Sun, Dengjiang (Beijing Jiaotong University), Xie, Dongfan (Beijing Jiaotong University), Zhao, Xiaomei (Beijing Jiaotong University)

Event-Trigger Mechanism Based Multi-Mode Platoon Control in Heterogeneous Traffic Flow

Scheduled for presentation during the Poster Session "Automated vehicle platoons" (ThBT16), Thursday, September 26, 2024, 14:30−16:30, Foyer

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on December 26, 2024

Abstract

This paper presents a multi-mode control strategy integrating Model Predictive Control (MPC) and Linear Quadratic Regulator (LQR) control models with an event-triggered mechanism. In the multi-mode control strategy, we have developed an MPC-based control model to achieve cooperative control of connected and automated vehicles (CAVs) in a platoon. Due to the uncertainties of human-driven vehicles in heterogeneous traffic, the predictive control model utilizes the predicted acceleration of the front vehicle generated by a data-driven state prediction model. To integrate the predictive control model with the LQR control model, we have developed a series of criteria to detect abnormal events and implement the event-triggered mechanism. Simulation experiments have been conducted to evaluate the performance of the proposed control strategy in terms of efficacy and computational efficiency. Additionally, traffic simulation experiments have been conducted to assess the impact of the proposed control strategy on traffic flow dynamics under CAV penetration of 50% and 100%. The simulation results demonstrate that the proposed control strategy can effectively improve control efficiency with minimal loss of control performance compared to the pure MPC control model.