DOI QR코드

DOI QR Code

복수 중력모형의 구축과 적용방법에 관한 연구

A Study on the Development of Plural Gravity Models and their Application Method

  • 투고 : 2012.10.16
  • 심사 : 2013.01.23
  • 발행 : 2013.04.30

초록

본 논문에서는 중력모형의 예측 정확도 향상을 위하여 복수의 중력모형을 구축하여 적용하는 방법을 개발하였다. 개발한 방법은 결정계수($R^2$)를 이용하여 목표수준을 결정하고, 중력모형을 구축한다. 구축된 중력모형의 결정계수가 목표수준을 만족하면 모형 구축을 종료하고, 장래 통행분포 예측을 행한다. 만약 결정계수가 목표수준을 만족하지 못하면 목표수준에 만족할 때까지 구축된 모형에서 표준화 잔차가 큰 순서로 죤 페어(Zone pair)를 제거한다. 제거된 죤 페어들은 구축된 모형을 기준으로 보면 +영역과 -영역으로 나누어지는데 각 영역에서 중력모형을 구축하고 목표수준에 도달할 수 있도록 한다. 제거해야 할 죤 페어가 존재하지 않으면 모형구축 작업이 중단되고, 장래 통행분포량 예측을 한다. 사례연구에서 개발된 방법을 42개 죤페어에 적용하여 보았는데, 기존방법, 즉 하나의 중력모형으로 구축하면 설명력($R^2$)이 51.3%였으나, 개발된 방법은 3개의 중력모형을 구축하고, 설명력($R^2$)이 90% 이상되었다. 또한, 장래 예측 정확도도 기존 방법보다 월등히 높은 것으로 검정 되었다.

This study developed plural gravity models and their application method in order to increase the accuracy of trip distribution estimation. The developed method initially involves utilizing the coefficient of determination ($R^2$) to set the target level. Afterwards, the gravity model is created, and if the gravity model's coefficient of determination is satisfactory in regards to the target level, the model creation is complete and future trip distribution estimation is calculated. If the coefficient of determination is not on par with the target level, the zone pair with the largest standardized residual is removed from the model until the target level is obtained. In respect to the model, the removed zone pairs are divided into positive(+) and negative(-) sides. In each of these sides, gravity models are made until the target level is reached. If there are no more zone pairs to remove, the model making process concludes, and future trip distribution estimation is calculated. The newly developed plural gravity model and application method was adopted for 42 zone pairs as a case study. The existing method of utilizing only one gravity model exhibited a coefficient of determination value ($R^2$) of 51.3%, however, the newly developed method produced three gravity models, and exhibited a coefficient of determination value ($R^2$) of over 90%. Also, the accuracy of the future trip distribution estimation was found to be higher than the existing method.

키워드

참고문헌

  1. Celik H. Murat (2010), Sample size needed for calibrating trip distribution and behavior of the gravity model, J. Transp. Geography 18, pp.183-190. https://doi.org/10.1016/j.jtrangeo.2009.05.013
  2. Giles D. E. A., Hampton P. (1981), Interval estimation in the calibration of certain trip distribution models, Transp. Res. Part B., Vol.15B, pp.203-219.
  3. Goncalves M. B., Cursi J. E. S. (2001), Parameter estimation in a trip distribution model by random perturbation of a descent method. Transp. Res. Part B, 35, pp.137-161. https://doi.org/10.1016/S0191-2615(99)00043-0
  4. Hallefjord A., Jornsten K. (1986), Gravity models with multiple objectives theory and applications, Transp. Res. Part B, Vol.20B, pp.19-39.
  5. Kim D. O. (2001), Urban Comprehensive Transportation Plan, Hyungseul Press. Co., pp.224-227.
  6. Kim H. J. (1996), Testing Goodness of Fit of Gravity Models, J. Korean Soc. Transp., Vol.14, No.1, Korean Society of Transportation, pp.43-50.
  7. Kim T. G. (2006), Development of a Trip Distribution Model Introducing Interzonal Relative Attractiveness, Hanyang Univ.
  8. Lim S. B., Lee B. W. (1996), A Study on the Application of Gravity Model using 1990 Seoul O/D Data, J. Korean Soc. Transp., Vol.14, No.1, Korean Society of Transportation, pp.29-42.
  9. Lim Y. T. (2011), Integratrd Trip Distribution/Mode Choice Model and Sensitivity Analysis, J. Korean Soc. Transp., Vol.29, No.2, Korean Society of Transportation, pp.81-89.
  10. Ryu Y. G. (2006), Development of an Improved Gravity Model Using Residuals, J. Korean Soc. Civil. Engineers, Vol.26, 3D, pp.417-424.
  11. Yun D. S. (2008), Transportation Demand Analysis, Pakyoungsa, pp.72-139.