Spatially-oriented data, methods, and models to plan transit for reverse commuters

Authors

Joshua H. Davidson
Ilil Feiglin
Megan S. Ryerson

Document Type

Journal Article

Publication Date

2021

Subject Area

ridership - commuting, ridership - demand, place - north america, planning - methods

Keywords

reverse commuting, transit planning, demand

Abstract

The reverse commuting population, those who travel from residences in the city to workplaces in the suburbs, are largely underserved by existing transit systems. One contributing factor to this limited service are issues in existing transit planning methods; serving the reverse commute with transit requires new methods and data sources that complement decision making based on ridership and revealed demand. We utilize administrative origin–destination data from the Philadelphia area that measures commuter flows across all travel modes, rather than just those who already use transit, to capture the potential demand for reverse commuting transit service. We develop an index to highlight target areas for new services, describe geographies for intervention, and utilize negative binomial regression models to analyze key covariates of the reverse commute. Our approach advances a new methodological framework that employs spatially-oriented analyses and open data and tools to generate actionable insights to better serve reverse commuters.

Rights

Permission to publish the abstract has been given by Elsevier, copyright remains with them.

Comments

Transportation Research Part D Home Page:

http://www.sciencedirect.com/science/journal/13619209

Recommended Citation

Davidson, J.H., Feiglin, I., & Ryerson, M.S. (2021). Spatially-oriented data, methods, and models to plan transit for reverse commuters. Transportation Research Part D: Transport and Environment, Vol. 100, 103051.