Connected and automated vehicle (CAV) is the development direction of future automobiles, and advanced driver safety assistance plays an important role as its safety assistance means. Advanced driver safety assistance technologies are electronic systems that aid a driver with safe driving. It is hard to provide all safety assistance at the same time, and the drivers have difficulty accepting the drivers are hard to accept all the assistant information. Therefore, there is a need to rank the importance of these assistance technologies. This paper first identified 23 types of important driving assistance functions, which have been recognized as the key functions for connected and automated vehicles. In order to get the subjective importance of these functions, this study adopted the maximum difference measurement method to design the questionnaire. The respondents chose the most important and the least important function. By doing this, the ambiguous judgment would be reduced. The results showed that the three most important functions were speeding warning, forward collision warning, and forward accident warning. Furthermore, the characteristics of respondents, e.g., driving age and gender, have significant impacts on the ranking results. The results of this study would support the vehicle manufacturers and policy-makers to decide the advanced driver safety assistant technologies which should give a high priority and should be installed in the connected and automated vehicles.


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    Titel :

    Subjective Importance of Advanced Driver Safety Assistance Technologies


    Beteiligte:
    He, Ziliang (Autor:in) / Zheng, Yuru (Autor:in) / Zhong, Hao (Autor:in) / Wang, Ling (Autor:in) / Ma, Wanjing (Autor:in) / Yu, Chunhui (Autor:in)

    Kongress:

    20th COTA International Conference of Transportation Professionals ; 2020 ; Xi’an, China (Conference Cancelled)


    Erschienen in:

    CICTP 2020 ; 5270-5283


    Erscheinungsdatum :

    2020-12-09




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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