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Seoul activity-based Model: An Application of Feathers Solutions to Seoul Metropolitan Area
Author(s) -
Won Do Lee,
SungJin Cho,
Tom Bellemans,
Davy Janssens,
Geert Wets,
Keechoo Choi,
ChangHyeon Joh
Publication year - 2012
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2012.06.109
Subject(s) - metropolitan area , computer science , flemish , scale (ratio) , schedule , dimension (graph theory) , operations research , population , transport engineering , geography , cartography , archaeology , demography , mathematics , sociology , pure mathematics , engineering , operating system
As a study area, Seoul metropolitan area in Korea, where has been experiencing transportation problems including congestions and emissions, currently needs an alternative policy measure at the individual level, instead of large scale infrastructure constructions. Even though some researches based on an activity-based approach dealing with an individual travel behavior have been conducted in Korea, none of them used a simulation framework. Considering a genuine activity-based transportation demand forecast, there is no better option but to introduce the activity-based simulation framework. Among several activity-based simulation frameworks, Feathers will indeed be applied into the study area because it is the most viable and suitable simulation platform for that area in terms of a similar spatial dimension. Although, the application for the study area is possible on Feathers, there are potential problems, including the prohibition of using individual and household data in census, an inconsistent administrative unit in Korea and inappropriate Flemish figures and patterns for the study area. To overcome these problems, IPF for synthesizing population and a comparative study of Flemish and the study area will be applied in this study. Moreover, we plan to integrate an agent-based model with the TDM research in order to complement the activity-based model by predicting an adapted daily schedule to an individual circumstance

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