IDEAS home Printed from https://ideas.repec.org/a/taf/transp/v28y2005i5p315-339.html
   My bibliography  Save this article

Evaluation of the Transferability of Incident Detection Algorithms Developed for Singapore Expressways

Author

Listed:
  • Chin Long Mak
  • Henry S.L. Fan

Abstract

Two new detection algorithms, single-station DV (dual-variable) and dual-station CODE (COmbined Detector Evaluation) were developed earlier using 160 incidents collected along Singapore's Central Expressway (CTE). The transferability of these CTE-developed algorithms is assessed, as a case study, using 100 incidents collected from the Tullamarine Freeway and South Eastern Freeway in Melbourne, Australia. The investigation covers the differences in traffic detector systems (loop detectors versus video-based), road geometry and behaviour between drivers in Singapore and Australia. The re-calibrated application of these algorithms to freeways in Melbourne yielded a reasonably good detection performance as well as satisfying the average expected performances of seven traffic management centres surveyed in the USA. The results suggested that the detection logic of the algorithms developed for CTE possessed reasonably good transferability and are also suitable for receiving traffic inputs from video-based detectors as well as from loop detectors.

Suggested Citation

  • Chin Long Mak & Henry S.L. Fan, 2005. "Evaluation of the Transferability of Incident Detection Algorithms Developed for Singapore Expressways," Transportation Planning and Technology, Taylor & Francis Journals, vol. 28(5), pages 315-339, August.
  • Handle: RePEc:taf:transp:v:28:y:2005:i:5:p:315-339
    DOI: 10.1080/03081060500319686
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03081060500319686
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03081060500319686?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Abdulhai, Baher, 1996. "A Neuro-Genetic-Based Universally Transferable Freeway Incident Detection Framework," University of California Transportation Center, Working Papers qt3q93f0jp, University of California Transportation Center.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Abdulhai, Baher & Porwal, Himanshu & Recker, Will, 1999. "Short Term Freeway Traffic Flow Prediction Using Genetically-Optimized Time-Delay-Based Neural Networks," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt4t05p2mp, Institute of Transportation Studies, UC Berkeley.
    2. Abdulhai, Baher & Ritchie, Stephen G. & Iyer, Mahadevan, 1999. "Implementation of Advanced Techniques for Automated Freeway Incident Detection," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3r3366br, Institute of Transportation Studies, UC Berkeley.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:transp:v:28:y:2005:i:5:p:315-339. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/GTPT20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.