Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Enhancing Traffic Flow and Safety in Mixed Vehicle Fleets: Mitigating the Influence of Non-Cooperative Vehicles on Autonomous Intersection Management Systems

Chamideh, Seyedezahra LU ; Tärneberg, William LU and Kihl, Maria LU (2023) 31st International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2023
Abstract
With the rapid advancement of autonomous vehicle technology, integrating mixed autonomous and non-autonomous vehicles that are not cooperative in vehicular network has become a significant challenge. This paper presents an innovative Autonomous Intersection Management (AIM) system designed to optimize traffic flow and enhance intersection safety in such mixed traffic scenarios. By utilizing vehicle-to-infrastructure (V2I) communication and advanced intersection control algorithms, the AIM system showcases the potential of next-generation vehicular network technologies in revolutionizing intersection management. To evaluate the performance of the AIM system and the impact of non-cooperative vehicles, extensive simulations were conducted... (More)
With the rapid advancement of autonomous vehicle technology, integrating mixed autonomous and non-autonomous vehicles that are not cooperative in vehicular network has become a significant challenge. This paper presents an innovative Autonomous Intersection Management (AIM) system designed to optimize traffic flow and enhance intersection safety in such mixed traffic scenarios. By utilizing vehicle-to-infrastructure (V2I) communication and advanced intersection control algorithms, the AIM system showcases the potential of next-generation vehicular network technologies in revolutionizing intersection management. To evaluate the performance of the AIM system and the impact of non-cooperative vehicles, extensive simulations were conducted using realistic traffic scenarios and a mixed traffic model. The results demonstrate that the proposed system effectively enhances intersection throughput, and ensures safe and efficient operations, particularly in situations involving a high proportion of autonomous vehicles. Additionally, the system’s robustness is demonstrated by evaluating its performance under various traffic flow rates and considering imperfect wireless communication conditions. (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
2023 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
31st International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2023
conference location
Split, Croatia
conference dates
2023-09-21 - 2023-09-23
external identifiers
  • scopus:85174531038
ISBN
979-8-3503-0107-6
DOI
10.23919/SoftCOM58365.2023.10271599
language
English
LU publication?
yes
id
38069a3b-4c7b-4dc8-8d4a-be5bae28f586
date added to LUP
2023-10-11 09:57:43
date last changed
2024-02-13 01:59:16
@inproceedings{38069a3b-4c7b-4dc8-8d4a-be5bae28f586,
  abstract     = {{With the rapid advancement of autonomous vehicle technology, integrating mixed autonomous and non-autonomous vehicles that are not cooperative in vehicular network has become a significant challenge. This paper presents an innovative Autonomous Intersection Management (AIM) system designed to optimize traffic flow and enhance intersection safety in such mixed traffic scenarios. By utilizing vehicle-to-infrastructure (V2I) communication and advanced intersection control algorithms, the AIM system showcases the potential of next-generation vehicular network technologies in revolutionizing intersection management. To evaluate the performance of the AIM system and the impact of non-cooperative vehicles, extensive simulations were conducted using realistic traffic scenarios and a mixed traffic model. The results demonstrate that the proposed system effectively enhances intersection throughput, and ensures safe and efficient operations, particularly in situations involving a high proportion of autonomous vehicles. Additionally, the system’s robustness is demonstrated by evaluating its performance under various traffic flow rates and considering imperfect wireless communication conditions.}},
  author       = {{Chamideh, Seyedezahra and Tärneberg, William and Kihl, Maria}},
  booktitle    = {{2023 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)}},
  isbn         = {{979-8-3503-0107-6}},
  language     = {{eng}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Enhancing Traffic Flow and Safety in Mixed Vehicle Fleets: Mitigating the Influence of Non-Cooperative Vehicles on Autonomous Intersection Management Systems}},
  url          = {{http://dx.doi.org/10.23919/SoftCOM58365.2023.10271599}},
  doi          = {{10.23919/SoftCOM58365.2023.10271599}},
  year         = {{2023}},
}