화물수요모형 개선을 위한 통행저항함수 추정
Deterrence Function Estimation for Improvement of Freight Demand Model
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초록
기존 물동량 기반 화물수요모형에서 활용되고 있는 품목별 통행저항함수는 단일 함수 형태이기 때문에, 품목별 상이한 특성을 반영하지 못하는 한계가 있다. 또한 물동량 기반 화물수요모형을 통하여 추정되는 화물자동차 O/D는 물동량 분포 추이를 따르기 때문에, 화물자동차의 통행특성을 고려하지 못하는 문제가 있다. 따라서 본 연구에서는 국내 화물수요모형의 통행분포 단계를 개선하기 위하여 화물 품목별 및 화물자동차 톤급별 통행특성을 검토하고, 각각의 특성을 반영할 수 있는 통행저항함수를 추정하였다. 총 30개 화물 품목에 대한 통행저항함수를 추정한 결과 대부분 역멱함수 형태가 통계적 설명력이 가장 높은 것으로 나타났으며, 화물자동차의 경우는 소형과 중·대형간 통행특성 차이가 두드러지는 것으로 나타났다. 또한 추정된 계수는 모두 통계적 유의미성을 확보하는 것으로 나타났다.
Abstract
Freight demand analysis in Korea is based on a commodity-based freight demand model, and a gravity model by a commodity as freight distribution model is used. The deterrence function in a gravity model, however, takes the same form for different commodities, thus the travel characteristics of the various commodities is unrealistically reflected. In addition, a truck trip O/D converted from a commodity ton O/D of the commodity-based freight demand model does not fully reflect the distribution characteristics of freight vehicles, since distribution pattern of a commodity O/D does not correctly reflect that of truck trip O/D. Accordingly, to improve the existing freight distribution model based on commodity, the trip distribution characteristics are analyzed and deterrence functions that reflect the characteristics are estimated by commodity and truck type. As a result, it is proven that the inverse power functional form is most appropriate for 30 out of 33 commodities. Moreover, for trucks, there is a large difference among small, middle and large trucks. The deterrence functions estimated by commodity and truck type is appear to be statistically significant at the 0.05 significance level.
참고문헌 (19)
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