Autonomous Vehicles (AVs) will impact the current travel behavior of people because the characteristics of AV are different than conventional cars. In AV, the machine takes the role of driving rather than a human driver. This study adds a new contribution to the literature by studying privately-used autonomous vehicle (PAV) and public transport (PT) considering multitasking availability. The focus of this research is on the influences of multitasking options availability, travel time, and travel cost on the travelers’ behavior. In this research, six options of multitasking are defined, such as reading, writing, talking, using social media, eating-drinking, and doing other things. A stated choice experiment is designed, where people are asked to choose either PAV or PT based on their preferences and the characteristics of each transport mode. A sample size of 4366 observations is collected in Budapest, Hungary at the beginning of 2020. A discrete choice modeling approach is applied through the Conditional Logit model to develop a transport choice model and find the impact of attribute’s changes on the choice of travelers. In this research, the main daily trip inside urban areas is only studied. The results show that only writing onboard adds a negative utility in choosing a transport mode, while others add a positive utility. Moreover, gender and car ownership variables impact the selection of a transport mode. In conclusion, people are more likely to choose PAV over PT inside urban areas because the margins show a larger modal share of PAV than PT at the same trip time and trip cost.


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    Titel :

    Modeling Multitasking Onboard of Privately-Used Autonomous Vehicle and Public Transport


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:

    Kongress:

    Scientific And Technical Conference Transport Systems Theory And Practice ; 2021 ; Katowice, Poland September 21, 2021 - September 23, 2021



    Erscheinungsdatum :

    2021-11-03


    Format / Umfang :

    16 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






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