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Prediction of arterial travel time considering delay in vehicle re-identification
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
KTH, School of Information and Communication Technology (ICT).
KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.ORCID iD: 0000-0002-1375-9054
2016 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Travel time is important information for management and planning of road traffic. In the past decades, automated vehicle identifi- cation (AVI) systems have been deployed in many cities for collecting reliable travel time data. The fast technology advance has made the budget cost of such data collection system much cheaper than before. For example, bluetooth and WiFi-based systems have become economically a more feasible way for collecting interval travel time information in urban area. Due to increasing availability of such type of data, this paper aims to develop a travel time prediction approach that may take into account both online and historical measurements. Indeed, a statistical prediction approach for real-time application is proposed, modeling the deviation of live travel time from historical distribution estimated per time interval. An extended Kalman Filter (EKF) based algorithm is implemented to combine online travel time with historical patterns. In particular, the system delay due to vehicle re-identification is considered in the algorithm development. The methods are evaluated using Automated Number Plate Recognition (ANPR) data collected in Stockholm. The results show that the prediction performance is good and reliable in capturing major trends during congestion buildup and dissipation. 

Place, publisher, year, edition, pages
Elsevier, 2016.
Keyword [en]
Travel time, real-time prediction, Automated Vehicle Identification, extended Kalman filter, data fusion, historical percentiles
National Category
Transport Systems and Logistics Information Systems
Identifiers
URN: urn:nbn:se:kth:diva-201672OAI: oai:DiVA.org:kth-201672DiVA: diva2:1073909
Conference
19th EURO Working Group on Transportation Meeting, EWGT2016, 5-7 September Istanbul, Turkey
Funder
Integrated Transport Research Lab (ITRL)Swedish Transport Administration
Note

QC 20170320

Available from: 2017-02-13 Created: 2017-02-13 Last updated: 2018-01-13Bibliographically approved

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fulltext(477 kB)35 downloads
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Other links

http://ewgt2016.itu.edu.tr/

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CiteExportLink to record
Permanent link

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