Fahrerabsichtserkennung und Risikobewertung für warnende Fahrerassistenzsysteme

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
Subjects:
Technology: general issues
Risk Assessment
Fahrerverhaltensmodell
Risikobewertung
Situationsbewusstsein
Fahrerabsichtserkennung
Dynamisches Bayes'sches NetzDriver Intent Inference
Situation Awareness
Driver Model
Dynamic Bayesian Network
Online Access:DOAB: download the publication
DOAB: description of the publication
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Description
Summary: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.
Physical Description:1 electronic resource (XX, 159 p. p.)
ISBN:KSP/1000053685
9783731505082
Access:Open Access

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