@article{KasparWeidlDangetal.2011, author = {Kaspar, Dietmar and Weidl, Galia and Dang, Thao and Breuel, Gabi and Tamke, Andreas and Rosenstiel, Wolfgang}, title = {Object-Oriented Bayesian Networks for Detection of Lane Change Maneuvers}, series = {IEEE Intelligent Transportation Systems Magazine}, journal = {IEEE Intelligent Transportation Systems Magazine}, number = {4(3)}, doi = {10.1109/IVS.2011.5940468}, pages = {19 -- 31}, year = {2011}, abstract = {In this paper we introduce a novel approach towards the recognition of typical driving maneuvers in structured highway scenarios and identify some of the key benefits of traffic scene modeling with object-oriented Bayesian networks (OOBNs). The approach exploits the advantages of an introduced lane-related coordinate system together with individual occupancy grids for all vehicles. This combination allows for an efficient classification of the existing vehiclelane and vehicle-vehicle relations in a traffic scene and thus substantially improves the understanding of complex traffic scenes. We systematically propagate probabilities and variances within our network which results in probabilistic sets of the modeled driving maneuvers. Using this generic approach, we are able to classify a total of 27 driving maneuvers including merging and object following.}, subject = {Fahrerassistenzsystem}, language = {en} } @inproceedings{KasparWeidlDangetal.2011, author = {Kaspar, Dietmar and Weidl, Galia and Dang, Thao and Breuel, Gabi and Tamke, Andreas and Rosenstiel, Wolfgang}, title = {Erkennung von Fahrman{\"o}vern mit objektorientierten Bayes-Netzen}, series = {7. Workshop. Fahrerassistenzsysteme. FAS2011}, booktitle = {7. Workshop. Fahrerassistenzsysteme. FAS2011}, year = {2011}, abstract = {In diesem Artikel wird ein Ansatz zur Erkennung von Spurwechselman{\"o}vern mit Hilfe von objekt-orientierten Bayes Netzen beschrieben. Dieser Ansatz ist eine Erweiterung von Grundlagenarbeiten zur Einscherererkennung. Zun{\"a}chst werden die zur Erkennung von Spurwechselvorg{\"a}ngen erforderlichen Fahrsituationsmerkmale vorgestellt. Darauf aufbauend wird das entwickelte objekt-orientierte Bayes Netz zur Modellierung der Spurwechsel erl{\"a}utert. Dabei wird ein Spurwechsel als eine Beziehung zwischen zwei Fahrzeugen betrachtet. Dabei kann ein Fahrzeug in der Spur bleiben, die Spur nach links oder nach rechts wechseln. Durch die Kombination der M{\"o}glichkeiten der beiden Fahrzeuge entstehen 9 Klassen. Aus den relativen Positionen der Fahrzeuge ergeben sich aus den 9 Situationsklassen 27 m{\"o}gliche Spurwechselman{\"o}ver. Dabei ist das Einschervorgang ein Sonderfall der modellierten Fahrman{\"o}ver.}, subject = {Fahrerassistenzsystem}, language = {de} } @article{KasparWeidlDangetal.2012, author = {Kaspar, Dietmar and Weidl, Galia and Dang, Thao and Breuel, Gabi and Tamke, Andreas and Wedel, Andreas and Rosenstiel, Wolfgang}, title = {Object-Oriented Bayesian Networks for Detection of Lane Change Maneuvers}, series = {IEEE Intelligent Transportation Systems Magazine}, volume = {2012}, journal = {IEEE Intelligent Transportation Systems Magazine}, number = {4/3}, doi = {10.1109/MITS.2012.2203229}, pages = {19 -- 31}, year = {2012}, abstract = {This article introduces a novel approach towards the recognition of typical driving maneuvers in structured highway scenarios and shows some key benefits of traffic scene modeling with object-oriented Bayesian networks (OOBNs). The approach exploits the advantages of an introduced lane-related coordinate system together with individual occupancy schedule grids for all modeled vehicles. This combination allows an efficient classification of the existing vehicle-lane and vehicle-vehicle relations in traffic scenes and thus substantially improves the understanding of complex traffic scenes. Probabilities and variances within the network are propagated systematically which results in probabilistic sets of the modeled driving maneuvers. Using this generic approach, the network is able to classify a total of 27 driving maneuvers including merging and object following.}, subject = {Fahrerassistenzsystem}, language = {en} }