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Incorporating features of autonomous vehicles in activity-based travel demand model for Columbus, OH

Author

Listed:
  • Gaurav Vyas

    (INRO)

  • Pooneh Famili

    (WSP USA Inc.)

  • Peter Vovsha

    (INRO)

  • Daniel Fay

    (WSP USA Inc.)

  • Ashish Kulshrestha

    (WSP USA Inc.)

  • Greg Giaimo

    (Ohio Department of Transportation)

  • Rebekah Anderson

    (Ohio Department of Transportation)

Abstract

Autonomous vehicles (AVs) could change travel patterns of the population significantly and with the rapid improvements in AV technology, transportation planners should address AV impacts in regional plans and project evaluations for the mid-term and long-term horizons (10–15 years and beyond). There are multiple travel model components from demand generation to network assignments that need to be modified, updated, or added to fully capture the potential impacts of AVs on regional travel patterns. This paper describes how the features of AVs were incorporated in the regional Activity-Based travel demand Model developed for Columbus, OH, metropolitan region. The model modifications included multiple adjustments to the travel demand sub-models, network assignments, as well as an addition of a new sub-model for vehicle routing and parking that addresses such new phenomenon as empty AV relocation trips. Due to many factors of uncertainty associated with AVs, a scenario-based approach was adopted for evaluation of the potential impacts of AVs on the travel patterns. The emphasis of the scenario analysis was on multiple dimensions of travel behavior in addition to such aggregate regional measures as VMT, etc. The paper presents an analysis of potential impacts of AVs on accessibility measures, activity participation, tour formation, and mode choice. The scenario analysis applied to the Columbus region showed overall logical potential impacts of AVs with many insights useful for transportation planning.

Suggested Citation

  • Gaurav Vyas & Pooneh Famili & Peter Vovsha & Daniel Fay & Ashish Kulshrestha & Greg Giaimo & Rebekah Anderson, 2019. "Incorporating features of autonomous vehicles in activity-based travel demand model for Columbus, OH," Transportation, Springer, vol. 46(6), pages 2081-2102, December.
    • Handle: RePEc:kap:transp:v:46:y:2019:i:6:d:10.1007_s11116-019-10030-w
    DOI: 10.1007/s11116-019-10030-w
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    References listed on IDEAS

    as
    1. Rajesh Paleti & Peter Vovsha & Gaurav Vyas & Rebekah Anderson & Gregory Giaimo, 2017. "Activity sequencing, location, and formation of individual non-mandatory tours: application to the activity-based models for Columbus, Cincinnati, and Cleveland, OH," Transportation, Springer, vol. 44(3), pages 615-640, May.
    2. Long T. Truong & Chris Gruyter & Graham Currie & Alexa Delbosc, 2017. "Estimating the trip generation impacts of autonomous vehicles on car travel in Victoria, Australia," Transportation, Springer, vol. 44(6), pages 1279-1292, November.
    3. Saptarshi Das & Ashok Sekar & Roger Chen & Hyung Chul Kim & Timothy J. Wallington & Eric Williams, 2017. "Impacts of Autonomous Vehicles on Consumers Time-Use Patterns," Challenges, MDPI, vol. 8(2), pages 1-15, December.
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    Cited by:

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    2. Angelidou, M. & Politis, C. & Panori, A. & Bakratsas, T. & Fellnhofer, K., 2022. "Emerging smart city, transport and energy trends in urban settings: Results of a pan-European foresight exercise with 120 experts," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    3. Alberto Dianin & Elisa Ravazzoli & Georg Hauger, 2021. "Implications of Autonomous Vehicles for Accessibility and Transport Equity: A Framework Based on Literature," Sustainability, MDPI, vol. 13(8), pages 1-17, April.
    4. Choi, Sungtaek & Mokhtarian, Patricia L., 2020. "How attractive is it to use the internet while commuting? A work-attitude-based segmentation of Northern California commuters," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 37-50.
    5. Ahmed, Tanjeeb & Hyland, Michael & Sarma, Navjyoth J.S. & Mitra, Suman & Ghaffar, Arash, 2020. "Quantifying the employment accessibility benefits of shared automated vehicle mobility services: Consumer welfare approach using logsums," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 221-247.

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