Issues in Feathers Application in the Seoul Metropolitan Area

Issues in Feathers Application in the Seoul Metropolitan Area

Won Do Lee (Kyung Hee University, Korea), Chang-Hyeon Joh (Kyung Hee University, Korea), Sungjin Cho (Hasselt University, Belgium) and Bruno Kochan (Hasselt University, Belgium)
Copyright: © 2014 |Pages: 15
DOI: 10.4018/978-1-4666-4920-0.ch004
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Abstract

Over the last decades, the trip-based approach, also known as the four-step model, has been playing an unrivaled role in transportation demand research in Korea. It has been used to predict changes in traffic volume resulting from new transportation policy measures, and also has allowed conducting benefit-cost analyses for new infrastructure provisions. It has been increasingly difficult for the trip-based model to anticipate individual responses to new transportation policy inputs and infrastructure provision as the society becomes personalized and diversified. Activity-Based Modeling (ABM) approaches, predicting travel demand derived from individual activity participations, were introduced to complement the trip-based approach in this regard. The chapter introduces the Seoul ABM project that aims to first apply FEATHERS as an ABM to the data collected in Seoul Metropolitan Area (SMA) and then develop a prototype of the ABM framework for Korea. More specifically, the chapter first briefly describes SMA in comparison with Flanders in Belgium and other countries. It then introduces related research works in Korea and the background of the Seoul ABM project. After these, a FEATHERS framework applied for the Seoul ABM project is described with its data requirements. Major issues of and solutions to the Seoul ABM project are then discussed with regard to the data preprocessing. The chapter ends with a summary and future work.
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Study Area

The SMA consists of three local governments, including Seoul, Inchon and Gyeonggi with 23,836,272 inhabitants (49% of the population in Korea). Metropolitan Transportation Authority (MTA) organizes the metropolitan transportation planning, and Korea Transportation Institute (KOTI) collects for MTA the network data from local governments and their institutions. The recent household travel survey was conducted in 2010 in the SMA, to collect household activity-travel data involving 665,801 respondents (2.79% of the population in SMA). Table 1 shows descriptive statistics of the survey data.

Table 1.
Activity-travel behavior in household travel survey in SMA (Lee, et al., 2012)
Overall Indicator
trip frequency2.51
transfer frequency0.06
travel time (min)84.04
transfer time (min)0.51
travel distance (km)13.73
inner-trip chain frequency1.91
outer-trip chain frequency0.54
Travel Mode (%)
walk31.6
car23.5
passenger7.8
local-line bus3.8
main-line bus10.7
inter-city bus3.1
metro/train12.5
taxi0.9
motorbike0.7
bike2.1
etc.3.4
Trip Purpose
pickup1.0
back home45.7
go to work19.5
go to school11.8
go to private education5.3
business4.1
shopping2.8
leisure3.7
etc.6.1

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