The attention towards hydrogen energy is growing as green energy sources are becoming more and more important over the world. the South Korean government has also implemented hydrogen economy since 2018 and established a plan to develop into a hydrogen economy leading country through fuel cell electric vehicles (FCEVs) and hydrogen fuel cells. Therefore, a preparatory process of verifying awareness and acceptance of FCEV and hydrogen energy through research is necessary. As there are issues about the safety of hydrogen energy due to several explosion accidents, we hypothesized that psychological attitudes to hydrogen energy like risk perception and familiarity would be effect on vehicle purchase behavior. In order to verify hypothesis this study analyzed using logistic regression and decision tree method, a machine learning technique for a preference model among FCEVs. The results show that hydrogen risk has a larger influence than hydrogen familiarity on the choice of FCEVs. In addition, we identified that the variables which are vehicle price, charge price, VKT(Vehicle Kilometers Traveled), distance to the charging station, gender, and age group also affect on vehicle purchase behavior. Using the decision tree algorithm in the AI technique, analysis results for vehicle preference in e-mobility (EVs, hybrid, FCEVs) show that hybrid vehicles select 46%, EVs 31%, FCEVs 23%. In addition, as a result of analyzing the influence of variables on the e-mobility Preference, the major variables were charge price, distance to the charging station, and vehicle price, in the descending order of importance.


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    Title :

    Do Perceptions of Hydrogen Energy Effect on Vehicle Preference? A Learning-Based Model Approach


    Additional title:

    KSCE J Civ Eng


    Contributors:
    Kim, Woojin (author) / Kim, Junghwa (author) / Jang, Jeong Ah (author) / Kim, Suk-Hee (author)

    Published in:

    Publication date :

    2023-02-01


    Size :

    9 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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