Experience is a kind of knowledge that people can get from everyday practice, which can make a novice an expert. Behavioral data showed that experienced driver and novice had different driving behavior patterns, and there existed a close relation between driving behavior pattern and driving performance. In this study, a simulated driving system was used as a driving environment. Based on 10 drivers' (including 5 drivers with more than 30 thousands kilometers driving and 5 just-got-license drivers) driving performance, a Hidden Markov Model (HMM) was built to find the critical features that differentiate expert driver and novice. The classification HMM model was verified by another 10 experienced + 10 novice drivers' driving performance. The correct recognition rate of the differentiation HMM model is more than 85%.


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    Titel :

    The Application of Hidden Markov Model in Classifying Novice and Experienced Drivers by Driving Behavioral Features


    Beteiligte:
    Yu, Lu (Autor:in) / Sun, Xianghong (Autor:in) / Ge, Yan (Autor:in)

    Kongress:

    Second International Conference on Transportation Engineering ; 2009 ; Southwest Jiaotong University, Chengdu, China



    Erscheinungsdatum :

    2009-07-29




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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