MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Accelerated on-line calibration of dynamic traffic assignment using distributed stochastic gradient approximation

Author(s)
Huang, Enyang; Antoniou, Constantinos; Lopes, Jorge Alves; Wen, Yang, Ph. D. Massachusetts Institute of Technology; Ben-Akiva, Moshe E
Thumbnail
DownloadBen-Akiva_Accelerated on-line.pdf (526.4Kb)
PUBLISHER_POLICY

Publisher Policy

Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.

Terms of use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Metadata
Show full item record
Abstract
Dynamic Traffic Assignment (DTA) system [Ben-Akiva et al., 1991] [Mahmassani, 2001] benefits travelers by providing accurate estimate of current traffic conditions, consistent anticipatory network information as well as reliable route guidance. Over the years, two types of model adjustment schemes have been studied - DTA off-line calibration [Balakrishna, 2006] [Toledo et al., 2003] [van der Zijpp, 1997] and DTA on-line calibration [Antoniou et al., 2007] [Wang et al., 2007] [Ashok and Ben-Akiva, 2000]. The on-line calibration of DTA system allows real-time model self-corrections and has proven to be a useful complement to off-line calibration. In this paper, we explore distributed gradient calculations for the speed-up of on-line calibration of Dynamic Traffic Assignment (DTA) systems. Extended Kalman Filter (EKF) and Stochastic Gradient Descent (GD) are examined and their corresponding distributed versions (Para-EKF and Para-GD) are proposed. A case study is performed on a 25-km expressway in Western Portugal. We empirically show that the application of distributed gradient calculation significantly reduce the computational time of on-line calibration and thus provide attractive alternatives for speed-critical real-time DTA systems.
Date issued
2010-09
URI
http://hdl.handle.net/1721.1/77566
Department
Massachusetts Institute of Technology. Center for Transportation & Logistics; Massachusetts Institute of Technology. Department of Civil and Environmental Engineering; Massachusetts Institute of Technology. Intelligent Transportation Systems Laboratory
Journal
Proceedings of the 2010 13th International IEEE Annual Conference on Intelligent Transportation Systems (ITSC)
Publisher
Institute of Electrical and Electronics Engineers
Citation
Huang, Enyang et al. “Accelerated On-line Calibration of Dynamic Traffic Assignment Using Distributed Stochastic Gradient Approximation.” 2010 13th International IEEE Conference on Intelligent Transportation Systems (ITSC), Madeira Island, Portugal, September 19-22, 2010, IEEE, 2010. 1166–1171. CrossRef. Web. © 2010 IEEE.
Version: Final published version
Other identifiers
INSPEC Accession Number: 11639450
ISBN
978-1-4244-7657-2
ISSN
2153-0009

Collections
  • MIT Open Access Articles

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.