Adaptive Event-Triggered Path Tracking Control for Self-Driving Vehicles Against Denial-of-Service Attacks

Abstract

This paper focuses on the secure path tracking control of wireless self-driving vehicles (SDVs). To address the challenges of network security and limited network bandwidth in the design of wireless SDVs, a co-modeling approach considering denial-of-service (DoS) attack and event trigger mechanism (ETM) is introduced for path tracking control of SDVs. To achieve a high level of tracking control performance, the threshold of the proposed adaptive ETM is designed to adjust dynamically based on the state information of the SDVs, resulting in better tracking performance. Additionally, a novel distributed control strategy is developed for SDVs using a leader-following approach, and the parameters of the distributed controllers and adaptive ETMs are obtained to meet the path tracking performance requirements and ensure effective communication through the use of Lyapunov stability theory and linear matrix inequality (LMI) techniques. The proposed method is verified through a numerical simulation of SDVs subjected to DoS attacks, demonstrating its effectiveness.

Keywords

• Adaptive event-triggered mechanism
• DoS attack
• self-driving vehicles