@inproceedings {pub2712,
	title = {Predictive risk maps},
	author = {Florian Damerow AND Julian Eggert},
	year = {2014},
	month = {October},
	abstract = {Risk evaluation schemes in urban environments have been developed for
many traffic situations such as lane keeping or crossings to validate
possible trajectories. Recent methods show difficulties for a high
number of scene entities, as it is the case for many inner city
scenarios. In this paper we address the problem of risk evaluation for motion planning in fast
changing traffic situations with high variability. The presented risk
evaluation scheme enables the generation of predictive risk maps, which
allow full motion planning taking efficiency and risk factors into
account. The introduced risk maps allow a combined motion planning for
scenes classified into situations. Simulations show a high
generality of the approach by applying it to several different scenarios
like crossings and highway driving as well as scenarios with combination
of several risk factors. For motion planning, we use simple gradient
based method on the predictive risk maps that result in collision free
trajectories with low risk.},
	publisher = {IEEE},
	booktitle = {IEEE Conference on Intelligent Transportation Systems},
	pages = {703 - 710}
}