Integrated risk management for automated driving

Abstract

This paper presents a model predictive control (MPC) approach to control a steering angle in an autonomous vehicle. In designing an automated driving control algorithm, probable risky driving situations should be considered to ensure vehicle safety. In order to guarantee safety to the possible change of traffic situation surrounding the subject vehicle, probabilistic future states of surrounding vehicles are predicted. The probabilistic behavior characteristics are analyzed based on driving data collected on a real road. Then a safe driving envelope which describes the driving condition for safety during a finite time-horizon is defined in consideration of the probabilistic prediction of future positions of surrounding vehicles. At each time step, MPC based controller computes the desired steering angle to keep the subject vehicle in the safe driving envelope during a finite time-horizon. The effectiveness of the proposed control algorithm is evaluated via computer simulation results and experiment results on a real vehicle.