Estimation of an urban OD matrix using different information sources

Asma Sbaï, Henk J. Van Zuylen, Jie Li*, Fang Fang Zheng, Fattehallah Ghadi

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

5 Citations (Scopus)

Abstract

An Origin Destination matrix for urban trips is more difficult to develop than for interurban long and medium distance trips. The socio-economic characteristics are valuable parameters to estimate trip attractions and destinations, but often the distance does not have a significant effect on the distribution of urban trips. Since the 1980s methods are developed to estimate the trip matrix from traffic volumes. The problem is underdetermined: the information in the OD matrix is more than the information contained in the traffic volumes. Nowadays there are more information sources like probe vehicles, Automated Number Plate Recognition cameras, mobile phone data etc. This article discusses the possibilities and limitations of these additional information sources. Use is made of traffic data collected in Changsha, a town in middle-south China.

Original languageEnglish
Title of host publicationComputational Science and Its Applications - ICCSA 2017 - 17th International Conference, 2017
PublisherSpringer
Pages183-198
Number of pages16
Volume10405
ISBN (Print)9783319623948
DOIs
Publication statusPublished - 1 Jan 2017
Event17th International Conference on Computational Science and Its Applications, ICCSA 2017 - Trieste, Italy
Duration: 3 Jul 20176 Jul 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10405
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Computational Science and Its Applications, ICCSA 2017
CountryItaly
CityTrieste
Period3/07/176/07/17

Keywords

  • Destination matrix
  • Information minimization
  • Origin
  • Probe vehicles
  • Urban traffic

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