DocumentCode :
2981283
Title :
Rule-based tracking of multiple lanes using particle filters
Author :
Vacek, Stefan ; Bergmann, Stephan ; Mohr, Ulrich ; Dillmann, Rüdiger
Author_Institution :
Inst. of Comput. Sci. & Eng., Karlsruhe Univ.
fYear :
2006
fDate :
Sept. 2006
Firstpage :
203
Lastpage :
208
Abstract :
Tracking of lanes is essential for intelligent vehicles in order to drive autonomously. A system is presented which allows tracking of multiple lanes. The system is based on a clear modelling of a lane and the parameter set of each lane is estimated using a particle filter which fuses different cues. A finite-state machine then decides whether or not a lane is really tracked. For each lane, a separate tracker is used and a set of rules controls the life-cycle of all trackers and keeps track of all the estimated lanes
Keywords :
finite state machines; intelligent robots; particle filtering (numerical methods); remotely operated vehicles; tracking; finite-state machine; intelligent vehicles; multiple lanes; particle filters; rule-based tracking; Fuses; Intelligent systems; Intelligent vehicles; Knowledge based systems; Life estimation; Particle filters; Particle tracking; Probability density function; Roads; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multisensor Fusion and Integration for Intelligent Systems, 2006 IEEE International Conference on
Conference_Location :
Heidelberg
Print_ISBN :
1-4244-0566-1
Electronic_ISBN :
1-4244-0567-X
Type :
conf
DOI :
10.1109/MFI.2006.265649
Filename :
4042066
Link To Document :
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