程类
数据挖掘
沟通
作者
Rounaq Basu,Andres Sevtsuk
标识
DOI:10.1016/j.tra.2022.06.007
摘要
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.
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