An evidential fusion architecture for advanced driver assistance

Autor:	Laurent Delahoche, Benjamin Allart, Arnaud Clerentin, M. Delafosse, Bruno Marhic
Rok vydání:	2009
Předmět:	Data stream Fusion Engineering business.industry Real-time computing Transferable belief model Sensor fusion Optimal management Computer vision Omnidirectional vision Artificial intelligence Advanced driver Architecture business
Zdroj:	IROS
DOI:	10.1109/iros.2009.5354784
Popis:	In this paper, we deal with an original Advanced driver assistance system (ADAS) based on the use of omnidirectional vision and an evidential fusion architecture. The panoramic perception solution permits us to address efficiently the problem of close vehicles detection but also the monitoring side traffic system. The fusion and integration of this sensorial data stream is assumed by a credibilist architecture based on the Transferable Belief Model (TBM) of Smets. This paradigm permits the filtering of false alarms efficiently by an optimal management of the uncertainties estimation.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::d9fe03459f62c129bf82befcf0e4a8f0 https://doi.org/10.1109/iros.2009.5354784 Zobrazit plný text záznamu