Energy-Optimal Adaptive Cruise Control in Time Domain based on Model Predictive Control

This paper presents a novel energy-optimal adaptive cruise control (EACC) strategy based on model predictive control (MPC). The EACC has three main objectives: a) reduce the real driving fuel consumption of the controlled car; b) the controlled car has good ability of tracking its preceding car; c) the controlled car strictly keeps the minimum safety distance to its preceding car. For this multi-objective optimal control, it is important to build up a suitable problem formulation to describe various control targets properly. In this paper, three different methods of problem formulation for MPC-based EACC in time domain are proposed, deeply analysed and compared in real driving situations. In addition to the importance of the problem formulation, the prediction information such as the future speed of the preceding car also has a considerable influence on MPC-based EACC. Therefore, how the prediction information affects the performance of EACC in different driving situations is investigated. Furthermore, the impact of the prediction horizon's length on MPC is analysed in this work. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.