A predictive driver model with physical constraints for closed loop simulation of vehicle-driver system

Abstract

This paper presents a longitudinal and lateral predictive driver model. The predictive driver model has been designed for closed loop simulation of vehicle-driver system. Preview, prediction, manipulation update and speed planning characteristics are considered as human driver characteristics. Human driver generally decelerates when the driver drives on curved path not to exceed expected lateral acceleration by driver. In this paper, Model Predictive Control (MPC) is used to represent human driver model characteristics. MPC design incorporates all constraints on state, control and output variables. And the constraints are used in driver model in order to represent drivability of human driver. Planned speed by human driver is considered in MPC receding prediction horizon to determine steering angle on curved path. Simulation results show that the proposed human driver model can represent actual human driver characteristics and also shows the feasibility of the MPC algorithm in real-time application.