Number and location of sensors for real-time network traffic estimation and prediction: Sensitivity analysis

Stacy M. Eisenman, Xiang Fei, Xuesong Zhou, Hani S. Mahmassani

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

48 Scopus citations


Installing and maintaining sensors in a transportation network can be expensive. The motivation for this research is finding the best way to deploy finite resources and generate a network detection system in a manner that produces minimal estimation errors. The analysis uses a simulation-based real-time network traffic estimation and prediction system based on dynamic traffic assignment (DTA) methodology to analyze different levels of detection and different sensor locations in a portion of the Chesapeake Highway Advisories Routing Traffic (CHART) network (between Washington, D.C., and Baltimore, Maryland). This study provides a conceptual framework of the sensor location problem and a theoretical description of the objectives associated with the sensor location problem. A sensitivity analysis of the estimation and prediction quality with the DYNASMART-X real-time DTA system in relation to sensor number and location is conducted in the Maryland CHART network. The analysis considers both randomly generated location scenarios and scenarios based on engineering judgment The analysis reveals the importance of providing detection in specific locations of the network and the dependence of the value of additional detection on the specific location selected.

Original languageEnglish (US)
Title of host publicationNetwork Modeling 2006
PublisherNational Research Council
Number of pages7
ISBN (Print)0309099730, 9780309099738
StatePublished - 2006
Externally publishedYes

Publication series

NameTransportation Research Record
ISSN (Print)0361-1981

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering


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