Equity in Accessibility to Opportunities: Insights, Measures, and Solutions based on Mobile Device Location Data

Project Abstract

This report summarizes the study of accessibility to opportunities among different population groups and neighborhoods in Baltimore City. The study is the first of its kind in utilizing observed multimodal mobile device location data from individual devices to systematically study accessibility to opportunities. Passively collected mobile device location data used in this study reveal day-to-day travel patterns of more than 25% of the U.S. population for an entire year across the nation. To showcase the application of this data, we selected the Baltimore city as our testbed. This new data source with very high sampling rates, combined with point of interest data and census data, allows us to analyze how residents in each neighborhood travel to work or seek their essential needs such as food and healthcare. The study introduces a data-driven accessibility measure based on the observed location data, which can also be calculated using individual-level outputs of a typical activity-based model. Research findings directly identify accessibility gaps among neighborhoods. In addition to the above, accessibility and equity measures from mobile device location data are compared with traditional measures, and the comparison results are discussed. Furthermore, this study draws on information from the data-driven method to capture the differences in accessibility among different income groups.

Read the full report here.

Impacts and Outcomes

This report presents the first study that uses mobile device big data to systematically study accessibility with a data-driven approach. As a new data source, mobile device location data offers a novel paradigm for measuring and analyzing accessibility.

Universities and Sponsoring Agencies Involved

University of Maryland

Morgan State University

U.S. Department of Transportation Office of the Secretary-Research

Principal Investigators

Dr. Lei Zhang, University of Maryland, lei@umd.edu

Dr. Hyeon-Shic Shin, Morgan State University, hyeonshic.shin@morgan.edu

Dr. Sepehr Ghader, Project Manager, University of Maryland, sghader@umd.edu

Project Team: Aref Darzi, Guangchen Zhao, Aliakbar Kabiri

Funding Sources and Amounts

USDOT: $135,000; MDOTSHA, $68,622

Completion Date

March 2021

Keywords

Mobile device location data, accessibility data analysis, travel patterns, equity, work trips