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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1. Verfasser:	Liebner, Martin
Format:	Buch
Sprache:	ger
Schlagworte:	Driver Model Dynamic Bayesian Network Dynamisches Bayes'sches NetzDriver Intent Inference Fahrerabsichtserkennung Fahrerverhaltensmodell Risikobewertung Risk Assessment Situation Awareness Situationsbewusstsein T1-995 Technology, Engineering, Agriculture, Industrial processes Technology: general issues
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creator	Liebner, Martin
description	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.
doi_str_mv	10.5445/KSP/1000053685
format	Book
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issn	1613-4214
language	ger
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source	DOAB: Directory of Open Access Books
subjects	Driver Model Dynamic Bayesian Network Dynamisches Bayes'sches NetzDriver Intent Inference Fahrerabsichtserkennung Fahrerverhaltensmodell Risikobewertung Risk Assessment Situation Awareness Situationsbewusstsein T1-995 Technology, Engineering, Agriculture, Industrial processes Technology: general issues
title	Fahrerabsichtserkennung und Risikobewertung für warnende Fahrerassistenzsysteme
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