Exploration on origin-destination-based travel time variability: Insights from Seoul metropolitan area
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim Sung Hoo | - |
dc.contributor.author | Chung Jin-Hyuk | - |
dc.date.accessioned | 2022-10-25T06:43:05Z | - |
dc.date.available | 2022-10-25T06:43:05Z | - |
dc.date.created | 2022-09-10 | - |
dc.date.issued | 2018-06 | - |
dc.identifier.issn | 0966-6923 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/111098 | - |
dc.description.abstract | Travel time variability can be defined as the variation in travel time over a certain time period. This study focuses on O/D-based analysis, which has been rarely studied due to the limited data in the context of travel time variability. The objectives of the study are twofold: to shed light on the O/D-based travel time variability and to get insights on travel time variability in the context of Seoul Metropolitan Area. This study utilizes the web information to obtain real-time estimated travel time data, and employs a Gaussian mixture model (GMM) to model the travel time distributions. The GMM parameters are found to be useful to fit travel time distribution, which exhibits skewness and multimodality, to identify underlying travel time states and to explain variability. The results indicate that O/D-based travel time variability can be characterized and that higher variability occurs during peak hours. In general, the selected O/D pairs are found to have four travel time states but exhibit different patterns. The existence of alternative paths seem to reduce travel time variability at the O/D level. The results suggest directions for future research and implementation of policies. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Pergamon Press Ltd. | - |
dc.title | Exploration on origin-destination-based travel time variability: Insights from Seoul metropolitan area | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim Sung Hoo | - |
dc.identifier.doi | 10.1016/j.jtrangeo.2018.05.021 | - |
dc.identifier.scopusid | 2-s2.0-85048194897 | - |
dc.identifier.wosid | 000442708300011 | - |
dc.identifier.bibliographicCitation | Journal of Transport Geography, v.70, pp.104 - 113 | - |
dc.relation.isPartOf | Journal of Transport Geography | - |
dc.citation.title | Journal of Transport Geography | - |
dc.citation.volume | 70 | - |
dc.citation.startPage | 104 | - |
dc.citation.endPage | 113 | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Business & Economics | - |
dc.relation.journalResearchArea | Geography | - |
dc.relation.journalResearchArea | Transportation | - |
dc.relation.journalWebOfScienceCategory | Economics | - |
dc.relation.journalWebOfScienceCategory | Geography | - |
dc.relation.journalWebOfScienceCategory | Transportation | - |
dc.subject.keywordPlus | RELIABILITY-MEASURES | - |
dc.subject.keywordPlus | TRAFFIC NETWORK | - |
dc.subject.keywordPlus | URBAN NETWORKS | - |
dc.subject.keywordPlus | TRANSPORT | - |
dc.subject.keywordPlus | ISSUES | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordAuthor | Origin-destination-based analysis | - |
dc.subject.keywordAuthor | Travel time distribution | - |
dc.subject.keywordAuthor | Travel time variability | - |
dc.subject.keywordAuthor | Urban mobility | - |
dc.subject.keywordAuthor | Web information | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0966692317305483 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.