Mixed Platoon Hierarchical Control: Elevating Safety, Stability, and Efficiency in CAV-HV Integration

In the evolving landscape of mixed traffic environments, the interaction between Connected and Autonomous Vehicles (CAVs) and Human-driven Vehicles (HVs) introduces complex dynamics that challenge traditional traffic control paradigms. The Mixed Platoon Hierarchical Control (MPHC) model innovatively addresses these dynamics by integrating advanced control strategies that optimize the coexistence of CAVs and HVs. Specifically, the model introduces two novel approaches: the Incorporate Real-time Changes in Dynamic Headway (IRC_DH), which dynamically adjusts CAV headways by utilizing real-time traffic data and road conditions, enhancing platoon efficiency and reducing headway by up to 24.35%; and the Incorporate Controls to Improve Response Speed (IC_IRS) for HVs, a multi-variable control strategy that considers vehicle states, reducing speed differentials by as much as 53.125%, thereby stabilizing platoon dynamics and significantly lowering collision risks. These strategies distinguish themselves from existing approaches by providing a more precise, adaptable, and robust solution to the dynamic challenges of mixed traffic flow, addressing both efficiency and safety. Simulation results confirm that these strategies significantly improve traffic flow efficiency and safety, providing a scalable and adaptable framework for traffic management in mixed vehicular environments. This work makes a substantial contribution to the field by emphasizing a comprehensive, real-time, and multi-dimensional approach to managing mixed traffic environments, thereby advancing the state-of-the-art in CAV-HV integration.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Intelligent Transportation Systems
Published
2025-02-21
DOI
https://doi.org/10.1109/tits.2025.3541266
Citations
3
Primary Topic
Traffic control and management
Type
article
Field-Weighted Citation Impact
3.64

Funders

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article

Mixed Platoon Hierarchical Control: Elevating Safety, Stability, and Efficiency in CAV-HV Integration

Chaofeng Pan, Jun Liang, Wensa Wang, Wei Zhao et al.
3 citations
IEEE Transactions on Intelligent Transportation Systems
Traffic control and management
3.64
article

Mixed Platoon Hierarchical Control: Elevating Safety, Stability, and Efficiency in CAV-HV Integration

Chaofeng Pan, Jun Liang, Wensa Wang, Wei Zhao, Zhou Zhang
article en
3 citations

Abstract

In the evolving landscape of mixed traffic environments, the interaction between Connected and Autonomous Vehicles (CAVs) and Human-driven Vehicles (HVs) introduces complex dynamics that challenge traditional traffic control paradigms. The Mixed Platoon Hierarchical Control (MPHC) model innovatively addresses these dynamics by integrating advanced control strategies that optimize the coexistence of CAVs and HVs. Specifically, the model introduces two novel approaches: the Incorporate Real-time Changes in Dynamic Headway (IRC_DH), which dynamically adjusts CAV headways by utilizing real-time traffic data and road conditions, enhancing platoon efficiency and reducing headway by up to 24.35%; and the Incorporate Controls to Improve Response Speed (IC_IRS) for HVs, a multi-variable control strategy that considers vehicle states, reducing speed differentials by as much as 53.125%, thereby stabilizing platoon dynamics and significantly lowering collision risks. These strategies distinguish themselves from existing approaches by providing a more precise, adaptable, and robust solution to the dynamic challenges of mixed traffic flow, addressing both efficiency and safety. Simulation results confirm that these strategies significantly improve traffic flow efficiency and safety, providing a scalable and adaptable framework for traffic management in mixed vehicular environments. This work makes a substantial contribution to the field by emphasizing a comprehensive, real-time, and multi-dimensional approach to managing mixed traffic environments, thereby advancing the state-of-the-art in CAV-HV integration.

IEEE Transactions on Intelligent Transportation SystemsVol. 26(6)
Jiangsu University (CN), Zhejiang University of Science and Technology (CN), Henan University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 8%
Traffic control and management
3.64
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