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IJRR
2006

Bayesian Occupancy Filtering for Multitarget Tracking: An Automotive Application

9 years 2 months ago
Bayesian Occupancy Filtering for Multitarget Tracking: An Automotive Application
Reliable and efficient perception and reasoning in dynamic and densely cluttered environments are still major challenges for driver assistance systems. Most of today's systems use target tracking algorithms based on object models. They work quite well in simple environments such as freeways, where few potential obstacles have to be considered. However, these approaches usually fail in more complex environments featuring a large variety of potential obstacles, as is usually the case in urban driving situations. In this paper, we propose a new approach for robust perception and risk assessment in highly dynamic environments. This approach is called Bayesian occupancy filtering; it basically combines a four-dimensional occupancy grid representation of the obstacle state space with Bayesian filtering techniques. KEY WORDS--multitarget tracking, Bayesian state estimation, occupancy grid
Christophe Coué, Cédric Pradalier, C
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2006
Where IJRR
Authors Christophe Coué, Cédric Pradalier, Christian Laugier, Thierry Fraichard, Pierre Bessière
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