상세정보
학술지
Study on the Take-over Performance of Level 3 Autonomous Vehicles Based on Subjective Driving Tendency Questionnaires and Machine Learning Methods
- 발행일
- 202302
- 출처
- ETRI Journal, v.45 no.1, pp.75-92
- ISSN
- 1225-6463
- 출판사
- 한국전자통신연구원 (ETRI)
- 협약과제
- 20IR1400, 자율주행자동차(SAE 레벨 2,3) 기반 인적요인 심층 연구, 윤대섭
- 초록
- Level 3 autonomous vehicles require conditional autonomous driving in which autonomous and manual driving are alternately performed; whether the driver can resume manual driving within a limited time should be examined. This study investigates whether the demographics and subjective driving tendencies of drivers affect the take-over performance. We measured and analyzed the reengagement and stabilization time after a take-over request from the autonomous driving system to manual driving using a vehicle simulator that supports the driver's take-over mechanism. We discovered that the driver's reengagement and stabilization time correlated with the speeding and wild driving tendency as well as driving workload questionnaires. To verify the efficiency of subjective questionnaire information, we tested whether the driver with slow or fast reengagement and stabilization time can be detected based on machine learning techniques and obtained results. We expect to apply these results to training programs for autonomous vehicles' users and personalized human-vehicle interfaces for future autonomous vehicles.
- KSP 제안 키워드
- Autonomous driving system, Autonomous vehicle, Level 3, Machine Learning Methods, Machine Learning technique(MLT), Training programs, manual driving, stabilization time, take-over request, vehicle simulator
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