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Journal of Science Policy & Governance | Volume 18, Issue 01 | March 24, 2021

Policy Analysis: Improving Bus Route Design Using Stop Balancing and Community-level Data

Justin McKetney (1)*, Edna A. Trujillo (2)*, Megan Tabbutt (3,4), Brittany Baur (5)
  1. Department of Biomolecular Chemistry, University of Wisconsin - Madison, Madison, WI
  2. Department of Chemistry, University of Wisconsin - Madison, Madison, WI
  3. Department of Physics, University of Wisconsin - Madison, Madison, WI
  4. Department of Computer Science, University of Wisconsin - Madison, Madison, WI
  5. Wisconsin Institute for Discovery, University of Wisconsin - Madison, Madison, WI

*Authors contributed equally

Corresponding author: mcketney@wisc.edu
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https://doi.org/10.38126/JSPG180109
Keywords: public transportation; transit policy; equitable transit; route design; bus stop balancing; transit efficiency; data-driven transit
Executive Summary: Public transportation brings numerous benefits to communities when it provides people with mobility and access to opportunities. A well-designed and widely utilized system is required for regions to gain access to these benefits. Transit policies must be efficient, relevant to their specific region, and take into consideration how residents utilize public transit. In this paper, we focus on the implications of bus stop balancing and route schedule design for the Madison Metropolitan Transit in Madison, Wisconsin. We discuss where populations live and work to illustrate potential servicing barriers that limit access to employment centers. We recommend adopting standardized spacing between stops of 1000-2500 feet to increase transit speed and reliability with a particular focus on areas with low car ownership. Finally, we spotlight how transit services can be expanded to include non-traditional commuters. The adoption of these suggested improvements will lead to faster transit times with improved reliability and more equitable service within the Greater Madison Area.

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Justin McKetney is a PhD Student in the Integrated Program in Biochemistry at the University of Wisconsin-Madison, where his research focuses on developing and utilizing mass spectrometry-based proteomic tools to investigate human health. He has specifically focused on increasing understanding of molecular protein signatures for aging, stress, and Alzheimer’s disease. Justin received his BS in Cell and Molecular Biology from San Diego State University.
 
Edna Angelica Trujillo is a Ph.D. student in Chemical Biology (Chemistry Department) at the University of Wisconsin-Madison where she studies the application and technology of mass spectrometry in the field of Bio-Analytical Chemistry. She has a Ph.D. minor in Life Science Communication and utilizes her training to create science curriculum for non-expert audiences at the Wisconsin Science Festival and Madison elementary schools. She is passionate about making science more accessible and mentoring young adults on how to apply to college and the first-generation college experience. A new member of the Catalysts for Science Policy, she has pioneered in leveraging big data for designing inclusive science policy. Edna is a first generation Latinx college student and received her AS in Chemistry from Santa Barbara Community College and then transferred to Humboldt State University where she received her BS in Chemistry.
 
Megan Tabbutt is a Ph.D. student in Physics at the University of Wisconsin-Madison where she studies Cosmology, specifically large-scale structure, using optical imaging surveys. She is a member of the Dark Energy Survey (DES) and the Rubin Observatory Legacy Survey of Space and Time (LSST). In addition, she is applying for the M.S. program in Computer Science to be completed along with her Ph.D. She is a National Defense Science and Engineering Graduate Fellow and a member of the Catalysts for Science Policy. She is passionate about civil hacking using data analysis and enjoys spending free time on such projects. She received her B.S. in Physics, Astrophysics and Math from the University of Wisconsin - Madison.
 
Brittany Baur is a Postdoctoral Researcher at the Wisconsin Institute for Discovery at the University of Wisconsin-Madison. She holds a Ph.D. in Computational Sciences and a M.S. in Bioinformatics from Marquette University. She studies the role of the 3-dimensional structure of the genome in gene regulation and disease. She is an active member of Catalysts for Science Policy and is passionate about effective science communication and leveraging data science to inform policy decisions.
 
Acknowledgements
The authors would like to thank the City of Madison for the creation and maintenance of the City of Madison Open Data Portal, from which much of the data here is derived. We thank Catalysts for Science Policy (CaSP) and its members for both inspiring an interest in science policy and providing a forum for development of many of the ideas included in this manuscript. Specifically, we would like to thank Evan Linck, Tyler Peterson, and Maia Gumnit for helping to sustain the project in its early conception. We would also like to thank Dr. Tyler Caraza-Harter who provided feedback and guidance throughout the development process.
DISCLAIMER: The findings and conclusions published herein are solely attributed to the author and not necessarily endorsed or adopted by the Journal of Science Policy and Governance. Articles are distributed in compliance with copyright and trademark agreements.

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