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Evaluating Carpool Potential for Home-to-Work SOV Commuters Using a Scalable and Practical Simulation Framework

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  • Liu, Diyi
  • Fan, Huiying
  • Guin, Angshuman
  • Guensler, Randall

Abstract

Given that morning peak period vehicle occupancy rates are generally 1.1 to 1.2 persons per vehicle in urban areas, transportation planners have long argued that effective carpooling strategies could significantly reduce traffic congestion and the carbon footprint of commuters. Community-based carpooling, which is designed to match drivers and passengers that reside within subregions and that are traveling to similar destination zones, can be exploited once technology, communication, demographic, and economic barriers are overcome. While community-based carpool has the potential to provide sustainability benefits, integration into transportation plans and models is not prevalent, due to the lack of appropriate analytical tools. CarpoolSim is a new scalable analytical framework designed evaluate the potential performance and impact of intelligent carpooling system (ICS) for regional networks. Designed to be directly integrated into the travel demand modeling process, CarpoolSim uses a two-stage approach: 1) a filtering step with a set of comprehensive filtering conditions, to eliminate unreasonable carpool matches, given spatiotemporal constraints; and 2) an optimization step, to match as many carpools as possible (and eliminate any remaining assignment conflicts). Experiments using trip-level outputs from the Atlanta Regional Commission’s activity-based travel demand model (ABM) show that, under conservative carpool matching constraints, about 24.1% of candidate single occupancy home-to-work commute trips to major employment centers along the I-85 corridor in Atlanta, GA could be carpooled by direct carpool. More than 19.2% of the same candidate commute trips could be carpooled via park-and-ride. Sensitivity analyses were applied. Among all of the control parameters, the minimum ratio between shared trip and individual trips travel time has the greatest impact on results. Although only 26,029 trips are selected for carpool matching (less than 0.5% of total daily trips originating near I-85), the experiments show that the potential for intelligent carpooling systems to manage commute trips to major employment center is reasonable, considering the spatiotemporal travel constraints of these travelers. View the NCST Project Webpage

Suggested Citation

  • Liu, Diyi & Fan, Huiying & Guin, Angshuman & Guensler, Randall, 2024. "Evaluating Carpool Potential for Home-to-Work SOV Commuters Using a Scalable and Practical Simulation Framework," Institute of Transportation Studies, Working Paper Series qt0gt458qt, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt0gt458qt
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    References listed on IDEAS

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    1. Meyer, Michael D., 1999. "Demand management as an element of transportation policy: using carrots and sticks to influence travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(7-8), pages 575-599.
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    Keywords

    Engineering; Social and Behavioral Sciences; Carpools; Commuters; Optimization; Simulation; Spatial analysis; Travel demand;
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