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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
Bahir Dar Univ, Fac Civil & Water Resources Engn, Bahir Dar Inst Technol, POB 26, Bahir Dar, Ethiopia.;Univ Mons, Fac Engn, B-7000 Mons, Belgium..
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.ORCID iD: 0000-0002-5522-9983
Budapest Univ Technol & Econ, Dept Transport Technol & Econ, H-1111 Budapest, Hungary.;KTI Inst Transport Sci, Dept Transport Policy & Econ, H-1111 Budapest, Hungary..
2022 (English)In: Energies, E-ISSN 1996-1073, Vol. 15, no 18, article id 6669Article in journal (Refereed) Published
Abstract [en]

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 (CO2), nitrogen oxides (NOx), and particulate matter (PM10) 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.

Place, publisher, year, edition, pages
MDPI AG , 2022. Vol. 15, no 18, article id 6669
Keywords [en]
cooperative automated vehicles, autonomous automated vehicles, microscopic simulation, experimental analysis, traffic flow, traffic emissions, freeway segments
National Category
Cardiac and Cardiovascular Systems Manufacturing, Surface and Joining Technology Cancer and Oncology
Identifiers
URN: urn:nbn:se:kth:diva-319835DOI: 10.3390/en15186669ISI: 000858591200001Scopus ID: 2-s2.0-85138701180OAI: oai:DiVA.org:kth-319835DiVA, id: diva2:1702902
Note

QC 20221012

Available from: 2022-10-12 Created: 2022-10-12 Last updated: 2023-08-28Bibliographically approved

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Zefreh, Mohammad Maghrour

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