Using Support Vector Machines and Bayesian Filtering for Classifying Agent Intentions at Road Intersections
Name
Aoude_How_SVM_BF.pdf
Size
1.22 MB
Format
Adobe PDF
Checksum (MD5)
c96b211ec763775ad13a1679350dd834
Author(s)
Aoude, Georges S.
How, Jonathan P.
Date Issued
September 15, 2009
Series/Report no.
;ACL09-02
Abstract
Classifying other agents’ intentions is a very complex task but it can be very essential in assisting (autonomous or human) agents in navigating safely in dynamic and possibly hostile environments. This paper introduces a classification approach based on support vector machines and Bayesian filtering (SVM-BF). It then applies it to a road intersection problem to assist a vehicle in detecting the intention of an approaching suspicious vehicle. The SVM-BF approach achieved very promising results.
Subjects
SVM
intersection safety
support vector machines
classification
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