Hybrid model for motorway travel time estimation considering increased detector spacing

Ashish Bhaskar, Ming Qu, Edward Chung

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review

6 Citations (Scopus)

Abstract

Travel time estimation and prediction on motorways has long been a topic of research. Prediction modeling generally assumes that the estimation is perfect. However good the modeling, errors in estimation can significantly weaken the accuracy and reliability of the prediction. Models have been proposed for estimating travel time from loop detector data. Generally, detectors are closely spaced (say, 5(M) m), and travel time can be estimated accurately. However, detectors are not always perfect, and even during normal running conditions a few detectors malfunction, with a resultant increase in the spacing between functional detectors. Under such conditions, an error in the travel time estimation is significant and generally unacceptable. This research evaluated the in-practice travel time estimation models during various traffic conditions. Existing models fail to estimate travel time accurately under large detector spacing and during shoulder congestion periods. To address this issue, an innovative hybrid model that considered loop data for travel time estimation w as proposed. The model was tested with simulation and was validated with real Bluetooth data from the Pacific Motorway in Brisbane, Queensland, Australia. Results indicate that during non-free-flow conditions and larger detector spacing, the proposed model provides significant improvement in the accuracy of travel time estimation.

Original languageEnglish
Title of host publicationTransportation Research Record
PublisherNational Research Council
Pages71-84
Number of pages14
ISBN (Electronic)9780309295321
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes

Publication series

NameTransportation Research Record
Volume2442
ISSN (Print)0361-1981

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering

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