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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Detalles Bibliográficos
Otros Autores: Liebner, Martin (auth)
Formato: Libro electrónico
Idioma:Alemán
Publicado: KIT Scientific Publishing 2016
Colección:Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009429723706719
Descripción
Sumario: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.
Descripción Física:1 electronic resource (XX, 159 p. p.)