Network Origin-Destination Demand Estimation using Limited Link Traffic Counts: Strategic Deployment of Vehicle Detectors through an Integrated Corridor Management Framework

In typical road traffic corridors, freeway systems are generally well-equipped with traffic surveillance systems such as vehicle detector (VD) and/or closed circuit television (CCTV) systems in order to gather timely traffic information for traffic control and/or management purposes. However, other highway facilities in the corridor, especially arterials and surface streets in the vicinity of the freeway, mostly lack detector/sensor systems. Yet, most traffic management and control methods/frameworks in the literature assume the availability of time-dependent traffic measures (such as counts, flows, speeds, etc.) on all links of the corridor. Hence, there is a critical disconnect between the practical reality and methodological expectations in terms of detection capabilities. This research seeks to develop a mechanism to strategically deploy vehicle detectors to infer network origin-destination (O-D) demands using limited link traffic count data. It leads to the problem of the identification of “optimal” locations for installing detectors so that maximum system observability is achieved with a limited monetary budget. From an integration standpoint, it addresses the question of where to locate detectors on the non-freeway facilities so that, in conjunction with the installed detectors on freeways, the entire corridor can be managed effectively by obtaining the maximum possible accurate information on traffic conditions. The primary goal of the first stage of this project is to address the network sensor location problem (NSLP) directly so as to obtain the unobserved link flows given the minimum subset of observed link flows provided by passive counting sensors.

  • Record URL:
  • Supplemental Notes:
    • This document is disseminated under the sponsorship of the Department of Transportation, University Transportation Centers Program.
  • Corporate Authors:

    NEXTRANS

    Purdue University
    3000 Kent Avenue
    Lafayette, IN  United States  47906-1075

    Research and Innovative Technology Administration

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Authors:
    • Peeta, Srinivas
    • Hu, Shou-Ren
    • Chu, Chun-Hsiao
    • Liou, Han-Tsung
  • Publication Date: 2009-10-15

Language

  • English

Media Info

  • Media Type: Print
  • Edition: Final Report
  • Features: Figures; References; Tables;
  • Pagination: 60p

Subject/Index Terms

Filing Info

  • Accession Number: 01149527
  • Record Type: Publication
  • Report/Paper Numbers: NEXTRANS Project No. 018PY01
  • Contract Numbers: DTRT07-G-005 (Grant)
  • Files: UTC, TRIS, USDOT
  • Created Date: Jan 20 2010 11:21AM