Enhancing Vehicle Platoons in Connected and Automated Environments With an Improved Spectral Clustering-Based Pinning Control Strategy

Abstract

In connected and automated environments, implementing feedback control on selected key connected and automated vehicles within a platoon can indirectly influence the operation of human-driven vehicles, ultimately optimizing overall traffic efficiency and safety. To enhance global traffic flow through centralized control of essential vehicles, an improved spectral clustering-based pinning control (ISC-PC) strategy is proposed in this paper. The strategy considers communication topology, vehicle individual features and vehicle interactive features to identify key control nodes, targeting them for pinning control to enhance traffic flow. A control algorithm is developed for these pinning vehicles, incorporating communication topology and vehicle dynamics, with a dual focus on safety and efficiency. Furthermore, the proposed ISC-PC strategy is validated through numerical simulations, employing both synthetic and real-world datasets, which include typical noises in traffic flow. Control effects are analyzed and compared under various pinning node identification methods and pinning rates. Experimental results indicate that the ISC-PC strategy is highly effective in reducing traffic oscillations and improving traffic efficiency and safety, underscoring its potential to maximize control effects under constrained control conditions.