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Using Multi-Modal Path-Specific Transit Trips in Transportation Social Sustainability Analysis: Case Study in Atlanta, GA

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Listed:
  • Fan, Huiying
  • Lu, Hongyu
  • Guin, Angshuman
  • Guensler, Randall

Abstract

A previous National Center for Sustainable Transportation (NCST) study examined pandemic-related changes in MARTA transit system service and ridership in Atlanta, GA, and the combined effects on energy use and per-passenger energy use (Fan, et al., 2022). For that previous study, General Transit Feed Specification (GTFS) and the Automated Passenger Counter (APC) datasets were used to develop the transit network and derive distance and passenger load information within the TransitSim analytical framework. The research coupled ridership data with energy use and emission rates from MOVES-Matrix to assess how the changes in transit service and ridership affected energy use and emissions on a per passenger-mile basis. Research performed in this supplemental NCST study improved model algorithms to increase analytical efficiency and to integrate ridership demographics, so that energy use impacts could be assessed across demographic groups for use in social sustainability analysis. This report summarizes improvements that generated TransitSim 3.0 and provides a social sustainability modeling demonstration. View the NCST Project Webpage

Suggested Citation

  • Fan, Huiying & Lu, Hongyu & Guin, Angshuman & Guensler, Randall, 2024. "Using Multi-Modal Path-Specific Transit Trips in Transportation Social Sustainability Analysis: Case Study in Atlanta, GA," Institute of Transportation Studies, Working Paper Series qt3171b0j4, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt3171b0j4
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    References listed on IDEAS

    as
    1. Fan, Huiying & Lu, Hongyu & Guin, Angshuman & Watkins, Kari E & Guensler, Randall, 2022. "Combined Effect of Changes in Transit Service and Changes in Occupancy on Per-Passenger Energy Consumption," Institute of Transportation Studies, Working Paper Series qt2x1320p5, Institute of Transportation Studies, UC Davis.
    2. Luyu Liu & Harvey J Miller & Jonathan Scheff, 2020. "The impacts of COVID-19 pandemic on public transit demand in the United States," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-22, November.
    3. Welch, Timothy F. & Mishra, Sabyasachee, 2013. "A measure of equity for public transit connectivity," Journal of Transport Geography, Elsevier, vol. 33(C), pages 29-41.
    4. Jomehpour Chahar Aman, Javad & Smith-Colin, Janille, 2020. "Transit Deserts: Equity analysis of public transit accessibility," Journal of Transport Geography, Elsevier, vol. 89(C).
    5. Wei, Ran & Liu, Xiaoyue & Mu, Yongjian & Wang, Liming & Golub, Aaron & Farber, Steven, 2017. "Evaluating public transit services for operational efficiency and access equity," Journal of Transport Geography, Elsevier, vol. 65(C), pages 70-79.
    6. Xu, Xiaodan & Liu, Haobing & Passmore, Reid & Patrick, Tyler & Gbologah, Franklin & Rodgers, Michael O. & Guensler, Randall, 2018. "Fuel and Emissions Calculator (FEC), Version 3.0, Summary Report," Institute of Transportation Studies, Working Paper Series qt59z12905, Institute of Transportation Studies, UC Davis.
    7. Taylor, Brian D & Garrett, Mark, 1999. "Reconsidering Social Equity in Public Transit," University of California Transportation Center, Working Papers qt2bm7b38n, University of California Transportation Center.
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    More about this item

    Keywords

    Engineering; Social and Behavioral Sciences; Algorithms; Demographics; Energy consumption; Public transit; Ridership; Sustainable transportation;
    All these keywords.

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