Fahrerabsichtserkennung und Risikobewertung für warnende Fahrerassistenzsysteme

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...

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Bibliographic Details
Main Author: Liebner, Martin (auth)
Format: Electronic Book Chapter
Published: KIT Scientific Publishing 2016
Series:Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie
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Online Access:DOAB: download the publication
DOAB: description of the publication
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520 |a 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. 
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650 7 |a Technology: general issues  |2 bicssc 
653 |a Risk Assessment 
653 |a Fahrerverhaltensmodell 
653 |a Risikobewertung 
653 |a Situationsbewusstsein 
653 |a Fahrerabsichtserkennung 
653 |a Dynamisches Bayes'sches NetzDriver Intent Inference 
653 |a Situation Awareness 
653 |a Driver Model 
653 |a Dynamic Bayesian Network 
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856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/47328  |7 0  |z DOAB: description of the publication