This initial research study examines the preferences of the general public concerning the adoption of various scenarios associated with self-driving vehicles (SDV). This study aimed to evaluate the readiness of one hundred volunteers to employ self-driving vehicles (SDVs) in fifteen scenarios. The simulations included highway driving with options for human intervention and autonomous public transportation systems. We conducted descriptive and cluster analyses to identify significant patterns and classify comparable scenarios. Participants exhibited a moderate to high desire to employ autonomous vehicles in different scenarios. People expressed a strong willingness to use these technologies in settings such as universities and airports and for daily life. However, there was an apparent hesitation regarding the acceptance of autonomous vehicles for long trips and the concept of self-driving taxis operating without any human supervision. The findings reveal four distinct preference clusters: 'Highway Focus' (highway driving with manual control option), 'Safety Conscious' (hesitant toward full automation), 'Convenience Seekers' (specific situations such as traffic congestion), and 'Enthusiastic Adopters' (high overall acceptance). These clusters show various attitudes toward adopting self-driving vehicles (SDVs) and the importance of developing tailored strategies to tackle specific challenges and improve overall acceptance. There is a general openness to autonomous vehicles, particularly in specific scenarios or regulated settings. However, safety concerns and the need for control still pose major challenges to widespread use. Public acceptance will likely take time and depend on how well these issues are addressed. Further research and development are needed to improve safety, reliability, and public trust in driverless technology.


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    Titel :

    Self-Driving Vehicles: Exploring Preferred Adoption Scenarios - A Preliminary Study


    Beteiligte:


    Erscheinungsdatum :

    17.12.2024


    Format / Umfang :

    256457 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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