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Opportunities, Challenges, and Uncertainties in Urban Road Transport Automation

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  • Steven E. Shladover

    (California PATH Program, Institute of Transportation Studies, University of California, Berkeley, CA 94720, USA
    Retired.)

Abstract

Automated driving has attracted intense attention in the media and among the general public, based on extremely optimistic predictions from some industry participants, but these have started to become more realistic in the last couple of years, after the “hype cycle” for automation peaked. This paper explains the opportunities for Automated Driving System (ADS) technology to improve the urban transport of people and goods, together with the challenges that will limit the scope and timing of the deployment of urban ADS. The discussion emphasizes the diversity of ADS applications and services, each of which has its own opportunities, challenges, and uncertainties, leading to diverse deployment scopes and schedules. The associated challenges are sufficiently daunting that ADS deployment will lag behind electrification and connectivity, leaving more time for cities to prepare for it.

Suggested Citation

  • Steven E. Shladover, 2022. "Opportunities, Challenges, and Uncertainties in Urban Road Transport Automation," Sustainability, MDPI, vol. 14(3), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1853-:d:743112
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    References listed on IDEAS

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    1. Wadud, Zia & MacKenzie, Don & Leiby, Paul, 2016. "Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 1-18.
    2. Schaller, Bruce, 2021. "Can sharing a ride make for less traffic? Evidence from Uber and Lyft and implications for cities," Transport Policy, Elsevier, vol. 102(C), pages 1-10.
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    Cited by:

    1. Tengilimoglu, Oguz & Carsten, Oliver & Wadud, Zia, 2023. "Infrastructure requirements for the safe operation of automated vehicles: Opinions from experts and stakeholders," Transport Policy, Elsevier, vol. 133(C), pages 209-222.
    2. Veisi, Omid & Moradi, Mohammad Amin & Gharaei, Beheshteh & Maleki, Farid Jabbari & Rahbar, Morteza, 2025. "Sustainable forestry logistics: Using modified A-star algorithm for efficient timber transportation route optimization," Forest Policy and Economics, Elsevier, vol. 173(C).
    3. Zwick, Felix & Kuehnel, Nico & Hörl, Sebastian, 2022. "Shifts in perspective: Operational aspects in (non-)autonomous ride-pooling simulations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 300-320.
    4. Tengilimoglu, Oguz & Carsten, Oliver & Wadud, Zia, 2024. "The effects of infrastructure quality on the usefulness of automated vehicles: A case study for Leeds, UK," Journal of Transport Geography, Elsevier, vol. 121(C).
    5. Masoud Khanmohamadi & Marco Guerrieri, 2025. "Smart Intersections and Connected Autonomous Vehicles for Sustainable Smart Cities: A Brief Review," Sustainability, MDPI, vol. 17(7), pages 1-32, April.
    6. Tengilimoglu, Oguz & Carsten, Oliver & Wadud, Zia, 2024. "Are current roads ready for highly automated driving? A conceptual model for road readiness for AVs applied to the UK city of Leeds," Transportation Research Part A: Policy and Practice, Elsevier, vol. 186(C).

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