creators_name: Coue, C creators_name: Pradalier, C creators_name: Laugier, C type: confpaper datestamp: 2004-08-10 lastmod: 2011-03-11 08:55:39 metadata_visibility: show title: Bayesian Programming Multi-Target Tracking: an Automotive Application ispublished: pub subjects: comp-sci-robot full_text_status: public keywords: Bayesian reasonning, multi-sensor target tracking abstract: A prerequisite to the design of future Advanced Driver Assistance Systems for cars is a sensing system providing all the information required for high-level driving assistance tasks. In particular, target tracking is still challenging in urban trafc situations, because of the large number of rapidly maneuvering targets. The goal of this paper is to present an original way to perform target position and velocity, based on the occupancy grid framework. The main interest of this method is to avoid the decision problem of classical multi-target tracking algorithms. Obtained occupancy grids are combined with danger estimation to perform an elementary task of obstacle avoidance with an electric car. date: 2003 date_type: published refereed: FALSE citation: Coue, C and Pradalier, C and Laugier, C (2003) Bayesian Programming Multi-Target Tracking: an Automotive Application. [Conference Paper] document_url: http://cogprints.org/3754/1/coue03.pdf