Optimizing platoon safety through key node selection in pinning control strategy

Linheng Li, Can Wang, Jing Gan, Yan Zhao, Xu Qu and Bin Ran

Physica A: Statistical Mechanics and its Applications, 2024, vol. 643, issue C

Abstract: The advent of Connected and Automated Vehicles (CAVs) and vehicular platooning has ignited high expectations for improving the safety performance of future transportation systems. Present control strategies for CAV platoons primarily concentrate on regulating each vehicle within the platoon. Although theoretically equipped to optimize a variety of performance metrics, this method is heavily dependent on communication and computational resources, which may lead to exorbitant costs. This study proposes a pinning control strategy that focuses on the selection of pivotal nodes, thereby facilitating the optimization of safety indexes for the entire platoon through the control of a select group of vehicles. The strategy encompasses two critical aspects: the identification of key control nodes and the application of node-based control. Initially, a feature matrix that includes both the intrinsic dynamics of the vehicles and the dynamics relative to other vehicles is developed. Spectral clustering is then utilized to identify these pivotal nodes. Subsequently, specialized control mechanisms for these nodes are devised, based on Proportional-Integral-Derivative (PID) controllers, with the objective of improving platoon safety. The efficacy of this strategy is corroborated through numerical simulations. To assess the safety performance, four categories of Surrogate Safety Measures (SSMs), which consider distance and acceleration, are applied. The findings confirm that the pinning control strategy significantly enhances performance across various SSMs, considerably reducing the risk of collisions during platoon operations. Moreover, it improves operational efficiency and platoon stability, establishing its value as an effective method for safety enhancement.

Keywords: Vehicle platoon; Traffic safety; Connected and automated vehicles; Pinning control; Spectral clustering (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:643:y:2024:i:c:s037843712400339x

DOI: 10.1016/j.physa.2024.129830

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