제어권 전환 수행 능력에 대한 최적의 정보 수준에 대한 연구Optimal Level of Information for Takeover Performance
- Other Titles
- Optimal Level of Information for Takeover Performance
- Authors
- 홍준기; 이라현; 오형석; 윤용덕; 명노해
- Issue Date
- 2020
- Publisher
- 대한인간공학회
- Keywords
- Conditionally Autonomous Driving (CAD); Takeover; Takeover Request (TOR); Information level; Takeover performance; Workload
- Citation
- 대한인간공학회지, v.39, no.3, pp.179 - 189
- Indexed
- KCI
- Journal Title
- 대한인간공학회지
- Volume
- 39
- Number
- 3
- Start Page
- 179
- End Page
- 189
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/131205
- ISSN
- 1229-1684
- Abstract
- Objective: The aim of this study is to investigate the effects of information level on takeover performance and workload in conditionally autonomous driving (CAD).
Background: Takeover Request (TOR) is important in conditionally autonomous driving (CAD) while driver must drive in certain situations. A driver receives help from the information given by the car when TOR is given. It is known that specific information helps driver more effectively than simple signals. However, information level may affect the driver's takeover performance and the workload. So, investigating takeover performance and workload in takeover situation is necessary. This paper focuses on the optimal level of information for takeover performance.
Method: To investigate the effects of information level on takeover performance and workload in CAD, an experiment on the takeover situation using a driving simulator was designed. The required information for takeover was extracted through a prior survey and the information level was distinguished. In the scenarios with six information levels, participants deal with takeovers. During the experiments, takeover performance was measured by hands-on-time and distance to obstacle, and workload was measured by DALI (Driving Activity Load Index) and PCPS (Percent Change of Pupil Size).
Results: Takeover performance was reduced when the level of information was too low or too high. The takeover time measured through hands-on-time showed no significant difference when the level is too low or too high. Takeover performance, measured by the distance to obstacles, decreased and showed a significant difference when the level is too low or too high. For subjective workload, there was no significant difference when the level is too low or too high. Subjective workload was measured by DALI. For objective workload, there was no significant difference. Objective workload was measured by PCPS.
Conclusion: Takeover performance measured by the distance to obstacles tend to decrease when the information level is too low or too high. Therefore, it is important to provide an appropriate level of information in the case of takeovers.
Application: Through this paper, providing an appropriate level of information is more effective for takeover in CAD. Therefore, it will be used to reduce risk of accidents in design of TOR displays in conditionally autonomous driving vehicles in the future.
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Collections - College of Engineering > School of Industrial and Management Engineering > 1. Journal Articles
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