@inproceedings {pub3320,
	title = {Risk-based Driver Assistance for Approaching Intersections of Limited Visibility},
	author = {Florian Damerow AND Tim Puphal AND Julian Eggert},
	year = {2017},
	month = {June},
	abstract = {This work addresses the general problem of risk evaluation in traffic scenarios for the case of limited observability of the scene due to a restricted sensory coverage. 
Here we especially concentrate on intersection scenarios, which are visually difficult to access. To distinguish the area of sight, we employ publicly available digital map data which
include, besides the general road geometry, information about buildings potentially blocking the drivers visibility. Based on the estimated area of sight, we augment the driver{\textquoteright}s sensory
perceived environment with potentially present, but not perceivable, critical scene entities. For those potentially present scene entities, we predict a, for the ego driver, worst-case-like
behavior and evaluate the upcoming collision risk. This risk model can then be employed to enrich the drivers traffic scene analysis with potentially upcoming hazards, which result
from a restricted sensory coverage. Furthermore, it can then be utilized to evaluate the drivers current behavior in terms of risk, warn the driver in case its current behavior is considered as
critical and give suggestions on how to act in a risk-aversive way. By applying the resulting intersection warning system to real world scenarios, we could validate our approach. The proposed
system{\textquoteright}s behavior reveals to be highly similar to the general behavior of a correctly acting human driver.},
	publisher = {IEEE},
	booktitle = {International Conference on Vehicular Electronics and Safety 2017},
	pages = {178-184}
}