Abstract:
At the present time cars and other private
vehicles are being used daily by large numbers of people. The biggest problem
regarding the increased use of private transport is the rising number of
fatalities that are occurring as a consequence of accidents on the roads; the
associated expense and related dangers have been recognized as a serious
problem that is being confronted by modern society. This paper focuses on developing a novel and
non-intrusive driver behavior detection system using a context-aware system in
VANET to detect abnormal behaviors exhibited by drivers, and to warn other
vehicles on the road so as to prevent accidents from happening. A five-layer
context aware architecture is proposed which is able to collect contextual information
about the driving environment, perform reasoning about certain and uncertain
contextual information and react upon that information.
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