자동차안전학회지 (Journal of Auto-vehicle Safety Association)

한국자동차안전학회 (Korean Auto-vehicle Safety Association)
권호 표지
DOI QR코드

DOI QR Code

실도로 주행 데이터 기반 차선변경 주행 특성 분석

Lane Change Driving Analysis based on Road Driving Data

  • 박종철 (서울대학교 차량동역학 및 제어연구실) ;
  • 채흥석 (서울대학교 차량동역학 및 제어연구실) ;
  • 이경수 (서울대학교 차량동역학 및 제어연구실)
  • 투고 : 2018.02.01
  • 심사 : 2018.03.09
  • 발행 : 2018.03.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This paper presents an analysis on driving safety in lane change situation based on road driving data. Autonomous driving is a global trend in vehicle industry. LKAS technologies are already applied in commercial vehicle and researches about lane change maneuver have been actively studied. In autonomous vehicle, not only safety control issue but also imitating human driving maneuver is important. Driving data analysis in lane change situation has been usually dealt with ego vehicle information such as longitudinal acceleration, yaw rate, and steering angle. For this reason, developing safety index according to surrounding vehicle information based on human driving data is needed. In this research, driving data is collected from perception module using LIDAR, radar and RT-GPS sensors. By analyzing human driving pattern in lane change maneuver, safety index that considers both ego vehicle and surrounding vehicle state by using relative velocity and longitudinal clearance has been designed.

키워드

참고문헌

  1. Eidehall, A., Pohl, J., and Gustafsson, F., 2005, "A new approach to lane guidance systems", Intelligent Transportation Systems Conference, Vienna, Austria, pp. 108-112.
  2. Minoiu, N., Mammar, S., Glaser, S., and Lusetti, B., 2010, "Driver assistance system for lane departure avoidance by steering and differential braking", in 6th IFAC Symposium Advances in Automotive Control, Munich, Germany, July. 12-14, pp. 471-476.
  3. 채흥석, 임형호, 홍윤석, 이경수, 2017, "실 도로 주행 상황을 반영한 최소 안전 거리 기반 자율주행 차선 변경 알고리즘 개발", 대한기계학회 IT융합부문 2017년도 춘계학술대회, 2017.5, 133-134.
  4. Lu, Xiao-Yun, et al., 2004, "Automated vehicle merging maneuver implementation for AHS." Vehicle System Dynamics 41.2, pp. 85-107. https://doi.org/10.1076/vesd.41.2.85.26497
  5. Kachroo, Pushkin, and Zhijun Li., 1997, "Vehicle merging control design for an automated highway system." Intelligent Transportation System, 1997. ITSC'97., IEEE Conference on. IEEE.
  6. Kim, B. and. Yi, K., 2013, "Probabilistic states prediction algorithm using multi-sensor fusion and application to Smart Cruise Control systems", IEEE Intelligent Vehicles Symposium, Gold Coast, Australia, pp. 888-895.
  7. Kim, B. and. Yi, K., 2014, "Probabilistic and Holistic Prediction of Vehicle States Using Sensor Fusion for Application to Integrated Vehicle Safety Systems", IEEE Transactions on Intelligent Transportation Systems, Vol. 15, No. 5, pp. 2178-2190. https://doi.org/10.1109/TITS.2014.2312720
  8. IWG, 2017, "Proposal for amendments to Regulation No. 79 (steering equipment) Requirements applicable to ACSF of Category C1", GRRF-84-02 84th GRRF, 19-22, Agenda item 9(b).
  9. Miller, R. J. and Srinivasan, G., 2005, "Determination of Lane Change Maneuvers Using Naturalistic Driving Data", 19th International Technical Conference on the Enhanced Safety of Vehicles (ESV), Washington, D.C., No. 05-0337.
  10. Zheng, Y. and Hansen, J. H. L., 2017, "Lane-Change Detection From Steering Signal Using Spectral Segmentation and Learning-Based Classification", IEEE Transactions on intelligent vehicles, Vol. 2, No. 1.