DOI QR코드

DOI QR Code

상습지체구간 결정을 위한 일관성 서비스지수(CSI) 개발

Development of Consistency Service Index for Deciding Habitual Congestion Section

  • 이기영 (한국도로공사 도로교통연구원) ;
  • 최기주 (아주대학교 교통시스템공학과) ;
  • 손범수 (한국도로공사 경기지역본부) ;
  • 김형곤 (남경 E&C) ;
  • 이숭봉 (한국도로공사 도로교통연구원)
  • 투고 : 2013.09.04
  • 심사 : 2013.09.29
  • 발행 : 2013.10.15

초록

PURPOSES : In order to do an improving countermeasures for congestion on the highway with a limited budget, it is very important to select a habitual congestion section effectively. This study is develop CSI(Consitency Service Index) which contained the service for drivers on the highway to select a habitual congestion section. METHODS : By applying the concept of service for the users paying a fee, proposed CSI(Consistency Service Index) to determine habitual delay. CSI is mean that users using the highway road must be provided an environment which can driving more than 80kph, anytime, anywhere. RESULTS : The result applying developed method in this study included most of congestion sections selected by conventional method. but, in some section of existing non-congestion section were included by CSI. The annual average speed and CSI correlation analysis result was high correlation. This result proved that CSI was reflecting road traffic condition well. CONCLUSIONS : It was verified practicality from the delay section of gyeonggi-do area highway. we can judge whether or not to be a habitual congestion in the specific highway and do the traffic improving countermeasures accordingly.

키워드

참고문헌

  1. Bok K. C., Lee S. J., Choi Y. H., Kang J. G., Lee S. H., 2009. Development of a Traffic Condition Index (TCI) on Expressways, J. Korean Soc. Transp., Vol. 27 No. 5, Korean Society of Transportation, 85-95) (복기찬, 이승준, 최윤혁, 강정규, 이승환, 2009. 고속도로 소통 상태지수 개발에 관한 연구, 대한교통학회, Vol. 27, No. 5, 85-95)
  2. California Department of Transportation Division of Research & Innovation, 2004. Transportation System Impacts Cross- cutting Evaluation Report.
  3. CAMPO, 2004. Congestion management system(CMS) state of the system report.
  4. Hwang S. K, 2002. Development of Urban Congestion Index for Economic Congestion Estimation(1 step). (황상규, 2002. 도시교통혼잡지표의 개발 및 활용방안 1단계, 한국교통연구원)
  5. Jo J. H., Han J. H., Kim S. H., Lee B. S., 2006. The Selection of Optimal Probability Distribution and Estimaion forDesign Hourly Factor in National Highway Roads, J. Korean Soc. Transp., Vol. 24, No. 6, Korean Society of Transportation, 33-43. (조준환, 한종현, 김성호, 이병생, 2006. 일반국도 설계시간계수의 적정 확률분포 선정 및 추정, 대한교통학회지, Vol. 24, No. 6, 33-43)
  6. Kim H. G. 2013. Development of Speed and Speed Forecasting Model for Selecting the Freeway Recurring Congested Section, Master Thesis. (김형곤, 2013. 고속도로 상습 지체구간 선정을 위한 지체판단 속도 산정 및 추정모형 개발, 한양대학교 박사학위 논문)
  7. Lee S. G., 1997. A Study on the Development of Road Congestion Index, KRIHS, 33-57. (이상건, 1997. 도로교통 혼잡지표 개발에 관한 연구, 국토개발연구원, 33-57)
  8. Lee S. J., 2006. Development of Traffic Operating Condition Audit Technique on Freeways, Expressway & transportation research Institute. (이승준, 2006. 고속도로 교통소통진단기법 개발, 한국도로공사 도로교통연구원)
  9. Lo HK, Tung YK, 2003. Network with degra-dable links: Capacity analysis and design, Transportation Research Part B, 37, 45-363.
  10. Ministry of Land., 2013. Highway Capacity Manual. (국토교통부, 2013. 도로용량편람)
  11. Moon M. K., Jang M. S., Kang J. S., 2003. A study on improvement of the DDHV estimating method, J. Korean Soc. Transp., Vol. 21, No. 5, Korean Society of Transportation, 61-71. (문미경, 장명순, 강재수, 2003. 설계시간교통량 산정방법 개선, 대한교통학회지 Vol. 21, No. 5 61-71)
  12. NCHRP, 1997. Quantifying congestion: user's guide, NCHRP Report 398 Vol. 2.
  13. Satish C. Sharma, Pawan Lingras, 1999. Neural networks as alternative to traditional factor approach of annual average daily traffic estimation from traffic counts, TRR1660, 24-31
  14. S.C. Sharma, Y. Wu, S.N. Rizak, 1995. Determination of DDHV from directional traffic flows, Journal of Transportation Engineering, Vol. 121, No. 4, 369-375. https://doi.org/10.1061/(ASCE)0733-947X(1995)121:4(369)
  15. Texas Transportation Institute, 2004. Monitoring Urban Freeways in 2003 : Current Conditions and Trends from Archived Operations Data.
  16. Transportation Research Board, 2001. Freeway performance measurement system : mining loop detector data.