Matthias Platho

Learn More
With the trend to highly automated driving, future driver assistance systems are required to correctly assess even complex traffic situations and to predict their progress. As soon as other road users are present the number of possible situations becomes infinite, rendering their assessment based on learned situation types impossible. In this paper we(More)
Intersections are the most accident-prone spots in the road network. In order to assist the driver in complex urban intersection situations, an ADAS will be required not only to recognize current but also to anticipate future maneuvers of the involved road users. Current approaches for intention estimation focus mainly on discerning only two intentions(More)
In order to offer even more sophisticated functionality, future driver assistance systems need the ability to robustly recognize and understand driving situations. Especially in inner-city scenarios the high complexity and variability of situations encountered make their assessment a challenging task. We propose to tackle these challenges by decomposing(More)
Intersections are among the most complex traffic situations that motorists encounter, which is reflected by the fact that in Europe more than 40 percent of accidents resulting in injury occur at intersections. In order to support the driver in crossing an intersection an advanced driver assistance system is required to predict the behavior of other drivers,(More)
For an Advanced Driver Assistance System recognizing the driving situation of other vehicles is a crucial prerequisite to anticipate their behavior and plan own maneuvers accordingly. Current methods for situation recognition usually rely on an expert for defining the considered driving situations manually while solely the parameters of the corresponding(More)
  • 1