Estimation of Adjustment Coefficients to Improve Accuracy of Predictions of Inter-zonal Trips

?????? ???????????? 4?????? ??? ???????????? ????????? ???????????? ???????????? ????????? ????????? ?????? ??????·???????????? ?????? ?????? ??????????????? ???????????? ????????????. ????????? ???????????? ??????????????? ????????????(Gravity model)??? ?????? ????????????. ??????????????? ??????????????? ??? ??? ????????????(travel costs)?????? ??????????????? ???????????? ?????? ???????????? ????????????, ?????? ???????????? ??????????????? ?????????????????? ????????? ???e??? ?????? ??????. ?????????, ??????????????? ??????????????? ??? ??? ??? ??????????????? ????????? ????????????????????????????????? ???????????? ?????? ??? ?????? ???????????? ??????????????????????????? ????????? ??? ????????? ????????? ????????? ????????? ??????. ?????? ??????, ??????????????? ???????????? ???????????? ??? ??????????????? ?????????(predictions)??? ???????????? ????????????(??????, ??????, ??????, ??????)?????? ?????? ????????????(??????, ?????????, ???e)?????? ???????????? ????????? ?????????????????? ????????? ?????????, ????????? ?????? ?????????????????????. ????????? ?????? ????????? ???????????? ???????????? ???????????? ?????? ???????????? ???????????? ??????. ?????? ?????????????????? ????????? ????????? ??? ?????? ?????? ????????? ?????? ????????? ???????????? ????????? ????????????. ????????? ???????????? ???????????? ?????? ?????? ???????????????????????? ??????. ????????? ?????? ????????? ????????? ???, ????????? ??? ?????? ????????????????????? ???????????? ?????? ???????????? ????????? ?????? ?????????(forecasts)??????????????? ???????????????. ????????? ?????? ?????? ???????????? ???????????? ????????? ?????? ????????? ??????????????????????????? ??????????????? ???????????? ???????????? ?????? ?????????. ?????? ????????? ???????????????????????? ?????? ??????????????? ??? ?????? ?????? ????????? ????????? ????????????????????? ????????? ?????? ??????. ????????? ??? ????????? ??? ??? ?????? ???????????? ????????????????????? ?????? ????????? ???????????? ?????? ???????????? ??? ????????????????????? ????????? ?????? ???????????? ???????????? ??????????????? ??????????????? ??????. ??? ??? ?????? ?????????????????????????????? ????????? ?????? ????????? ‘????????????(adjustment coefficients)’?????? ????????????. ??? ??????????????? ??? ??? ??????????????? ????????? ??? ??? ???????????????????????? ???, ?????? ???????????? ?????????????????? ????????????????????? ??????????????? ?????? ????????? ???????????? ??????????????? ??? ??????????????? ???????????? ???????????? ???????????? ?????????????????? ??????. ??? ???????????? ??????????????? ???????????? ?????? ????????? ???????????? ????????? ??????????????? ?????????. ????????? ??? ????????? ????????? ???????????? ???????????? ?????????????????? ???????????? ??????, ??????????????? ???????????? ???????????? ????????? ????????????, ?????? ?????? ??????????????? ???????????? ????????? ?????? ?????? ???????????? ????????? ??? ??????????????? ????????????, ?????? ???????????? ?????? ???????????? ???????????? ????????? ??????????????? ?????? ?????? ???????????? ??????. ?????? ?????? ??? ??????????????? ?????? ????????? ??????????????? 3??? ?????? ??????????????? ????????? K-factor?????? ?????? ?????? ??? ???????????? ??????????????? ????????? ?????? ???????????? ??????. The gravity model is the most widely used trip distribution model. This model is based on the assumption that the travel cost is inversely proportional. However, the gravity model has limitations for predicting inter-zonal trips in accuracy and reliability. In previous studies to complement these limitations, some methods applying factors to adjust predictions into observations are applicable. However previous studies still have some limitations in terms of implementation of the model for forecasting inter-zonal trips of target years. In this study, not only socio-economic variables used in the previous studies but variables related to spatial structure within a city and transportation services in each zone are introduced in inter-zonal trips. Adjustment coefficients are estimated by multiple regression analysis methods. Variables such as Residential Density, Accessibility of Subway, Accessibility of Highway were significant. The results of calibration are tested and checked in respect to the appropriateness and applicability. Comparing to the predictions from the traditional gravity model, the models suggested in this paper show improved results. Applying adjustment coefficients for each zone-pair reduced RMSEs in 9% and SE in 16%.This study is a part of the research project(Grant No. 09-TSIP-I06) sponsored by KICTTEP(Korea Institute of Construction & Transportation Technology Evaluation and Planning). The financial support is gratefully acknowledged