DocumentCode :
3467012
Title :
Combined road prediction and target tracking in collision avoidance
Author :
Eidehall, Andreas ; Gustafsson, Fredrik
Author_Institution :
Vehicle Dynamics & Active Safety, Volvo Car Corp., Goteborg, Germany
fYear :
2004
fDate :
14-17 June 2004
Firstpage :
619
Lastpage :
624
Abstract :
Detection and tracking of other vehicles and lane geometry will be required for many future intelligent driver assistance systems. By integrating the estimation of these two features into a single filter, a more optimal utilization of the available information can be achieved. For example, it is possible to improve the lane curvature estimate during bad visibility by studying the motion of other vehicles. This paper derives and evaluates various approximations that are needed in order to deal with the non-linearities that are introduced by such an approach.
Keywords :
Kalman filters; approximation theory; collision avoidance; driver information systems; filtering theory; geometry; target tracking; vehicles; Kalman filters; approximation theory; collision avoidance; intelligent driver assistance systems; lane curvature estimation; lane geometry; optimal utilization; road prediction; target tracking; vehicle detection; vehicle motion; vehicle tracking; Collision avoidance; Geometry; Information filtering; Information filters; Intelligent systems; Intelligent vehicles; Roads; Target tracking; Vehicle detection; Vehicle driving;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium, 2004 IEEE
Print_ISBN :
0-7803-8310-9
Type :
conf
DOI :
10.1109/IVS.2004.1336455
Filename :
1336455
Link To Document :
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