Learning Mobility Insecurity from Location Intelligence Data
This project aims to overcome the limitations of existing tools in measuring transportation insecurity (TI) by developing a novel, learning-based method to capture a critical aspect of TI: travel irregularity. The method leverages the burgeoning availability of location intelligence data, combined with the team’s expertise in utilizing such data. By analyzing the rich mobility patterns embedded in location intelligence data, the research team plans to learn about mobility irregularity (MI), broadly defined by the variations in spatial and temporal patterns of trip making. Central to this approach is the creation of the Mobility Regularity Index (MRI), a comprehensive metric quantifying such variations. The MRI will consider diverse trip characteristics such as frequency, purpose, duration, length, mode, and destination. The team hypothesizes a strong correlation between MI and TI, positing that MI could serve as a predictive indicator for TI. This research represents a significant step towards a more nuanced understanding and measurement of transportation insecurity, moving beyond the limitations of current data and tools.
Language
- English
Project
- Status: Active
- Funding: $265514
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Contract Numbers:
69A3552348305
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
University of Michigan Transportation Research Institute
2901 Baxter Road
Ann Arbor, Michigan United States 48109 -
Project Managers:
Stearns, Amy
Bezzina, Debra
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Performing Organizations:
Northwestern University, Evanston
Transportation Center, Department of Civil and Environmental Engineering
2145 Sheridan Road, A335
Evanston, IL United States 60208University of Michigan Institute for Social Research
P.O. Box 1248
426 Thompson St.
Ann Arbor, MI United States 48109-1248 -
Principal Investigators:
Nie, Yu
- Start Date: 20240701
- Expected Completion Date: 20250630
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers
Subject/Index Terms
- TRT Terms: Equity; Location data; Machine learning; Mobility; Transportation disadvantaged persons; Travel behavior
- Subject Areas: Planning and Forecasting; Society; Transportation (General);
Filing Info
- Accession Number: 01929641
- Record Type: Research project
- Source Agency: Center for Connected and Automated Transportation
- Contract Numbers: 69A3552348305
- Files: UTC, RIP
- Created Date: Sep 5 2024 11:06AM