Determination of network origin-destination demands using limited link trffic counts

Shou Ren Hu, Chang Ming Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Making valid inferences about network origin-destination (OD) demands from limited link traffic count data requires a carefully structured data collection strategy. Determination of the required number of vehicle detectors (VDs) and their installation in strategic locations for OD estimation purpose is essentially a network location problem. In the present research, an integer programming framework based on the user equilibrium assumption was developed to determine the most desirable locations for the deployment of vehicle detectors. The proposed models were evaluated under a simplified transportation network and hypothetical OD demands. Numerical results indicate that the proposed mathematical programming model framework is able to find the critical VD deployment locations for OD demand estimation purpose under limited budgetary resources. These findings can beneficially contribute to the preparation of a desirable vehicle detector deployment plan in a general transportation network.

Original languageEnglish
Title of host publication14th World Congress on Intelligent Transport Systems, ITS 2007
PublisherIntelligent Transportation Society of Japan (ITS Japan)
Pages3028-3039
Number of pages12
ISBN (Print)9781617387777
Publication statusPublished - 2007
Event14th World Congress on Intelligent Transport Systems, ITS 2007 - Beijing, China
Duration: 2007 Oct 92007 Oct 13

Publication series

Name14th World Congress on Intelligent Transport Systems, ITS 2007
Volume4

Other

Other14th World Congress on Intelligent Transport Systems, ITS 2007
Country/TerritoryChina
CityBeijing
Period07-10-0907-10-13

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Mechanical Engineering
  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Networks and Communications
  • Transportation
  • Computer Science Applications
  • Automotive Engineering

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