인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Objective: To investigate how the blackout of natural driving visual information on the windshield in Level 5 autonomous driving impacts passengers' flow states during non-driving related tasks (NDRTs).
Background: As Level 5 autonomous driving technology progresses, passengers are no longer required to engage in driving, allowing full focus on NDRTs. Prior research has primarily focused on Level 3 autonomous driving, examining driver handover scenarios and the necessary visual information. However, in a fully autonomous setting where no driver intervention is required, understanding the influence of visual information on NDRT engagement is essential.
Method: This study employed a Level 5 autonomous driving simulator with 27 participants performing NDRTs, specifically video watching and gaming tasks, under both conditions: with and without windshield visual information. An ANOVA analysis was conducted to evaluate the effect of visual information control on NDRT flow states.
Results: The findings showed a significant decrease in NDRT flow states when windshield visual information was blocked. Notably, participants with driving licenses experienced a pronounced impact, while those without licenses showed no significant difference in flow states between conditions.
Conclusion: The blackout of windshield visual information affects NDRT flow states, particularly for participants with prior driving experience, highlighting the need to reconsider in-car interface design and information presentation in Level 5 autonomous vehicles.
Application: This study offers valuable insights for optimizing NDRT experiences in fully autonomous vehicles, informing strategies for visual information control and user interface design.
Background: As Level 5 autonomous driving technology progresses, passengers are no longer required to engage in driving, allowing full focus on NDRTs. Prior research has primarily focused on Level 3 autonomous driving, examining driver handover scenarios and the necessary visual information. However, in a fully autonomous setting where no driver intervention is required, understanding the influence of visual information on NDRT engagement is essential.
Method: This study employed a Level 5 autonomous driving simulator with 27 participants performing NDRTs, specifically video watching and gaming tasks, under both conditions: with and without windshield visual information. An ANOVA analysis was conducted to evaluate the effect of visual information control on NDRT flow states.
Results: The findings showed a significant decrease in NDRT flow states when windshield visual information was blocked. Notably, participants with driving licenses experienced a pronounced impact, while those without licenses showed no significant difference in flow states between conditions.
Conclusion: The blackout of windshield visual information affects NDRT flow states, particularly for participants with prior driving experience, highlighting the need to reconsider in-car interface design and information presentation in Level 5 autonomous vehicles.
Application: This study offers valuable insights for optimizing NDRT experiences in fully autonomous vehicles, informing strategies for visual information control and user interface design.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-151-25-02-092110096