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Investigating the Effects of Automated Vehicles on Large Urban Road Networks: Some Evidence from Rome

Author

Listed:
  • Umberto Crisalli

    (Department of Enterprise Engineering, University of Rome Tor Vergata, 00133 Rome, Italy)

  • Andrea Gemma

    (Department of Civil, Computer Science and Aeronautical Technologies Engineering, Roma Tre University, 00146 Rome, Italy)

  • Marco Petrelli

    (Department of Civil, Computer Science and Aeronautical Technologies Engineering, Roma Tre University, 00146 Rome, Italy)

Abstract

This paper explores the possibility of applying simulation models formalized in the macrosimulation approach to predict the effects from the presence of automated vehicles in our cities. It is based on the use of a robust equilibrium assignment model allowing us to obtain multiclass traffic flows, including automated vehicles (AVs) and conventional ones (CVs) on large real-sized road networks. This modelling framework has been successfully applied to the road network of the metropolitan area of Rome, allowing us to assess the effects of AVs in future traffic at increasing penetration rates and the effects of possible transport policies involving AVs.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10714-:d:1188935
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    References listed on IDEAS

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    1. Meyer, Jonas & Becker, Henrik & Bösch, Patrick M. & Axhausen, Kay W., 2017. "Autonomous vehicles: The next jump in accessibilities?," Research in Transportation Economics, Elsevier, vol. 62(C), pages 80-91.
    2. Wen-Xing, Zhu & Li-Dong, Zhang, 2018. "A new car-following model for autonomous vehicles flow with mean expected velocity field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 2154-2165.
    3. Gong, Siyuan & Du, Lili, 2018. "Cooperative platoon control for a mixed traffic flow including human drive vehicles and connected and autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 116(C), pages 25-61.
    4. Ghiasi, Amir & Hussain, Omar & Qian, Zhen (Sean) & Li, Xiaopeng, 2017. "A mixed traffic capacity analysis and lane management model for connected automated vehicles: A Markov chain method," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 266-292.
    5. Ye, Lanhang & Yamamoto, Toshiyuki, 2018. "Modeling connected and autonomous vehicles in heterogeneous traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 269-277.
    6. van den Berg, Vincent A.C. & Verhoef, Erik T., 2016. "Autonomous cars and dynamic bottleneck congestion: The effects on capacity, value of time and preference heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 43-60.
    7. Chen, Danjue & Ahn, Soyoung & Chitturi, Madhav & Noyce, David A., 2017. "Towards vehicle automation: Roadway capacity formulation for traffic mixed with regular and automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 100(C), pages 196-221.
    8. 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.
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