Investigating dual-directional collective human mobility patterns of place-level incoming and outgoing travel behaviors using big data

Abstract

Collective human mobility is an important phenomenon within defined geographic areas for specific mobility patterns. Studies have been conducted to understand human mobility patterns and the determinants, including the built environment, and socioeconomic factors. However, there is a dearth of systematic investigation focusing on the dual-directional nature of collective human mobility in places, referring to both incoming and outgoing mobility behaviors. This study addresses this gap by analyzing mobility density, dwell time, and trip distance of both incoming and outgoing travel behaviors using mobile phone big data in 165,181 census block groups in U.S. cities in 2019. As the results show, built environment features usually demonstrate greater explanatory power than socioeconomic variables, highlighting their vital roles in shaping human mobility. Specifically, built environment characteristics, including developed open space, population density, employment diversity, street intersections, walkability, transit service, and destination accessibility, are noticeably associated with collective mobility patterns in terms of incoming and outgoing density, dwell time, and distance. Socioeconomic variables, such as the proportion of older adults, Black individuals, household income, commuting mode choices are also significantly linked to specific mobility patterns. We also suggest policy implications for built environment interventions to support sustainable place-level human mobility.