A comparison of selected simple supervised learning algorithms to predict driver intent based on gaze data

Neurocomputing

Volumn 121, Issue , 2013, Pages 108-130

  Lethaus, Firas ^a   Baumann, Martin R K ^a   Köster, Frank ^a   Lemmer, Karsten ^a  

^a GERMAN AEROSPACE CENTER DLR   (Germany)

Author keywords

Artificial Neural Networks; Bayesian Networks; Driver intent; Eye tracking; Naive Bayes Classifiers; Supervised learning

Indexed keywords

ARBITRARY FUNCTIONS; BAYESIAN NETWORKS (BNS); CONTROLLER AREA NETWORK; DRIVER INTENT; EYE-TRACKING; INFORMATION GATHERING; LIDAR (LIGHT DETECTION AND RANGING); NAIVE BAYES CLASSIFIERS;

BAYESIAN NETWORKS; CONTROL SYSTEM SYNTHESIS; EYE MOVEMENTS; FORECASTING; NEURAL NETWORKS; OPTICAL RADAR; SUPERVISED LEARNING;

BEHAVIORAL RESEARCH;

ACCURACY; ADULT; ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYESIAN LEARNING; DRIVER; DRIVING ABILITY; EYE MOVEMENT; FEMALE; GAZE; HUMAN; HUMAN EXPERIMENT; INFORMATION PROCESSING; INTERMETHOD COMPARISON; LEARNING ALGORITHM; MACHINE LEARNING; MALE; MODEL; NORMAL HUMAN; PREDICTIVE VALIDITY; PRIORITY JOURNAL; PSYCHOMOTOR ACTIVITY; SIMULATION; TRAFFIC;

EID: 84884160212     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2013.04.035     Document Type: Article

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