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<p>The application of multi-agent systems (MAS) in autonomous vehicle coordination is one such example and has the potential to be an important factor for improving transport systems with increased efficiency, safety, and sustainability. In this paper, a MAS framework is designed for coordinating vehicles, including agent architecture, communication protocols, and decision-making algorithms, as well as coordination strategies. The framework is evaluated in a number of heterogeneous environments (including urban traffic management and highway merging scenarios) using real-time data from case studies and simulations. Traffic flow, network efficiency, and congestion reduction are the performance metrics used to assess the proposed MAS approach. The results show that the proposed framework attains the highest overall network efficiency (92.85%) as compared to existing recent studies, thereby integrating MAS with AVs.</p>

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Augmenting traffic flow efficiency using multi-agent systems (MAS)

  • 期刊论文

  • 发表日期：

    2025年3月28日

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  • Tarak Hussain,
  • Dundi Urlamma,
  • Ratnasri Vericharla,
  • Jagjit Singh Dhatterwal

摘要

The application of multi-agent systems (MAS) in autonomous vehicle coordination is one such example and has the potential to be an important factor for improving transport systems with increased efficiency, safety, and sustainability. In this paper, a MAS framework is designed for coordinating vehicles, including agent architecture, communication protocols, and decision-making algorithms, as well as coordination strategies. The framework is evaluated in a number of heterogeneous environments (including urban traffic management and highway merging scenarios) using real-time data from case studies and simulations. Traffic flow, network efficiency, and congestion reduction are the performance metrics used to assess the proposed MAS approach. The results show that the proposed framework attains the highest overall network efficiency (92.85%) as compared to existing recent studies, thereby integrating MAS with AVs.