The impact of autonomous vehicles on urban traffic network capacity: an experimental analysis by microscopic traffic simulation
ABSTRACTUrban commuters have been suffering from traffic congestion for a long time. In order to avoid or mitigate the congestion effect, it is significant to know how the introduction of autonomous vehicles (AVs) influence the road capacity . The effects that AVs bring to the macroscopic fundamental diagram (MFD) were investigated through microscopic traffic simulations. This is a key issue as the MFD is a basic model to describe road capacity in practical traffic engineering. Accordingly, the paper investigates how the different percentage of AVs affects the urban MFD. A detailed simulation study was carried out by using SUMO both with an artificial grid road network and a real-world network in Budapest. On the one hand, simulations clearly show the capacity improvement along with AVs penetration growth. On the other hand, the paper introduces an efficient modeling for MFDs with different AVs rates by using the generalized additive model (GAM).
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/19427867
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Supplemental Notes:
- © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. 2019. Abstract reprinted with permission of Taylor & Francis.
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Authors:
- Lu, Qiong
- Tettamanti, Tamás
- Hörcher, Dániel
- Varga, István
- Publication Date: 2020-9
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 540-549
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Serial:
- Transportation Letters: The International Journal of Transportation Research
- Volume: 12
- Issue Number: 8
- Publisher: Taylor & Francis
- ISSN: 1942-7867
- EISSN: 1942-7875
- Serial URL: http://www.tandfonline.com/toc/ytrl20/current
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Highway capacity; Market penetration; Microscopic traffic flow; Traffic simulation; Urban highways; Vehicle mix
- Geographic Terms: Budapest (Hungary)
- Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment;
Filing Info
- Accession Number: 01754264
- Record Type: Publication
- Files: TRIS
- Created Date: Oct 6 2020 9:32AM