A hybrid Bayesian Network approach to detect driver cognitive distraction

Transportation Research Part C: Emerging Technologies

Volumn 38, Issue , 2014, Pages 146-155

  Liang, Yulan ^a   Lee, John D ^a,b  

^a University of Iowa   (United States)

^b Wisconsin Electric Machines and Power Electronics Consortium   (United States)

Author keywords

Bayesian Network; Data mining; Distraction detection; Distraction mitigation; Driver cognitive distraction; Driver state monitoring; Layered algorithm; Supervised clustering

Indexed keywords

AUTOMOBILE DRIVERS; BAYESIAN NETWORKS; COGNITIVE SYSTEMS; COMPUTATIONAL EFFICIENCY; DATA MINING; DIGITAL STORAGE; EYE MOVEMENTS; SUPPORT VECTOR MACHINES;

COGNITIVE DISTRACTIONS; DISTRACTION MITIGATION; DRIVING PERFORMANCE MEASURES; DYNAMIC BAYESIAN NETWORKS; HYBRID BAYESIAN NETWORKS; STATE MONITORING; SUPERVISED CLUSTERING; SUPPORT VECTOR MACHINE ALGORITHM;

CLUSTERING ALGORITHMS;

ALGORITHM; BAYESIAN ANALYSIS; CLUSTER ANALYSIS; DATA MINING;

EID: 84889672828     PISSN: 0968090X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trc.2013.10.004     Document Type: Article

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