Ride Comfort Optimization via Speed Planning and Preview Semi-Active Suspension Control for Autonomous Vehicles on Uneven Roads

Abstract

By simultaneously utilizing preview and global road information, a comfort optimization strategy which combines vehicle speed planning and preview semi-active suspension control is designed for autonomous vehicles. Considering that the impact of vehicle speed at the suspension vibration source is always a barrier for preview suspension control, a processing method for the road data is novelly proposed. Then, to utilize the processed data and to handle the nonlinearity of semi-active actuators, a hybrid horizon-varying (HV) model predictive control (MPC) method is given. The method can adapt to speed variation and meanwhile take the most of the road data within a fixed preview length. Further, based on the global information and considering multiple road irregularities in a driving path, a speed planning problem is established in the spatial domain and a dynamic programming based solution is provided. The final speed trajectory can compromise the driving time, vertical vibration and longitudinal acceleration. Various simulation results have been employed to verify the superiority of the hybrid HV-MPC method and the significance of speed and suspension coordination for comfort improvement.