A Real-Time Dynamic Adjustment Cooperative Adaptive Cruise Control Method Based on Fuzzy-Robust MPC

The cooperative adaptive cruise control (CACC) system can simplify the driver's operation and improve driving safety. However, the current CACC methods can not adapt to the rapid changes in following and comfort requirements caused by complex and time-varying traffic environments. In this paper, a novel CACC method is proposed. Firstly, a switching logic of cruise following mode is formulated. Secondly, a safety distance model for velocity classification under the requirements of full velocity region of vehicle is established. Thirdly, the CACC method is designed based on fuzzy-robust model predictive control (Fuzzy-RMPC) algorithm. A five-order model of vehicle longitudinal distance is constructed. According to the safety, compliance and comfort requirements, MPC cost function and constraints are obtained. A robust controller is constructed to provide error correction terms, and a relaxation factor is introduced to extend the feasible solution. The fuzzy weight factor of the performance index is given, so that the vehicle can adapt to the complex and changeable traffic conditions. Finally, four typical conditions are selected to verify the performance of the proposed method in complex traffic environment.