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Implications of the Emergence of Autonomous Vehicles and Shared Autonomous Vehicles: A Budapest Perspective

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  • Mohamad Shatanawi

    (Department of Transport Technology and Economics, Budapest University of Technology and Economics, Műegyetem rkp. 3, 1111 Budapest, Hungary)

  • Ferenc Mészáros

    (Department of Transport Technology and Economics, Budapest University of Technology and Economics, Műegyetem rkp. 3, 1111 Budapest, Hungary)

Abstract

The introduction of autonomous vehicles (AVs) and shared autonomous vehicles (SAVs) is projected to enhance network performance and accessibility. The future share distribution of AV and SAV is not yet apparent, nor is which of these two future transport modes will become dominant. Therefore, this research deploys a simulation-based dynamic traffic assignment using Visum software to investigate the impact of varying the share distribution of AVs and SAVs on Budapest’s network performance and consumer surplus in three projected future traffic scenarios for the years 2030 and 2050 compared to the Base scenario for 2020. The three future scenarios are presented and characterized by different penetration rates of AVs and SAVs to reflect the uncertainty in the market share of these future cars as follows: Mix-Traffic scenario for 2030, and AV-Focused and SAV-Focused scenarios for 2050. The results revealed that the emergence of AVs and SAVs would improve the overall network performance, and better performance was observed with increasing the share distribution of SAVs. Similarly, the consumer surplus increased in all future scenarios, especially with increasing the share distribution of AVs. Consequently, the advent of AVs and SAVs will improve traffic performance and increase consumer surplus, benefiting road users and authorities.

Suggested Citation

  • Mohamad Shatanawi & Ferenc Mészáros, 2022. "Implications of the Emergence of Autonomous Vehicles and Shared Autonomous Vehicles: A Budapest Perspective," Sustainability, MDPI, vol. 14(17), pages 1-19, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:17:p:10952-:d:904761
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    References listed on IDEAS

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    Cited by:

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    2. Jing Zuo & Mengxing Shang & Jianwu Dang, 2022. "Research on the Optimization Model of Railway Emergency Rescue Network Considering Space-Time Accessibility," Sustainability, MDPI, vol. 14(21), pages 1-14, November.

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