Learning Mobility Insecurity from Location Intelligence Data

Center for Connected and Automated Transportation/Research/Research from Northwestern University/Learning Mobility Insecurity from Location Intelligence Data

Learning Mobility Insecurity from Location Intelligence Data

In Progress
Headshot of Marco Nie. The link directs to their profile page.
Marco Nie
Headshot of Ying Chen. The link directs to their profile page.
Ying Chen
Headshot of Alexandra Murphy. The link directs to their profile page.
Alexandra K. Murphy
Northwestern University Logo. The link directs to the funded research led by this institution.
The University of Michigan Logo. The link directs to the funded research led by this institution.

Principal Investigator(s):

Marco Nie, Professor of Civil and Environmental Engineering – Northwestern University
Ying Chen, Assistant Professor of Civil and Environmental Engineering – Northwestern University
Alexandra K. Murphy, Assistant Professor of Sociology – The University of Michigan

Project Abstract:
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. Our method leverages the burgeoning availability of location intelligence data, combined with our team’s expertise in utilizing such data. By analyzing the rich mobility patterns embedded in location intelligence data, we plan to learn about mobility irregularity (MI), broadly defined by the variations in spatial and temporal patterns of trip making. Central to our 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. We hypothesize 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.

Institution(s): Northwestern University
University of Michigan – Ann Arbor

Award Year: 2024

Research Focus: Equity

Project Form(s):

Project Information Form
Data Management Plan