Statistical modelling of algorithms for signal processing in systems based on environment perception
Abstract (englisch):
One cornerstone for realising automated driving systems is an appropriate handling of uncertainties in the environment perception and situation interpretation. Uncertainties arise due to noisy sensor measurements or the unknown future evolution of a traffic situation. This work contributes to the understanding of these uncertainties by modelling and propagating them with parametric probability distributions.
| Zugehörige Institution(en) am KIT | Institut für Anthropomatik und Robotik (IAR) |
| Publikationstyp | Hochschulschrift |
| Publikationsjahr | 2016 |
| Sprache | Englisch |
| Identifikator | urn:nbn:de:swb:90-567492 KITopen-ID: 1000056749 |
| Verlag | Karlsruher Institut für Technologie (KIT) |
| Umfang | XII, 234 S. |
| Art der Arbeit | Dissertation |
| Fakultät | Fakultät für Informatik (INFORMATIK) |
| Institut | Institut für Anthropomatik und Robotik (IAR) |
| Prüfungsdaten | 09.06.2016 |
| Schlagwörter | automated driving, advanced driver assistance systems, probabilistic modelling, uncertainty propagation |
| Referent/Betreuer | Zöllner, J. M. |