Caiazzo, Bianca (University of Naples Federico II), Leccese, Sara (University of Naples Federico II), Petrillo, Alberto (University of Naples Federico II), Santini, Stefania (University of Naples Federico II)

Improving the Communication Overhead in Vehicles Platoon: A Novel Dynamic Event-Triggered Predictor Method

Scheduled for presentation during the Invited Session "S24a-Traffic Control and Connected Autonomous Vehicles: benefits for efficiency, safety and beyond" (TH-LM-T24), Thursday, November 20, 2025, 11:50−12:10, Coolangata 3

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Abstract

The paper introduces a novel distributed digital predictor-feedback control combined with a dynamic event-triggered mechanism to solve the platoon formation control problem of autonomous connected vehicles undergoing large actuation delays. Due to the limited communication bandwidth, they make the control over the communication network significantly prone to hazard events during the cooperative driving. The approach achieves a twofold benefit: i) easier implementation in digital platform provided by its own sampled-data structure; ii) significant reduction of the computational/communication resources over the network by means of an event-based mechanism. The predictive control scheme modifies the classical model reduction approach in a fully distributed way so to take into account the vehicles nonlinearities, even though completely unknown. The exponential stability of the vehicular network is established by means of the Lyapunov-Krasovskii method, with derived stability conditions in the form of linear matrix inequality. Hardware-In-the-Loop validations confirm the theoretical findings.