DOI QR코드

DOI QR Code

Improved Real-Time Variable Speed Limits for a Stable Controlling of the Freeway

안정적인 고속도로 통제를 위한 향상된 실시간 가변 속도 제한

  • 전수빈 (강원대학교 컴퓨터정보통신공학과) ;
  • 한영탁 (강원대학교 컴퓨터정보통신공학과) ;
  • 서동만 (대구가톨릭대학교 컴퓨터공학과) ;
  • 정인범 (강원대학교 컴퓨터정보통신공학과)
  • Received : 2016.04.18
  • Accepted : 2016.07.01
  • Published : 2016.09.15

Abstract

Recently, many researchers have studied the VSL decision method using traffic information in multiple detector zones. However, this method selects incorrect VSL starting points, leading to the selection of the wrong speed control zone and calculation of the wrong VSL, causing traffic congestion. Eventually, the Unstable VSL system causes more congestion on the freeway. This paper proposes an improved VSL algorithm stably operated in multiple detector zones on the Korea highway. The proposed algorithm selects a preliminary VSL start station (VSS) expected to end the congestion using the acceleration of stations. It also determines the VSS at each congestion area. Finally, it calculates the VSL relative to the determined VSS and controls the vehicles that enters the traffic congestion zone. The developed strategy is compared with Real-time Variable Speed Limits for Urban Freeway (RVSL) to test the stability and efficiency of the proposed algorithm. The results show that the proposed algorithm resolves the problems of the existing algorithm, demonstrated by the correct VSS decision and the reduction of total travel time by 1-2 minutes.

최근, 다중 구역의 교통 정보를 이용한 가변 속도 제한(VSL) 결정 방법이 연구되고 있다. 하지만 부정확한 VSL 시작 구간 및 거리 계산으로 더 심각한 정체현상을 유발하고 있다. 불안정한 VSL 시스템은 결국 도로의 정체 현상을 더 악화 시키고 결국 전체적인 교통 흐름의 악화로 발전될 수 있다. 본 논문은 다중 구간에서 안정적으로 동작할 수 있는 새로운 VSL 방법을 제안한다. 본 알고리즘은 가속도를 이용하여 정체 구간의 끝 부분으로 예상되는 예비 VSL 시작 구간(VSS)을 설정하고 정체 구간별 VSS를 선정한다. 선정된 VSS를 기준으로 VSL을 계산하고 정체구간으로 진입하는 차량을 통제한다. 제안하는 방법의 안정성 및 효율성 테스트를 위해 기존 시스템과 비교 실험을 진행한다. 실험을 통하여 제안하는 방법은 정확한 VSS 선정을 통해 기존 알고리즘의 문제점을 해결 하였고 총 이동시간이 1~2분 감소한 것을 확인하였다.

Keywords

Acknowledgement

Supported by : 한국연구재단

References

  1. L. Figueiredo, I. Jesus, J. A. Tenreiro Machado, J. R. Ferreira, and J. L. Martins de Carvalho, "Towards the Development of Intelligent Transportation Systems," 2001 IEEE Intelligent Transportation Systems Conference, 2001.
  2. S. B. Jeon, E. Kwon, and I. B. Jung, "Traffic Measurement on Multiple Drive Lanes with Wireless Ultrasonic Sensors," Sensors, Vol. 14, No. 12, pp. 22891-22906, Dec. 2014. https://doi.org/10.3390/s141222891
  3. S. B. Jeon, and I. B. Jung, "Density-Based Ramp Metering Method Considering Traffic of Freeway and Ramp on ITS," Journal of KIISE: Computing Practices, Vol. 21, No. 3, pp. 223-238, Mar. 2015. (in Korean) https://doi.org/10.5626/KTCP.2015.21.3.223
  4. Y. T. Jo, Y. Kim, and I. B. Jung, "Variable Speed Limit to Improve Safety near Traffic Congestion on Urban Freeways," International Journal of Fuzzy Systems, Vol. 14, No. 2, pp. 278-288, Sep. 2012.
  5. C. Lee, B. Hellinga, and F. Saccomanno, "Evaluation of variable speed limits to improve traffic safety," Transportation Research Part C, Vol. 14, No. 3, pp. 213-288, 2006. https://doi.org/10.1016/j.trc.2006.06.002
  6. P. Allaby, B. Hellinga, and M. Bullock, "Variable Speed Limits: Safety and Operational Impacts of a Candidate Control Strategy for Freeway Applications," 2006 IEEE Intelligent Transportation Systems Conference, 2006.
  7. P. Rama, "Effects of Weather-Controlled Variable Speed Limits and Warning Signs on Driver Behavior," Transportation Research Record: Journal of the Transportation Research Board, No. 1689, pp. 53-59, 2007.
  8. I. Papamichail, K. Kampitaki, M. Papageorgiou, and A. Messmer, "Integrated Ramp Metering and Variable Speed Limit Control of Motorway Traffic Flow," Proc. of the 17th World Congress The International Federation of Automatic Control, 2008.
  9. A. Hegyi, B. De Schutter, and H. Hellendoorn, "Model Predictive Control for Optimal Coordination of Ramp Metering and Variable Speed Limits," Transportation Research Part C, Vol. 13, pp. 185-209, 2005. https://doi.org/10.1016/j.trc.2004.08.001
  10. C. M. Park, and E. Kwon, Development of Freeway Operational Strategies with IRIS-in-Loop Simulation, Minnesota Department of Transportation, Twin cities, 2012.
  11. Korea Highway Corridor Information, Korea Expressway Corporation, Gincheon, 2016. Available online: http://data.ex.co.kr (accessed on 2 June 2016).
  12. G. Gomes, A. May, and R. Horowitz, "Congested Freeway microsimulation model Using VISSIM," Transportation Research Record: Journal of the Transportations Research Board, Vol. 1876, No. 1, pp. 71-81, Jan. 2004. https://doi.org/10.3141/1876-08
  13. Y. T. Jo, and I. B. Jung, "Analysis of vehicle detection with WSN-based ultrasonic sensors," Sensors, No. 14, Vol. 8, pp. 14050-14069, Aug. 2014. https://doi.org/10.3390/s140814050
  14. S. J. Shin, C. S. Lee, Y. T. Han, S. B. Jeon, D. M. Seo, and I. B. Jung, "Calibration for Simulating a ITS Algorithm in Korea Highway," 23th KIPS Conference, No. 23, Vol. 1, pp. 443-446, Apr. 2016.
  15. Y. T. Han, C. S. Lee, S. J. Shin, S. B. Jeon, D. M. Seo, and I. B. Jung, "Traffic Analysis and Simulation System for Korea Highway," 23th KIPS Conference, No. 23, Vol. 1, pp. 447-450, Apr. 2016.