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.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2019.4
- 수록면
- 61 - 71 (11page)
- DOI
- 10.5143/JESK.2019.38.2.61
이용수
초록· 키워드
오류제보하기
Objective: The aim of this study is to investigate the effects of Takeover Request Lead Time (TORlt) to Driver Workload in conditionally autonomous driving (CAD).
Background: Takeover request (TOR) is important issue in conditionally autonomous driving. A human driver must be ready to take control of the vehicle when TOR is given. However, driver could be underload when autonomous driving lasts for a long time or be overload if NDRT (Non-driving related task) is highly demanding or TOR appears suddenly. Therefore, investigating driver workload in takeover situation is essential. This paper focuses on effects of TORlt to driver workload.
Method: To investigate effects of TORlt to driver workload in CAD, experiment were conducted on the takeover situation through a driving simulator. Experiment were conducted on 7 levels of TORlt (3, 7, 10, 15, 30, 45, 60s) and ghost session. Also, the participants performed NDRT to assume CAD. During the experiments, subjective and physiological workload was measured by DALI (Driving Activity Load Index) and respiration rate respectively.
Results: TORlt has a large effect on driver workload. When TORlt was 3 seconds, the subjective and objective workload was the highest. As TORlt increases, both of workload decreases. For subjective workload, there was a slight increase in workload when TORlt was long, but it was not statistically significant. For physiological workload, the workload continued to decline, but there was no statistically significant difference for longer TORlt In addition, there was a significant positive correlation between subjective workload and physiological workload. Therefore, subjective workload can be replaced by physiological workload in takeover situation.
Conclusion: As TORlt increases, the driver workload decreases, but the difference is not significant if TORlt was long. Also, subjective workload measurement could be replaced by measuring physiological signals.
Application: Through this paper, it has been found that physiological measure could be an alternative for measuring workload in autonomous vehicle. Therefore, in autonomous vehicles, sensors that measure physiological signals will be installed to determine the driver`s workload.
Background: Takeover request (TOR) is important issue in conditionally autonomous driving. A human driver must be ready to take control of the vehicle when TOR is given. However, driver could be underload when autonomous driving lasts for a long time or be overload if NDRT (Non-driving related task) is highly demanding or TOR appears suddenly. Therefore, investigating driver workload in takeover situation is essential. This paper focuses on effects of TORlt to driver workload.
Method: To investigate effects of TORlt to driver workload in CAD, experiment were conducted on the takeover situation through a driving simulator. Experiment were conducted on 7 levels of TORlt (3, 7, 10, 15, 30, 45, 60s) and ghost session. Also, the participants performed NDRT to assume CAD. During the experiments, subjective and physiological workload was measured by DALI (Driving Activity Load Index) and respiration rate respectively.
Results: TORlt has a large effect on driver workload. When TORlt was 3 seconds, the subjective and objective workload was the highest. As TORlt increases, both of workload decreases. For subjective workload, there was a slight increase in workload when TORlt was long, but it was not statistically significant. For physiological workload, the workload continued to decline, but there was no statistically significant difference for longer TORlt In addition, there was a significant positive correlation between subjective workload and physiological workload. Therefore, subjective workload can be replaced by physiological workload in takeover situation.
Conclusion: As TORlt increases, the driver workload decreases, but the difference is not significant if TORlt was long. Also, subjective workload measurement could be replaced by measuring physiological signals.
Application: Through this paper, it has been found that physiological measure could be an alternative for measuring workload in autonomous vehicle. Therefore, in autonomous vehicles, sensors that measure physiological signals will be installed to determine the driver`s workload.
목차
1. Introduction
2. Method
3. Results
4. Discussion
5. Conclusion
References
참고문헌 (30)
참고문헌 신청
Borojeni, S. S. / 2017 / Comparing Shape-Changing and Vibro-Tactile Steering Wheels for Take-Over Requests in Highly Automated Driving / Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications :221~225
Brookhuis, K. A. / 2001 / Stress, workload and fatigue / Lawrence Erlbaum :321~333
De Waard, D / 1996 / The measurement of drivers' mental workload
De Winter, J. C. / 2014 / Effects of adaptive cruise control and highly automated driving on workload and situation awareness: A review of the empirical evidence / Transportation research part F: traffic psychology and behaviour 27:196~217
Endsley, M. R. / 1995 / The out-of-the-loop performance problem and level of control in automation / Human Factors 37(2):381~394
Brookhuis, K. A. / 2001 / Stress, workload and fatigue / Lawrence Erlbaum :321~333
De Waard, D / 1996 / The measurement of drivers' mental workload
De Winter, J. C. / 2014 / Effects of adaptive cruise control and highly automated driving on workload and situation awareness: A review of the empirical evidence / Transportation research part F: traffic psychology and behaviour 27:196~217
Endsley, M. R. / 1995 / The out-of-the-loop performance problem and level of control in automation / Human Factors 37(2):381~394
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UCI(KEPA) : I410-ECN-0101-2019-530-000667038