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Impacts of Different Types of Automated Vehicles on Traffic Flow Characteristics and Emissions: A Microscopic Traffic Simulation of Different Freeway Segments

Author

Listed:
  • Abebe Dress Beza

    (Faculty of Civil and Water Resources Engineering, Bahir Dar Institute of Technology, Bahir Dar University, Bahir Dar P.O. Box 26, Ethiopia
    Faculty of Engineering, University of Mons, B-7000 Mons, Belgium)

  • Mohammad Maghrour Zefreh

    (KTH Royal Institute of Technology, Division of Transport Planning, Brinellvägen 23, SE-100 44 Stockholm, Sweden)

  • Adam Torok

    (Department of Transport Technology and Economics, Budapest University of Technology and Economics, H-1111 Budapest, Hungary
    Department of Transport Policy and Economics, KTI–Institute for Transport Sciences, H-1111 Budapest, Hungary)

Abstract

Different types of automated vehicles (AVs) have emerged promptly in recent years, each of which might have different potential impacts on traffic flow and emissions. In this paper, the impacts of autonomous automated vehicles (AAVs) and cooperative automated vehicles (CAVs) on capacity, average traffic speed, average travel time per vehicle, and average delay per vehicle, as well as traffic emissions such as carbon dioxide (CO 2 ), nitrogen oxides (NO x ), and particulate matter (PM 10 ) have been investigated through a microsimulation study in VISSIM. Moreover, the moderating effects of different AV market penetration, and different freeway segments on AV’s impacts have been studied. The simulation results show that CAVs have a higher impact on capacity improvement regardless of the type of freeway segment. Compared to other scenarios, CAVs at 100% market penetration in basic freeway segments have a greater capacity improvement than AAVs. Furthermore, merging, diverging, and weaving segments showed a moderating effect on capacity improvements, particularly on CAVs’ impact, with merging and weaving having the highest moderating effect on CAVs’ capacity improvement potential. Taking average delay per vehicle, average traffic speed, and average travel time per vehicle into account, simulation results were diverse across the investigated scenarios. The emission estimation results show that 100% AAV scenarios had the best performance in emission reductions in basic freeway and merging sections, while other scenarios increased emissions in diverging and weaving sections.

Suggested Citation

  • Abebe Dress Beza & Mohammad Maghrour Zefreh & Adam Torok, 2022. "Impacts of Different Types of Automated Vehicles on Traffic Flow Characteristics and Emissions: A Microscopic Traffic Simulation of Different Freeway Segments," Energies, MDPI, vol. 15(18), pages 1-19, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6669-:d:913138
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    References listed on IDEAS

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    Cited by:

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    2. Maksymilian Mądziel & Tiziana Campisi, 2023. "Investigation of Vehicular Pollutant Emissions at 4-Arm Intersections for the Improvement of Integrated Actions in the Sustainable Urban Mobility Plans (SUMPs)," Sustainability, MDPI, vol. 15(3), pages 1-20, January.
    3. Maksymilian Mądziel, 2023. "Vehicle Emission Models and Traffic Simulators: A Review," Energies, MDPI, vol. 16(9), pages 1-31, May.
    4. Maksymilian Mądziel, 2023. "Future Cities Carbon Emission Models: Hybrid Vehicle Emission Modelling for Low-Emission Zones," Energies, MDPI, vol. 16(19), pages 1-16, October.
    5. Yao, Zhihong & Li, Le & Liao, Wenbin & Wang, Yi & Wu, Yunxia, 2024. "Optimal lane management policy for connected automated vehicles in mixed traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).

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