Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Urban Network Travel Time Prediction via Online Multi-Output Gaussian Process Regression
KTH, School of Architecture and the Built Environment (ABE), Transport Science.
KTH, School of Architecture and the Built Environment (ABE), Transport Science.
Linkoping Univ, Div Stat & Machine Learning, SE-58183 Linkoping, Sweden..
2017 (English)In: 2017 IEEE 20TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), IEEE , 2017Conference paper, Published paper (Refereed)
Abstract [en]

The paper explores the potential of Multi-Output Gaussian Processes to tackle network-wide travel time prediction in an urban area. Forecasting in this context is challenging due to the complexity of the traffic network, noisy data and unexpected events. We build on recent methods to develop an online model that can be trained in seconds by relying on prior network dependences through a coregionalized covariance. The accuracy of the proposed model outperforms historical means and other simpler methods on a network of 47 streets in Stockholm, by using probe data from GPS-equipped taxis. Results show how traffic speeds are dependent on the historical correlations, and how prediction accuracy can be improved by relying on prior information while using a very limited amount of current-day observations, which allows for the development of models with low estimation times and high responsiveness.

Place, publisher, year, edition, pages
IEEE , 2017.
Series
IEEE International Conference on Intelligent Transportation Systems-ITSC, ISSN 2153-0009
National Category
Civil Engineering
Identifiers
URN: urn:nbn:se:kth:diva-230880DOI: 10.1109/ITSC.2017.8317796ISI: 000432373000201Scopus ID: 2-s2.0-85046289474ISBN: 978-1-5386-1526-3 OAI: oai:DiVA.org:kth-230880DiVA, id: diva2:1219823
Conference
20th IEEE International Conference on Intelligent Transportation Systems (ITSC), OCT 16-19, 2017, Yokohama, JAPAN
Note

QC 20180618

Available from: 2018-06-18 Created: 2018-06-18 Last updated: 2018-06-19Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Jenelius, Erik
By organisation
Transport Science
Civil Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf