Fahrerabsichtserkennung und Risikobewertung für warnende Fahrerassistenzsysteme
Abstract
To avoid accidents, warning driver assistance systems require an on-line estimation of the current risk of collision. For that, a new method is proposed that – in principle – is able to deal with arbitrary traffic situations. This is achieved by the use of generative models to describe the expected driver behavior. Corresponding user studies in real traffic show promising results even when real time constraints are taken into account.
Keywords
Risk Assessment; Fahrerverhaltensmodell; Risikobewertung; Situationsbewusstsein; Fahrerabsichtserkennung; Dynamisches Bayes'sches NetzDriver Intent Inference; Situation Awareness; Driver Model; Dynamic Bayesian NetworkISBN
9783731505082Publisher
KIT Scientific PublishingPublisher website
http://www.ksp.kit.edu/Publication date and place
2016Series
Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie,Classification
Technology: general issues