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Evaluation of Decentralized Algorithms for Coordination of Autonomous Vehicles at Intersections

Chamideh, Seyedezahra LU ; Tärneberg, William LU and Kihl, Maria LU (2021)
Abstract
Connected Autonomous Vehicles (AVs) with Vehicle-to-Vehicle (V2V) communication are becoming an essential component of the transportation system. Self-driving cars have the potential to optimize the roads' traffic flow, fuel consumption and remove the possibility of human error and distractions. In these systems, all involved vehicles must be fully autonomous for maximum gain. However, a fully automated system requires major updates in the transportation and network infrastructure. In this paper, we investigate intelligent traffic control mechanisms for autonomous vehicles at intersections as a replacement of traditional intersection control (i.e traffic lights). Two well-cited decentralized optimization algorithms for cooperative vehicles... (More)
Connected Autonomous Vehicles (AVs) with Vehicle-to-Vehicle (V2V) communication are becoming an essential component of the transportation system. Self-driving cars have the potential to optimize the roads' traffic flow, fuel consumption and remove the possibility of human error and distractions. In these systems, all involved vehicles must be fully autonomous for maximum gain. However, a fully automated system requires major updates in the transportation and network infrastructure. In this paper, we investigate intelligent traffic control mechanisms for autonomous vehicles at intersections as a replacement of traditional intersection control (i.e traffic lights). Two well-cited decentralized optimization algorithms for cooperative vehicles are compared with realistic simulations in SUMO. We investigate the safety and feasibility of deploying the proposed algorithms in the real world. Further, we study the scalability and performance of the algorithms in the presence of communication impairments associated with wireless channels. This side-by-side comparison helps to gain insight into the strengths and limitations of these types of algorithms. (Less)
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
2021 IEEE International Intelligent Transportation Systems Conference (ITSC)
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:85118446676
ISBN
978-1-7281-9142-3
DOI
10.1109/ITSC48978.2021.9564604
language
English
LU publication?
yes
id
3f8ca3fb-c883-455c-98a6-3774417425f2
date added to LUP
2021-11-11 12:28:14
date last changed
2022-05-05 05:38:47
@inproceedings{3f8ca3fb-c883-455c-98a6-3774417425f2,
  abstract     = {{Connected Autonomous Vehicles (AVs) with Vehicle-to-Vehicle (V2V) communication are becoming an essential component of the transportation system. Self-driving cars have the potential to optimize the roads' traffic flow, fuel consumption and remove the possibility of human error and distractions. In these systems, all involved vehicles must be fully autonomous for maximum gain. However, a fully automated system requires major updates in the transportation and network infrastructure. In this paper, we investigate intelligent traffic control mechanisms for autonomous vehicles at intersections as a replacement of traditional intersection control (i.e traffic lights). Two well-cited decentralized optimization algorithms for cooperative vehicles are compared with realistic simulations in SUMO. We investigate the safety and feasibility of deploying the proposed algorithms in the real world. Further, we study the scalability and performance of the algorithms in the presence of communication impairments associated with wireless channels. This side-by-side comparison helps to gain insight into the strengths and limitations of these types of algorithms.}},
  author       = {{Chamideh, Seyedezahra and Tärneberg, William and Kihl, Maria}},
  booktitle    = {{2021 IEEE International Intelligent Transportation Systems Conference (ITSC)}},
  isbn         = {{978-1-7281-9142-3}},
  language     = {{eng}},
  month        = {{10}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Evaluation of Decentralized Algorithms for Coordination of Autonomous Vehicles at Intersections}},
  url          = {{http://dx.doi.org/10.1109/ITSC48978.2021.9564604}},
  doi          = {{10.1109/ITSC48978.2021.9564604}},
  year         = {{2021}},
}