Strategic Decision-Making Process in Advanced Driver Assistance Systems

Contemporary driver assistance systems obtain a steadily increasing grade of automation. A novel system, the emergency stop assistant, performs completely autonomous driving in emergency situations. This system takes over the vehicle's control, steers the vehicle safely to the roadside and stops, if the driver suffers a health irregularity such as a heart attack. In order to navigate through the traffic, sensors have to gain information, concerning the road and the surrounding vehicles. Subsequently, the gathered data is used to analyze and interpret the traffic situation. Depending on the current situation, driving strategies are derived, which navigate the vehicle autonomously to the roadside. The information concerning suitable areas to stop the vehicle is obtained from a digital map. This paper presents a novel method of situation interpretation based on static and dynamic state space assessment. Furthermore, the decision-making process in driving strategies using a combination of hybrid automata and decision trees will be presented.