Citation

Kwon, Hyug, Lee， Man-Hyung, 김남경. J. Transp. Res. (Seoul) 2022; 29(1): 29-41.

Vernacular Title

딥러닝을 이용한 민자도로 교통수요예측 위험 추정에 관한 연구

Copyright

(Copyright © 2022, Korea Transport Institute)

DOI

10.34143/JTR.2022.29.1.29

PMID

unavailable

Abstract

BTO Public-Private Partnership(PPPs) is exposed to various risks. In particular, demand risk, which is an uncertainty in predicting traffic demand, leads to profitability of private projects and acts as the most important risk. It can be said that the main problem in PPP Projects is due to demand risk. There is a limit to reducing the error in predicting traffic demand, which predicts movement based on human behavior. This study developed a model for estimating traffic demand prediction errors through Deep learning by constructing variables related to traffic demand prediction errors.

Language: ko