Context-Aware Driver Behavior Detection System in Intelligent Transportation Systems
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Abstract
Vehicular ad hoc networks (VANETs) enable short-range communication between nearby vehicles. This paper presents a five-layer architecture for detecting abnormal driver behaviors using context-aware techniques and dynamic Bayesian networks. The system identifies four behavior types-normal, intoxicated, reckless, and fatigued-by integrating driver, vehicle, and environmental data for real-time inference and accident prevention.
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Publisher: IEEE