Li, Xinyu (Yanshan University), Zhang, Jin (Yanshan University), Xue, Jiaqi (Yanshan University), Qi, Lin (Yanshan University), Tang, Wenbin (YanShan University), Jiao, Xiaohong (Yanshan University)

Predictive Cruise Control for Connected Autonomous Vehicles Considering Communication Delay in Mixed Traffic

Scheduled for presentation during the Invited session "New Advances in Automotive Control Technology" (ThB2), Thursday, October 31, 2024, 13:30−13:50, Room T2

7th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, Oct 30 - Nov 1, 2024, Dalian, China

This information is tentative and subject to change. Compiled on May 16, 2025

Abstract

The stochastic behaviors of human-driven vehicles (HDVs) and the communication delay of Vehicle-to-Everything (V2X) technique present challenges to the advancement of connected autonomous vehicles (CAVs) in mixed traffic comprising CAVs, uncertain numbers of HDVs and connected HDVs (CHDVs). Consequently, a predictive cruise control strategy based on V2X communication is proposed for CAVs in a mixed platoon. Firstly, a long-short-term memory (LSTM) network combined with a conditional linear Gaussian (CLG) model is adopted for speed prediction of the preceding vehicle considering the communication delay. Subsequently, the CAV’s speed planning is conducted for passing continuous signalized intersections without stopping. Then, the planned speed is tracked in energy-efficient, safe, and comfortable manners under a stochastic model predictive control (SMPC) framework. The simulation results validate the effectiveness and advantages of the proposed strategy