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Fully autonomous vehicles: analyzing transportation network performance and operating scenarios in the Greater Toronto Area, Canada

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  • Bradley Kloostra
  • Matthew J. Roorda

Abstract

Fully autonomous vehicles (AVs) have the potential to considerably change urban mobility in the future. This study simulates potential AV operating scenarios in the Greater Toronto Area (GTA), Canada, and assesses transportation system performance on a regional level. For each scenario, the base capacities of certain types of road links are modified to simulate the theoretical increase in throughput enabled by AV driving behavior. Another scenario examines driverless parking operations in downtown Toronto. Simulation results indicate that the increased attractiveness of freeways relative to other routes leads to slightly increased average travel distance as vehicles divert to access higher capacity road links. Average travel time is found to decrease by up to one-fifth at the 90% AV market penetration level. Concurrently, localized increases in congestion suggest that proactive transportation planning will be needed to mitigate negative consequences of AV adoption, especially in relation to induced demand for personal automobile travel.

Suggested Citation

  • Bradley Kloostra & Matthew J. Roorda, 2019. "Fully autonomous vehicles: analyzing transportation network performance and operating scenarios in the Greater Toronto Area, Canada," Transportation Planning and Technology, Taylor & Francis Journals, vol. 42(2), pages 99-112, February.
    • Handle: RePEc:taf:transp:v:42:y:2019:i:2:p:99-112
    DOI: 10.1080/03081060.2019.1565159
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    Cited by:

    1. Jonghan Park & Seunghwa Jang & Joonho Ko, 2023. "Effects of Exclusive Lanes for Autonomous Vehicles on Urban Expressways under Mixed Traffic of Autonomous and Human-Driven Vehicles," Sustainability, MDPI, vol. 16(1), pages 1-14, December.
    2. Umberto Crisalli & Andrea Gemma & Marco Petrelli, 2023. "Investigating the Effects of Automated Vehicles on Large Urban Road Networks: Some Evidence from Rome," Sustainability, MDPI, vol. 15(13), pages 1-10, July.
    3. Lavoie, Brenden & Ong, Felita & Habib, Khandker Nurul, 2024. "Relax on the way to work or work on the way to relax? Influences of vehicle interior on travel time perceptions in autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 183(C).
    4. Baichuan Mo & Zhejing Cao & Hongmou Zhang & Yu Shen & Jinhua Zhao, 2020. "Competition between shared autonomous vehicles and public transit: A case study in Singapore," Papers 2001.03197, arXiv.org, revised Feb 2021.
    5. Nadafianshahamabadi, Razieh & Tayarani, Mohammad & Rowangould, Gregory, 2021. "A closer look at urban development under the emergence of autonomous vehicles: Traffic, land use and air quality impacts," Journal of Transport Geography, Elsevier, vol. 94(C).
    6. Chowdhury, Tufayel & Vaughan, James & Roorda, Matthew J., 2024. "Modeling impacts of freight automated vehicles in the Greater Toronto and Hamilton Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 184(C).

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