Browse > Article
http://dx.doi.org/10.22680/kasa2021.13.1.038

Driving behavior Analysis to Verify the Criteria of a Driver Monitoring System in a Conditional Autonomous Vehicle - Part I -  

Son, Joonwoo (대구경북과학기술원)
Park, Myoungouk (대구경북과학기술원)
Publication Information
Journal of Auto-vehicle Safety Association / v.13, no.1, 2021 , pp. 38-44 More about this Journal
Abstract
This study aimed to verify the criteria of the driver monitoring systems proposed by UNECE ACSF informal working group and the ministry of land, infrastructure, and transport of South Korea using driving behavior data. In order to verify the criteria, we investigated the safety regulations of driver monitoring systems in a conditional autonomous vehicle and found that the driver monitoring measures were related to eye blinks times, head movements, and eye closed duration. Thus, we took two different experimental data including real-world driving and simulator-based drowsy driving behaviors in previous studies. The real-world driving data were used for analyzing blink times and head movement intervals, and the drowsiness data were used for eye closed duration. In the real-world driving study, 52 drivers drove approximately 11.0 km of rural road (about 20 min), 7.9 km of urban road (about 25 min), and 20.8 km of highway (about 20 min). The results suggested that the appropriate number of blinks during the last 60 seconds was 4 times, and the head movement interval was 35 seconds. The results from drowsy driving data will be presented in another paper - part 2.
Keywords
Driver monitoring system; Autonomous driving; Motor vehicle safety regulations; Blinks; Head movements;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Son, J., Park, M., 2021, "The Effects of Distraction Type and Difficulty On Older Drivers' Performance and Behaviour: Visual vs. Cognitive", International Journal of Automotive Technology, In press.
2 Son, J., Park, M., 2020, "Chapter 6. Intelligent Vehicles and Older drivers", In Olaverri-Monreal, C., Garcia-Fernandez, F., and Rossetti, R.J.F. (Eds.), Human Factors in Intelligent Vehicles, River Publishers.
3 Son, J., Park, M., Park, B. B., 2015, "The effect of age, gender and roadway environment on the acceptance and effectiveness of Advanced Driver Assistance Systems", Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 31, pp. 12~24.   DOI
4 Seeing Machines, 2008, FaceLAB4 User Manual, Canberra, Australia.
5 Son, J., Park, M., 2017, "Situation awareness and transitions in highly automated driving a framework and mini-review". J Ergonomics Vol. 7, No. 212.
6 Casner, S. M., Hutchins, E. L., Norman, D., 2016, "The challenges of partially automated driving". Communications of the ACM, Vol. 59, No. 5, pp. 70~77.   DOI
7 UNECE, Transport-Vehicle Regulations, Automatically Commanded Steering Function (ACSF), Retrieved from https://wiki.unece.org/ display/trans/ACSF+23rd+session.
8 국토교통부, 2020, 자동차 및 자동차부품의 성능과 기준에 관한 규칙-별표27 부분 자율주행시스템의 안전기준, Retrieved from https://www.law.go.kr/법령/자동차및자동차부품의성능과기준에관한규칙.
9 박명옥, 손준우, 2021, "부분 자율주행자동차의 운전자 모니터링 시스템 안전기준 검증을 위한 실도로 운전 행동 분석 -2부-", 자동차안전학회지, In press.
10 Veltman, J. A., Gaillard, A. W. K., 1998, "Physiological workload reactions to increasing levels of task difficulty", Ergonomics, Vol. 41, No. 5, pp. 656~669.   DOI
11 Son, J., Lee, Y., Kim, M. H., 2011, "Impact of traffic environment and cognitive workload on older drivers' behavior in simulated driving", International Journal of Precision Engineering and Manufacturing, Vol. 12, No. 1, pp. 135~141.   DOI
12 Son, J., Park, M., 2013, "The Impact of Cognitive Workload on Driving Performance and Visual Attention in Younger and Older Drivers", The Korea Society of Automotive Engineers, Vol. 21, No. 4, pp. 62~69.   DOI
13 Lu, Z., Happee, R., Cabrall, C. D., Kyriakidis, M., de Winter, J. C., 2016, "Human factors of transitions in automated driving: A general framework and literature survey", Transportation research part F: traffic psychology and behaviour, Vol. 43, pp. 183~198.   DOI
14 Dingus, T. A., Klauer, S. G., Neale, V. L., Petersen, A., Lee, S. E., Sudweeks, J., et al., 2006, The 100-car naturalistic driving study, Phase II-Results of the 100-car field experiment (Report No. HS-810 593). Washington, DC: National Highway Traffic Safety Administration.
15 Kuehn, M., Hummel, T., Bende, J., 2009, "Benefit estimation of Advanced Driver Assistance Systems for cars derived from real-life accidents", In 21st International Technical Conference on the Enhanced Safety of Vehicles (EVS), Vol. 15.
16 SAE International, 2018, "Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-road Motor Vehicles", Standard No. J3016.
17 Endsley, M. R., Kiris, E. O., 1995, "The out-of-the-loop performance problem and level of control in automation", Human Factors: The Journal of the Human Factors and Ergonomics Society, Vol. 37, No. 2, pp. 381~394.   DOI