@inproceedings {pub2976,
	title = {Framework for risk aversive and efficient behavior planning under multiple situations with uncertainty},
	author = {Florian Damerow AND Julian Eggert},
	year = {2015},
	month = {September},
	abstract = {This paper addresses the problem of future behavior evaluation and planning for upcoming ADAS, especially for inner city traffic scenarios. Situations in inner city traffic scenarios are generally highly complex and of high uncertainty. The behavior in such complex scenarios differs strongly depending on the actual present situation. In general the current situation can only be determined with high uncertainty based on current and past measurement of the ego and other interacting entities. Additionally a situation can change very quickly, e.g. if an involved traffic participant suddenly changes it{\textquoteright}s behavior. Here we propose and approach how to plan safe but still efficient future behavior under consideration multiple possible situations with different probabilities of occurrence. For each situation we predict prototypical future trajectories of all involved entities, using a highly general interaction aware model (FDM). Then, based on a continuous, probabilistic model for future risk we build so-called predictive risk maps, one for each possible situation, and plan the own behavior while minimizing overall risk and efficiency. We could show, that our approach generates efficient behavior for situations with high probability, while generating a {\textquoteleft}{\textquoteleft}plan b{\textquoteright}{\textquoteright} to keep unprobable but risky situations safe.},
	publisher = {IEEE},
	booktitle = {18th IEEE International Conference on Intelligent Transportation Systems 2015 (ITSC)},
	city = {Las Palmas},
	pages = {656-663}
}