Journal of Korean Society of Transportation (대한교통학회지)

Korean Society of Transportation (대한교통학회)
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Comparison Between Travel Demand Forecasting Results by Using OD and PA Travel Patterns for Future Land Developments

장래 개발계획에 의한 추가 통행량 분석시 OD 패턴적용과 PA 패턴적용의 분석방법 비교

  • Kim, Ikki (Department of Transportation & Logistics Engineering, Hanyang University) ;
  • Park, Sang Jun (Korea Development Institute)
  • 김익기 (한양대학교 교통물류공학과) ;
  • 박상준 (한국개발연구원 공공투자관리센터)
  • Received : 2014.04.09
  • Accepted : 2015.03.24
  • Published : 2015.04.30
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Abstract

The KOTI(Korea Transport Institute) released the new version of KTDB(Korea Transport DataBase) in public. The new KTDB is different from the past KTDB in using the concept of trip generation and trip attraction instead of using the concept of Origin-Destination (OD), which was used in the past KTDB. Thus, the appropriate analysis method for future travel demand became necessary for the new type of KTDB. The method should be based on the concept of PA(Production-Attraction). This study focused on analysis of trip generation and trip distribution related to newly generated trips by future land developments. The study also described clearly the standardized forecasting process and methods with PA travel tables. The study showed that the analysis results with OD-based analysis can be different from the results with PA-based analysis in forecasting travel demand for a simple example case even though they used exactly same orignal travel data. Therefore, this study emphasized that a proper method should be applied with the new PA-based KTDB. It is necessary to prepare and disseminate guidelines of the proper forecasting method and application with PA-based travel data for practician.

한국교통연구원에서 2010년 가구통행실태조사 자료를 기초로 구축한 신규 KTDB 여객자료는 대도시권 모두에 대해 PA개념을 기반으로 통행생성과 통행유인의 통행발생량과 교통존 간의 통행량 자료를 처음으로 제공하였다. 따라서, 신규 KTDB를 활용한 장래 수요예측의 분석방법은 변화된 자료형태에 적합한 PA개념의 분석방법이 적용되어야 한다. 본 연구에서는 교통정책 분석 시 반영하게 되는 장래 개발사업에 대한 통행발생량 예측과 통행분포패턴 예측 분석에 있어 PA개념의 분석 절차를 정형화할 수 있는 방법을 명확하게 제시하고, 또한 과거의 OD기반의 분석방법이 적용될 경우 그 분석결과가 PA기반의 분석방법의 결과와 다르게 나올 수 있음을 단순 예제를 통해 증명하였다. 이와 같은 분석결과의 차이는 교통정책의 의사결정에 있어 신규 KTDB 여객자료를 활용하면서 과거의 OD기반의 분석방법이 적용될 경우 정책결정에 왜곡을 가져올 수 있음을 의미하는 것이므로, 신규 자료에 대해 적합한 분석방법이 적용되어야 함을 본 연구는 강조하였다. 또한 본 연구는 신규 KTDB 여객자료에 PA기반 분석방법이 올바로 응용 적용될 수 있도록 조속히 실무분석가들에게 분석방법 지침과 기술 보급이 필요함을 주장하였다.

Keywords

References

  1. de Dios Ortuzar J., Willumsen L. G. (2011), Modelling transport(4th edition), John Wiley & Sons.
  2. Douglas A. A., Lewis R. J. (1970), Transportation Generation Techniques: 2. Zonal Least-squares Regression Analysis, Traffic Engineering & Control, 428-431.
  3. Douglas A. A., Lewis R. J. (1971), Transportation Generation Techniques: 3. Household Least-squares Regression Analysis, Traffic Engineering & Control, 477-479.
  4. Easa S. M. (1993), Urban Trip Distribution in Practice I: Conventional Analysis, Journal of Transportation Engineering, 119(6), November/December, 793-815. https://doi.org/10.1061/(ASCE)0733-947X(1993)119:6(793)
  5. FHWA (1977), Computer Programs for Urban Transportation Planning: PLANPAC/BACKPAC General Information Manual, U.S. Department of Transportation, Federal Highway Administration.
  6. Ghareib A. H. (1996), Different Travel Patterns: Interzonal, Intrazonal, and External Trips, Journal of Transportation Engineering, 122(1), January/February, 67-75. https://doi.org/10.1061/(ASCE)0733-947X(1996)122:1(67)
  7. Goulias K. G., Pendyala R. M., Kitamura R. (1990), Practical Method for the Estimation of Trip Generation and Trip Chaining, Transportation Research Record 1285, TRB, 47-56.
  8. Jang T. Y. (2000), Establishing Trip Generation Model Based on Individual Travel Behavior, Journal of the Korean Society of Civil Engineers, 20(1-D), 39-47.
  9. Kim I.k. (1997), Theoretical Comparison of O-D Trips and P-A Trips in Travel Demand Analysis, J. Korean Soc. Transp., 15(1), Korean Society of Transportation, 45-62.
  10. Kim I.k. (2006), Reconsideration of Calibration and Forecasting Procedure for Transportation Demand Analysis, Transportation Technology and Policy, 3(1), Korean Society of Transportation, 87-106.
  11. Kim S. R., Kim J. H., Kim H. J., Chung J. H. (2012), The Trip Generation Models With Time-effects, J. Korean Soc. Transp., 30(1), Korean Society of Transportation, 103-112. https://doi.org/10.7470/jkst.2012.30.1.103
  12. Kim T. H., Rho J. H., Kim Y. I., Oh, Y. T. (2010), Development of Trip Generation Type Models toward Traffic Zone Characteristics, International journal of highway engineering, 12(4), 93-100.
  13. Korea Development Institute (2008), A Study on Roadway .Railway Part Feasibility Study Standard Guideline Supplementation and Amendment (5th Edition).
  14. KOTI (2012), Inter-regional (Passenger) Travel Demand Forecasting Ministry of Land, Infrastructure and Transport (2013), Transportation Facility Investment Evaluation Guidelines(The Preparation of the 5th) Ortuzar and Willumsen (2011), Modelling Transport, 4th Edition, John Wiley.
  15. Song J. I., Na S. W., Choo S. H. (2011), Developing Trip Generation Models Considering Land Use Characteristics, The Journal of the Korea institute of Intelligent Transport Systems, 10(6), 126-139.

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