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Driver behavioural classification from trajectory data
In recent years, traffic video surveillance has increased significantly. However, most of the footage is reviewed by humans or not at all. Tools capable of analysing traffic video sequences and autonomously extracting information are required. This paper presents an analysis of two automatic methods for classifying driver behaviour using only data provided by vehicle trackers. The algorithms are tested on several simulated traffic situations and their performance is compared to human observers. Factor analysis is shown to outperform human observers. We believe this is the first time automatic behavioural clustering of drivers using trajectory information has been successfully demonstrated.
Driver behavioural classification from trajectory data
In recent years, traffic video surveillance has increased significantly. However, most of the footage is reviewed by humans or not at all. Tools capable of analysing traffic video sequences and autonomously extracting information are required. This paper presents an analysis of two automatic methods for classifying driver behaviour using only data provided by vehicle trackers. The algorithms are tested on several simulated traffic situations and their performance is compared to human observers. Factor analysis is shown to outperform human observers. We believe this is the first time automatic behavioural clustering of drivers using trajectory information has been successfully demonstrated.
Driver behavioural classification from trajectory data
Rigolli, M. (Autor:in) / Williams, Q. (Autor:in) / Gooding, M.J. (Autor:in) / Brady, M. (Autor:in)
01.01.2005
265542 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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