File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1061/(ASCE)0733-947X(2009)135:9(658)
- Scopus: eid_2-s2.0-69249196057
- WOS: WOS:000269062200008
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Multivariate traffic forecasting technique using cell transmission model and SARIMA model
Title | Multivariate traffic forecasting technique using cell transmission model and SARIMA model | ||||
---|---|---|---|---|---|
Authors | |||||
Keywords | Data collections Forecasting Intersections Seasonal variations Traffic flow Traffic models | ||||
Issue Date | 2009 | ||||
Publisher | American Society of Civil Engineers. The Journal's web site is located at http://www.pubs.asce.org/journals/te.html | ||||
Citation | Journal Of Transportation Engineering, 2009, v. 135 n. 9, p. 658-667 How to Cite? | ||||
Abstract | The paper develops a short-term space-time traffic flow forecasting strategy integrating the empirical-based seasonal autoregressive integrated moving average (SARIMA) time-series forecasting technique with the theoretical-based first-order macroscopic traffic flow model-cell transmission model. A case study in Dublin city center which has serious traffic congestion is performed to test the effectiveness of the proposed multivariate traffic forecasting strategy. The results show that the forecasts at the junctions only deviate around 10% at a maximum from the original observations and seem to indicate that the proposed strategy is one of the effective approaches to predict the real-time traffic flow level in a congested network especially at the locations where no continuous data collection takes place. © 2009 ASCE. | ||||
Persistent Identifier | http://hdl.handle.net/10722/91218 | ||||
ISSN | 2018 Impact Factor: 1.520 2020 SCImago Journal Rankings: 0.571 | ||||
ISI Accession Number ID |
Funding Information: This research is jointly sponsored by the start-up grant (Grant No. R-264-000-229-112) from the National University of Singapore and the Program for Research in Third-Level Institutions (PRTLI) administered by the Irish Higher Education Authority. The writers are grateful for the constructive comments of the referees and editors. | ||||
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Szeto, WY | en_HK |
dc.contributor.author | Ghosh, B | en_HK |
dc.contributor.author | Basu, B | en_HK |
dc.contributor.author | O'Mahony, M | en_HK |
dc.date.accessioned | 2010-09-17T10:15:04Z | - |
dc.date.available | 2010-09-17T10:15:04Z | - |
dc.date.issued | 2009 | en_HK |
dc.identifier.citation | Journal Of Transportation Engineering, 2009, v. 135 n. 9, p. 658-667 | en_HK |
dc.identifier.issn | 0733-947X | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/91218 | - |
dc.description.abstract | The paper develops a short-term space-time traffic flow forecasting strategy integrating the empirical-based seasonal autoregressive integrated moving average (SARIMA) time-series forecasting technique with the theoretical-based first-order macroscopic traffic flow model-cell transmission model. A case study in Dublin city center which has serious traffic congestion is performed to test the effectiveness of the proposed multivariate traffic forecasting strategy. The results show that the forecasts at the junctions only deviate around 10% at a maximum from the original observations and seem to indicate that the proposed strategy is one of the effective approaches to predict the real-time traffic flow level in a congested network especially at the locations where no continuous data collection takes place. © 2009 ASCE. | en_HK |
dc.language | eng | en_HK |
dc.publisher | American Society of Civil Engineers. The Journal's web site is located at http://www.pubs.asce.org/journals/te.html | en_HK |
dc.relation.ispartof | Journal of Transportation Engineering | en_HK |
dc.subject | Data collections | en_HK |
dc.subject | Forecasting | en_HK |
dc.subject | Intersections | en_HK |
dc.subject | Seasonal variations | en_HK |
dc.subject | Traffic flow | en_HK |
dc.subject | Traffic models | en_HK |
dc.title | Multivariate traffic forecasting technique using cell transmission model and SARIMA model | en_HK |
dc.type | Article | en_HK |
dc.identifier.email | Szeto, WY:ceszeto@hku.hk | en_HK |
dc.identifier.authority | Szeto, WY=rp01377 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1061/(ASCE)0733-947X(2009)135:9(658) | en_HK |
dc.identifier.scopus | eid_2-s2.0-69249196057 | en_HK |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-69249196057&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 135 | en_HK |
dc.identifier.issue | 9 | en_HK |
dc.identifier.spage | 658 | en_HK |
dc.identifier.epage | 667 | en_HK |
dc.identifier.isi | WOS:000269062200008 | - |
dc.publisher.place | United States | en_HK |
dc.identifier.scopusauthorid | Szeto, WY=7003652508 | en_HK |
dc.identifier.scopusauthorid | Ghosh, B=15925454400 | en_HK |
dc.identifier.scopusauthorid | Basu, B=36027501000 | en_HK |
dc.identifier.scopusauthorid | O'Mahony, M=7102575274 | en_HK |
dc.identifier.issnl | 0733-947X | - |