five

Variables and parameters description.

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Variables_and_parameters_description_/29934241
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Connected and automated vehicle (CAV) platooning, enabled by Vehicle-to-Vehicle (V2V) communication, promises significant improvements in traffic safety, throughput, and energy efficiency. However, communication constraints — such as range limitations and intermittent connectivity — disrupt information flow, destabilizing platoon dynamics. Existing models lack a unified framework to analyze how these constraints propagate through CAV interactions. To address this gap, the Platoon Intelligent Driver Model (PIDM) is proposed, a novel analytical framework that integrates dynamic communication topologies (predecessor-following, predecessor-leader-following, and 𝕜-predecessor-leader-following) with vehicle dynamics under V2V limitations. The PIDM enables systematic stability analysis and quantifies disturbance propagation mechanisms. Through numerical simulations, the study demonstrates that: (1) 𝕜-predecessor-leader-following topology reduces recovery time by 32% compared to conventional topologies; (2) smaller communication ranges (4–6 vehicles) optimize stability in urban roads, while larger ranges (8–10 vehicles) suit highways; (3) delay time tolerance thresholds depend on platoon size and topology complexity. These findings provide actionable guidelines for designing robust CAV platoon systems under real-world communication constraints.
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2025-08-18
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