Journal of Korean Society of Transportation (대한교통학회지)

Korean Society of Transportation (대한교통학회)
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Compensation and Amendment of Highway Travel Demand Forecasting

고속도로 교통수요 보정모형에 관한 고찰

  • Lee, Eui-Jun (The SMART Highway R&D Center, Korea Expressway Corporation) ;
  • Kim, Young-Sun (Department of Civil and Transportation Engineering, Ajou University) ;
  • Yi, Yong-Ju (Department of Civil and Transportation Engineering, Ajou University) ;
  • OH, Young-Tae (Department of Transportation Systems Engineering, Ajou University) ;
  • Choi, Keechoo (Department of Transportation Systems Engineering, Ajou University) ;
  • Yu, Jeong Whon (Department of Transportation Systems Engineering, Ajou University)
  • 이의준 (한국도로공사 스마트하이웨이사업단) ;
  • 김영선 (아주대학교 일반대학원 건설교통공학과) ;
  • 이용주 (아주대학교 일반대학원 건설교통공학과) ;
  • 오영태 (아주대학교 교통시스템공학과) ;
  • 최기주 (아주대학교 교통시스템공학과) ;
  • 유정훈 (아주대학교 교통시스템공학과)
  • Received : 2013.01.10
  • Accepted : 2013.04.30
  • Published : 2013.06.30
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Abstract

In this study, a model of compensation and amendment of forecasted travel demand was developed to calculate the range of values depends on the changes in the risk factors, selecting factors that might affect traffic demand changes among risk factors. Selected factors are as follows: influenced area population, the number of registrated vehicle per person, ratio of service industry workers, and city intervals. Then this model is applied to six routes of expressway and the calculated value were compensated with error rate being reflected on each quartile value with respect to influenced area population (200,000 people standards). Result from appling developed model to Cheongwon-Sangju expressway suggests that the model could compensate the error rate by more than 50%, which in turn validate the effectiveness of the model developed. Some limitations and future research agenda have also been identified.

본 연구에서는 장래 교통수요의 변화에 영향을 주는 요인을 위험요인으로 선정하여, 위험요인 변화에 따라 달라지는 수요예측 값의 범위를 제시할 수 있는 교통수요 보정모형을 개발하였다. 장래 교통수요의 변화에 영향을 주는 요인으로 영향권인구, 1인당 자동차 등록대수, 3차산업종사자 비율, 도시간격 등이 선정되었고, 이를 바탕으로 수요예측의 오차율을 산정하는 모형을 개발하였다. 6개의 고속도로 노선에 모형을 적용하여 대상구간의 영향권 인구(20만명 기준)에 따라 각각 다른 사분위값을 반영하여 교통수요예측 결과의 오차율을 산정하여 수요예측을 보정하였다. 개발된 모형을 청원-상주 고속도로에 적용해 본 결과, 교통량 오차율의 차이를 50% 이상 보정 가능한 것으로 분석되어 본 연구를 통해 개발된 모형이 효과가 있음을 검증하였다. 또한 논문의 말미에 본 연구의 한계와 논문의 향후 연구과제에 대해서도 논하였다.

Keywords

References

  1. Bovy P. H. L., Jansen G. R. M. (1983), Network Aggregation Effects upon Equilibrium Assignmnet Outcomes : An Empirical Investigation, Transportation Science, Vol.17, No.3, pp.240-262. https://doi.org/10.1287/trsc.17.3.240
  2. Boyce D. E., Janson B. N., Eash R. W. (1981), The Effect on Equilibrium Trip Assignment of Different Link Congestion Functions, Transportation Research Part A, Vol.15, No.3, pp.223-232. https://doi.org/10.1016/0191-2607(81)90003-0
  3. Cervero R., Hansen M. (2002), Induced Travel Demand and Induced Road Investment : A Simultaneous Equation Analysis, Journal of Transport Economics and Policy, Vol.36, No.3, pp.469-490.
  4. Chung I. H., Oh S. H. (2005), Enhancement of Reliability for Traffic Demand Estimation: Focusing on Interval Estimation Model for Traffic Demand (통행수요 추정의 신뢰수준 제고 방안 연구: 구간 통행수요 모형 개발을 중심으로), Korea Research Institute for Human Settlements.
  5. Chung S. B., Chang S. E. (2007), Demand Forecasting Errors in Road Projects: Causes and Effects (도로 사업의 수요예측 오차발생 원인 및 영향분석), The Korea Transport Institute.
  6. Dargay J., Goodwin P., Hanly M. (2002), Development of an Aggregated Transport Forecasting Model, Centre for Transport Studies, University College London.
  7. Flyvbjerg B. (2005), Measuring Inaccuracy in Travel Demand Forecasting: Methodological Considerations Regarding Ramp Up and Sampling, Transportation Research Part A, Vol.39, No.6, pp.522-530.
  8. Flyvbjerg B., Skamris Holm M. K., Buhl S. L. (2006), Inaccuracy in Traffic Forecasts, Transport Reviews, Vol.26, No.1, pp.1-24. https://doi.org/10.1080/01441640500124779
  9. Fulton L. M., Noland R. B., Meszler D. J., Thomas J. V. (2000), A Statistical Analysis of Induced Travel Effects in the U.S. Mid-Atlantic Region, Journal of Transportation and Statistics, Vol.3, No.1, pp.1-14.
  10. Guo J. Y., Bhat C. R. (2004), Modifiable Areal Units: Problem or Perception in Modeling of Residential Location Choice?, Transportation Research Record, Vol.1898, pp.138-147. https://doi.org/10.3141/1898-17
  11. Hansen M., Huang Y. (1997), Road Supply and Traffic in California Urban Areas, Transportation Research Part A, Vol.31, No.3, pp.205-218.
  12. Kim K. W. (2007), Rationalization for Decision-making on SOC Investment: Risk Analysis of Estimated Road Link Traffic Flow (SOC 투자의사결정 합리 화 방안: 도로부문 교통량 추정위험 분석을 중심으로), KDI.
  13. Lee H. K., Yun I. S. (2007), 교통수요 예측의 한계 및 신뢰도 제고방안, The Korea Transport Institute, The Korea Transport Institute, Monthly KOTI Magazine on Transport, Vol.117, pp.60-67.
  14. Lim Y. T., Baek S. G. (2007), 교통수요 예측 관련 규제 제도의 진단과 보완방향, The Korea Transport Institute, Monthly KOTI Magazine on Transport, Vol.117, pp.56-59.
  15. Ministry of Land, Transport and Maritime Affairs (2011), 공공교통시설사업 투자평가지침(제4차개정).
  16. Shim J. K. et al. (1999), The Analysis of Social and Economic Effects of Highway Construction in Korea (고속도로 노선별 사업효과 분석(사회.경제분 야)), Korea Expressway Corporation.