Model predictive driver assistance control for cooperative cruise based on hybrid system driver model

Abstract

This paper presents a driver assisting system for cooperative cruising of multiple cars. In order to account for personal difference of individual drivers, each driver's vehicle following skill on expressways is identified as a PrARX model, a continuous approximation of hybrid dynamical system. The PrARX model describes the driver's logical decision making as well as continuous maneuvering in a uniform manner. The assisting acceleration is computed in the framework of model predictive control, where the plant model is a platoon of cars coupled with PrARX driver models. For computing assisting outputs in real time, a fast computation method for nonlinear model predictive control based on the continuation technique is employed. The proposed assisting system is tested in numerical simulations and on a driving simulator with a real human driver. The high speed calculation of the Homotopy method is also proved by comparison to the conventional method. Finally, the advantage of global optimization for cooperative safety is confirmed by comparing its control performance with the local optimization for individual safety.