The Journal of The Korea Institute of Intelligent Transport Systems (한국ITS학회 논문지)

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
권호 표지
DOI QR코드

DOI QR Code

Analyzing the Impact of Changes in the Driving Environmenton the Stabilization Time of Take-over in Conditional Automation

조건부 자율주행시 주행환경 변화에 따른 제어권 전환 안정화 시간 영향 분석

  • Sungho Park (Center for Convergence and open Sharing, Ajou University) ;
  • Kyeongjin Lee (Dept. of D.N.A. Convergence, Major in Transportation Eng., Ajou University) ;
  • Jungeun Yoon (Dept. of D.N.A. Convergence, Major in Transportation Eng., Ajou University) ;
  • Yejin Kim (Dept. of D.N.A. Convergence, Major in Transportation Eng., Ajou University) ;
  • Ilsoo Yun (Dept. of Transportation System Eng., Ajou University)
  • 박성호 (아주대학교 혁신융합사업단) ;
  • 이경진 (아주대학교 D.N.A.플러스융합학과 교통공학전공) ;
  • 윤정은 (아주대학교 D.N.A.플러스융합학과 교통공학전공) ;
  • 김예진 (아주대학교 D.N.A.플러스융합학과 교통공학전공) ;
  • 윤일수 (아주대학교 교통시스템공학과)
  • Received : 2023.11.20
  • Accepted : 2023.12.15
  • Published : 2023.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

The stabilization time of take-over refers to the time it takes for driving to stabilize after the take-over. Following a take-over request from an automated driving system, the driver must become aware of the road driving environment and perform manual driving, making it crucial to clearly understand the relationship between the driving environment and stabilization time of take-over. However, previous studies specifically focusing on stabilization time after take-over are rare, and research considering the driving environment is also lacking. To address this, our study conducted experiments using a driving simulator to observe take-over transitions. The results were analyzed using a liner mixed model to quantitatively identify the driving environment factors affecting the stabilization time of take-over. Additionally, coefficients for stabilization time based on each influencing factor were derived.

제어권 전환 안정화 시간(Stabilization time of take-over)은 제어권 전환 이후 운전이 안정화 될 때까지의 시간을 의미한다. 자율주행시스템(autonomated driving system)의 제어권 전환 요청(take-over request) 직후, 운전자는 도로의 주행환경을 인지하고 수동운전을 수행해야하기 때문에 주행환경과 제어권 전환 안정화 시간의 관계를 명확히 규명하는 것은 매우 중요하다. 반면, 제어권 전환 안정화 시간에 대해 특정하여 수행된 기존 연구는 드물었으며, 주행환경을 고려한 연구도 부족한 실정이다. 이 점에 기인하여 본 연구는 드라이빙 시뮬레이터를 활용한 제어권 전환 실험을 수행하고, 실험 결과를 선형혼합모형(linear mixed model)을 통해 분석하여 제어권 전환 안정화 시간에 영향을 미치는 주행환경 요소를 정량적으로 도출하였으며, 각 영향요인에 따른 제어권 전환 안정화 계수를 도출하였다.

Keywords

Acknowledgement

이 논문은 국토교통부 및 국토교통과학기술진흥원의 연구비지원(RS-2022-00142239)에 의해 수행되었습니다. 본 논문은 박성호의 박사학위논문에 게재되었던 내용을 수정·보완하여 작성하였습니다.

References

  1. Barisic, A., Sigrist, P., Oliver, S., Sciarra, A. and Winckler, M.(2023), "Driver model for Take-Over-Request in autonomous vehicles", Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, pp.317-324.
  2. Diggle, P., Diggle, P. J., Heagerty, P., Liang, K. and Zeger, S.(2002), Analysis of Longitudinal Data, Oxford University Press.
  3. Garson, G. D.(2019), Multilevel Modeling: Applications in STATA®, IBM® SPSS®, SAS®, R and HLMTM, Sage Publications.
  4. Gomes, G. D., Flynn, R. and Murray, N.(2022), "Continuous-time feedback device to enhance situation awareness during take-over requests in automated driving conditions", Proceedings of the 13th ACM Multimedia Systems Conference, pp.319-323.
  5. Huang, G. and Pitts, B. J.(2022), "The effects of age and physical exercise on multimodal signal responses: Implications for semi-autonomous vehicle takeover requests", Applied Ergonomics, vol. 98, p.103595.
  6. Kang, Y.(2011), Exploration of Optimal Statistical Methods to Analyze Longitudinal Data with Missing Values for Clinical Research Involving Knee Arthroplasty, Master's Thesis, Dankook University Graduate School.
  7. Kim, H., Kim, W., Kim, J., Lee, S. J., Yoon, D. and Jo, J.(2021), "A study on re-engagement and stabilization time on take-over transition in a highly automated driving system", Electronics, vol. 10, no. 3, p.344.
  8. Korber, M., Gold, C., Lechner, D. and Bengler, K.(2016), "The influence of age on the take-over of vehicle control in highly automated driving", Transportation Research. Part F, Traffic Psychology and Behaviour, vol. 39, pp.19-32. https://doi.org/10.1016/j.trf.2016.03.002
  9. Lee, K., Park, S., Park, G., Park, J. and Yun, I.(2022), "Analysis of Factors Affecting the Take-over Time of Automated vehicles Using a Meta-analysis", The Journal of The Korea Institute of Intelligent Transportation Systems, vol. 21, no. 4, pp.167-189. https://doi.org/10.12815/kits.2022.21.4.167
  10. Lee, S.(2019), Association between handgrip strength and cognitive function in the elderly: Korean longitudinal study of aging (2006-2016), Doctoral Dissertation, Yonsei University Graduate School of Public Health.
  11. Lim, J.(2019), "The Monthly Status of the International Vehicle Regulations in UNECE," Auto Journal, vol. 41, no. 5, pp.47-51.
  12. Ministry of Land, Transport and Maritime Affairs(2013), Korea Highway Capacity Manual, pp.12-53.
  13. Noh, Y.(2016), "A Comparison Study on Statistical Modeling Methods", Journal of the Korea Academia-Industrial Cooperation Society, vol. 17, no. 5, pp.645-652. https://doi.org/10.5762/KAIS.2016.17.5.645
  14. Park, S., Jeong, H., Kim, K. H. and Yun, I.(2018), "Development of Safety Evaluation Scenario for Autonomous Vehicle Take-over at Expressways", The Journal of the Korea Institute of Intelligent Transportation Systems, vol. 17, no. 2, pp.142-151. https://doi.org/10.12815/kits.2018.17.2.142
  15. Park, S., Jeong, H., Kwon, C., Kim, J. and Yun, I.(2019), "Analysis of Take-over Time and Stabilization of Autonomous Vehicle Using a Driving Simulator", The Journal of The Korea Institute of Intelligent Transportation Systems, vol. 18, no. 4, pp.31-43. https://doi.org/10.12815/kits.2019.18.4.31
  16. Park, S., Yun, Y., Ko H., Jeong, H. and Yun, I.(2020), "Analysis of the influence of Road Traffic conditions and weather on the take-over of a conditional autonomous vehicle", The Journal of The Korea Institute of Intelligent Transportation Systems, vol. 19, no. 6, pp.235-249. https://doi.org/10.12815/kits.2020.19.6.235
  17. SAE International(2021), Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles, pp.1-32.
  18. Shek, D. T. and Ma, C.(2011), "Longitudinal data analyses using linear mixed models in SPSS: Concepts, procedures and illustrations", The Scientific World JOURNAL, vol. 11, pp.42-76. https://doi.org/10.1100/tsw.2011.2
  19. So, J. J., Park, S., Kim, J., Park, J. and Yun, I.(2021), "Investigating the impacts of road traffic conditions and driver's characteristics on automated vehicle takeover time and quality using a driving simulator", Journal of Advanced Transportation, vol. 2021, pp.1-13. https://doi.org/10.1155/2021/8859553
  20. United Nations Economic Commission for Europe(UNECE)(2022), Proposal for the 01 series of amendments to UN Regulation No. 157(Automated Lane Keeping System), Economic and Social Council, pp.1-32.
  21. Wandtner, B., Schmidt, G., Schoemig, N. and Kunde, W.(2018), "Non-driving related tasks in highly automated driving-effects of task modalities and cognitive workload on take-over performance", AmE 2018-Automotive Meets Electronics; 9th GMM-Symposium, VDE, pp.1-6.
  22. Zeeb, K., Buchner, A. and Schrauf, M.(2016), "Is take-over time all that matters? The impact of visual-cognitive load on driver take-over quality after conditionally automated driving", Accident Analysis and Prevention, vol. 92, pp.230-239. https://doi.org/10.1016/j.aap.2016.04.002
  23. Zhang, B., De Winter, J., Varotto, S., Happee, R. and Martens, M.(2019), "Determinants of take-over time from automated driving: A meta-analysis of 129 studies", Transportation Research Part F: Traffic Psychology and Behaviour, vol. 64, pp.285-307. https://doi.org/10.1016/j.trf.2019.04.020