KSCE Journal of Civil and Environmental Engineering Research (대한토목학회논문집)

Korean Society of Civil Engeneers (대한토목학회)
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Development of Incident Detection Method for Interrupted Traffic Flow by Using Latin Square Analysis

라틴방격분석법을 이용한 단속류도로에서의 유고감지기법 개발

  • 모무기 ((주)엠케이이엔지) ;
  • 김형진 (연세대학교 도시공학과) ;
  • 손봉수 (연세대학교 도시공학과) ;
  • 김대훈 ((주)평화엔지니어링 교통계획부)
  • Received : 2007.09.18
  • Accepted : 2011.06.03
  • Published : 2011.10.31
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Abstract

In this study, a new method which can detect incidents in interrupted traffic flow was suggested. The applied method of detecting the incident is the Latin Square Analysis Method by using traffic traits. In the Latin Square Analysis, unlike other previously tried methods, the traffic situation was analyzed, this time considering the changes in traffic traits for each lane and for each time period. The data used in this study were the data observed in the actual field with fine weather. The traffic volumes, the vehicle speed and the occupancy rate were collected on the interrupted flow road. The data were collected in normal and incident situations. The incidents occurred on the second lane, the time of persistent incidents was set to 10 minutes. The Latin Square Analyses were performed using the collected data with the traffic volume, with the vehicle speed or with the occupancy rate. As a result in this study, in case of detecting the traffic situations with Latin Square Analysis, it will be more successful to apply traffic volume to detect the traffic situations than to apply other factors.

본 연구에서는 단속류 도로에서의 유고상황을 감지할 수 있는 새로운 유고감지기법을 제시하였다. 유고감지를 위하여 적용된 방법은 교통특성들을 이용한 라틴방격(Latin Square)분석법이다. 라틴방격분석법을 이용하여 기존 연구사례에서 시도했던 방법과는 다르게 차로별, 시간대별 교통특성의 변화를 분석하여 유고상황을 감지하였다. 사용된 교통특성자료는 맑은 기상상태에서 정상운영시 또는 유고발생시 관측된 교통량, 속도, 점유율 자료이며, 유고시 자료는 2차로에서 10분간 유고가 발생했었던 자료이다. 정상운영시 및 유고발생시에 대한 교통상황을 감지하기 위하여 교통량, 속도 및 점유율 등을 기준으로 각각 라틴방격분석을 시행했다. 분석결과, 라틴방격분석을 이용하여 교통상황을 감지하는 경우, 교통량을 기준으로 교통상황을 감지하는 것이 다른 교통특성을 기준으로 교통상황을 감지하는 것보다 감지능력이 우수한 것으로 나타났다.

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References

  1. 송서일(2001) 실험계획법, 한경사
  2. 장석환(2002) 실험계획과 응용, 교우사
  3. 황준환(2000) 간선도로 돌발상황 검지기법 개발연구, 박사학위논문, 서울시립대학교
  4. Bell, M. G. H. and Thancanamootoo, B. (1988) Automatic incident detection within urban traffic control systems, Proceedings of the Roads and Traffic 2000 Conference, Vol. 4, No. 2, pp. 35- 38.
  5. Bretherton, R. D. and Bowen, G. T. (1991) Incident detection and traffic monitoring in urban areas, Advanced telematics in road transport, Vol. 1, pp. 740-751.
  6. Cullip, M. J. and Hall, F. L. (1997) Incident detection on an arterial roadway, Transportation Research Record 1603, TRB, pp. 112-118.
  7. Han, Lee D. and May, Adolf D. (1989) Artificial intelligence approaches for urban network incident detection and control, Proceedings of the Engineering Foundation Conference on Traffic Control Methods, pp. 159-176.
  8. Lee,Sibok and Krammes, Raymond A. and Yen, John (1998) Fuzzy-logic-based incident detection for signalized diamond inter -changes, Transportation Research Part C, Vol. 6, No. 5- 6, pp. 359-377. https://doi.org/10.1016/S0968-090X(99)00004-2
  9. Sermons, M. William and Koppelman, Frank S. (1996) Use of vehicle positioning data for arterial incident detection, Transportation Research Part C, Vol. 4, No. 2, pp. 87-96. https://doi.org/10.1016/0968-090X(96)00003-4
  10. Sethi, Vaneet and Bhandari, Nikhil and Koppelman, and Schofer, Joseph L. (1995) Arterial incident detection using fixed detector and probe vehicle data, Transportation Research Part C, Vol. 3, No. 2, pp. 99-112. https://doi.org/10.1016/0968-090X(94)00017-Y
  11. Stephanedes, Yorgos J. and Vassilakis, George (1994) Intersection Incident Detection For IVHS, 74th Annual Meeting of the Transportation Research Board.