A Hierarchical Consensus-Based Negotiation Scheme for Multiplatoon Cooperative Control

Cooperative platooning holds great potential for driving safety and road efficiency. However, limited communication resources and dynamic network topologies pose challenges to reliable and timely vehicular negotiation on joint platoon control (e.g., changing lanes and giving ways) in cooperative platooning. In this article, we propose a new hierarchical consensus (HC) framework to support reliable and fast coordination among multiple platoons for safe and efficient driving control. The HC framework consists of intraplatoon and interplatoon schemes. For the intraplatoon scheme, we propose a new practical Byzantine fault tolerance (PBFT) enabled intraplatoon consensus mechanism. An adaptive local consensus scheme is designed to reduce the local consensus delay and improve the successful local consensus ratio. For the interplatoon consensus, we develop a new Raft and 5G time sensitive networking (5G-TSN)-based scheme to enhance the responsiveness and scalability of multiplatoon negotiations. Furthermore, we design a dynamic prioritization scheme for 5G-TSN flows and develop an intelligent flow scheduling algorithm to improve interactions among platoons and shorten the total negotiation delay, while ensuring successful multiplatoon negotiations. Simulation results indicate that the proposed scheme can significantly enhance the multiplatoon negotiation performance for cooperative control, with more than 16.9% higher successful consensus ratio and 14% lower negotiation delay than existing approaches.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-11-27
DOI
https://doi.org/10.1109/jiot.2024.3506930
Citations
3
Primary Topic
Traffic control and management
Type
article
Field-Weighted Citation Impact
0.98
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article

A Hierarchical Consensus-Based Negotiation Scheme for Multiplatoon Cooperative Control

Supeng Leng, Jianhua He, Hanwen Zhang, Jiayu Cao
3 citations
IEEE Internet of Things Journal
Traffic control and management
0.98
article

A Hierarchical Consensus-Based Negotiation Scheme for Multiplatoon Cooperative Control

Supeng Leng, Jianhua He, Hanwen Zhang, Jiayu Cao
article en
3 citations

Abstract

Cooperative platooning holds great potential for driving safety and road efficiency. However, limited communication resources and dynamic network topologies pose challenges to reliable and timely vehicular negotiation on joint platoon control (e.g., changing lanes and giving ways) in cooperative platooning. In this article, we propose a new hierarchical consensus (HC) framework to support reliable and fast coordination among multiple platoons for safe and efficient driving control. The HC framework consists of intraplatoon and interplatoon schemes. For the intraplatoon scheme, we propose a new practical Byzantine fault tolerance (PBFT) enabled intraplatoon consensus mechanism. An adaptive local consensus scheme is designed to reduce the local consensus delay and improve the successful local consensus ratio. For the interplatoon consensus, we develop a new Raft and 5G time sensitive networking (5G-TSN)-based scheme to enhance the responsiveness and scalability of multiplatoon negotiations. Furthermore, we design a dynamic prioritization scheme for 5G-TSN flows and develop an intelligent flow scheduling algorithm to improve interactions among platoons and shorten the total negotiation delay, while ensuring successful multiplatoon negotiations. Simulation results indicate that the proposed scheme can significantly enhance the multiplatoon negotiation performance for cooperative control, with more than 16.9% higher successful consensus ratio and 14% lower negotiation delay than existing approaches.

IEEE Internet of Things JournalVol. 12(7)
University of Essex (GB), University of Electronic Science and Technology of China (CN)
Openalex Percentile: Top 22%
Traffic control and management
0.98
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A Hierarchical Consensus-Based Negotiation Scheme for Multiplatoon Cooperative Control — Supeng Leng, Jianhua He, et al. · IEEE Internet of Things Journal (2024) | TGRS Research Map | TGRS