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

Project Abstract

This research project will study the accessibility to basic lifeline opportunities such as jobs, healthy food, and healthcare, among different population groups and neighborhoods in the Baltimore and Washington D.C. region, with a focus on disadvantaged population groups and underserved communities. The proposed study is the first of its kind in utilizing observed multimodal travel big data from individual mobile devices to systematically study accessibility for underserved population groups. Passively collected mobile device location data, already procured through a federally funded research project at UMD, reveals day-to-day travel patterns of more than 40% of the entire population in the entire nation including the Baltimore and Washington D.C. region for an entire year. This new data source with very high sampling rates, combined with point of interest data and census data, allows the UMD-Morgan project team to analyze how residents in each socio-demographic group and in each neighborhood actually travel to work, purchase food, and seek health care services. Research findings will directly identify accessibility gaps among various population groups and neighborhoods, and more importantly, identify feasible solutions to improve accessibility for disadvantaged population group and underserved communities. Accessibility and equity measured from mobile device big data will be compared with traditional measures. In addition, accessibility patterns and trends in Baltimore and Washington D.C. will be compared based on big data observations. The product of this research project will be an interactive data analytics and mapping toolbox that can be used to query these data-driven accessibility measures for improved understanding and decision-making. State and local governments, as well as non-profit organizations, have already showed strong support for this proposed research (see support letters from MDOT State Highway Administration, City of Baltimore, Baltimore Food Policy Initiative, and Health Care for the Homeless). MDOT SHA has also committed $100,000 in cash cost share in their support letter.

Universities and Sponsoring Organizations Involved

University of Maryland College Park
Morgan State University
Maryland Department of Transportation State Highway Administration (MDOT SHA)

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

Principal Investigator(s)

Dr. Lei Zhang (University of Maryland), lei@umd.edu; Dr. Hyeon-Shic Shin, Morgan State University

Funding Sources and Amounts

USDOT: $100,000 (Federal), University 1: $80,000 (Match), University 2: $10,000 (Match)
UMEC: $135,000
MDOT SHA: $68,622 (Cost Share)

Start Date

8/1/2019 (Expected)

Expected Completion Date


Expected Research Outcomes

Data-driven accessibility measures obtained from location data

Identifying gaps in accessibility to jobs, healthy food, and health care among different income groups and residential communities
Quantifying the accessibility gaps for low-income and underserved communities
Identifying causes of accessibility gaps based on the big data approach and propose mobility solutions that meet actual needs based on observed data
An interactive data analytics/query tool

Expected Equity Impacts and Benefits of Implementation

Accessibility measures derived directly from mobile device location data provides a new paradigm for quantifying accessibility. Products from the research project can be used to identify the distribution of accessibility by socio-demographic groups, by neighborhoods, and by travel modes. These distributions can highlight the population groups that are in need of improved transportation services to access jobs, healthy food, and health care. Decision-makers can use project products to more effectively invest limited resources to improve access to opportunities in underserved communities. Since mobile device location data are already available for the entire U.S. and in many other nations, our research methods and the proposed accessibility analysis can be readily expanded to other regions in the U.S. and internationally.

Subject Areas

Mobile device location data
Accessibility to opportunities
Under-served population
Accessibility equity
Multi-modal accessibility