Ecological Autonomous Vehicular Platoon Control With Privacy-Preserving Communication Protocol

This paper investigates the problem of eco-friendly autonomous driving platoon control with integrated privacy preserving. A unified car-follower modeling framework is proposed to address single-lane, multi-lane, and mode transition platoon merging scenarios. To safeguard information privacy while maintaining control accuracy, the stochastic vector obfuscation mechanism is developed. Corresponding privacy-preserving control strategies and privacy multiplication protocols (PMP) are designed for each scenario. Theoretical analyses establish stability, consensus, and privacy guarantees. Numerical simulations further confirm the effectiveness in preserving privacy and stability. Moreover, comparative experiments show that the proposed approach outperforms existing methods in terms of privacy preservation, real-time performance, and control accuracy.