Paper Info
Title
Bayesian programming for multi-target tracking: An automotive application
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 traffic 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 estimation, based on the occupancy grid framework. The main interest of this method is to avoid the decision problem of classical multitarget tracking algorithms. Obtained occupancy grids are combined with danger estimation to perform an elementary task of obstacle avoidance with an electric car.
Year
DOI
Venue
2003
10.1007/10991459_20
SPRINGER TRACTS IN ADVANCED ROBOTICS
Keywords
Field
DocType
ó bayesian reasonning,multi-sensor target tracking.
Obstacle avoidance,Truck,Computer vision,Computer science,Cruise control,Simulation,Collision,Bayesian programming,Artificial intelligence,Robotics,Occupancy grid mapping,Automotive industry
Conference
Volume
ISSN
Citations 
24
1610-7438
4
PageRank 
References 
Authors
0.94
4
3
Name
Order
Citations
PageRank
Christophe Coué1898.70
Cédric Pradalier233938.22
Christian Laugier320119.36