IDEAS home Printed from https://ideas.repec.org/p/cdl/itsrrp/qt5h70x5j9.html
   My bibliography  Save this paper

Estimation of Truck Traffic Volume from Single Loop Detectors Using Lane-to-Lane Speed Correlation

Author

Listed:
  • Kwon, Jaimyoung
  • Varaiya, Pravin
  • Skabardonis, Alexander

Abstract

An algorithm for real time estimation of truck traffic in multi-lane freeway is proposed. The algorithm uses data from single loop detectors-the most widely installed surveillance technology for urban freeways in the US. The algorithm works for those freeway locations that have a truck-free lane, and exhibit high lane-to-lane speed correlation. These conditions are met by most urban freeway locations. The algorithm produces real time estimates of the truck traffic volumes at the location. It can also be used to produce alternative estimate of the mean effective vehicle length, which can improve speed estimates from single loop detector data. The algorithm is tested with real freeway data and produces estimates of truck traffic volumes with only 5.7% error. It also captures the daily patterns of truck traffic and mean effective vehicle length. Applied to loop data on I-710 near Long Beach during the dockworkers lockout October 1-9, 2002, the algorithm finds a 32 % reduction in 5-axle truck volume.

Suggested Citation

  • Kwon, Jaimyoung & Varaiya, Pravin & Skabardonis, Alexander, 2003. "Estimation of Truck Traffic Volume from Single Loop Detectors Using Lane-to-Lane Speed Correlation," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt5h70x5j9, Institute of Transportation Studies, UC Berkeley.
    • Handle: RePEc:cdl:itsrrp:qt5h70x5j9
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/5h70x5j9.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Varaiya, Pravin, 2004. "Assessment of MeMS Sensors in an Urban Traffic Environment," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt82p3t7gx, Institute of Transportation Studies, UC Berkeley.
    2. Xing, Jiping & Wu, Wei & Cheng, Qixiu & Liu, Ronghui, 2022. "Traffic state estimation of urban road networks by multi-source data fusion: Review and new insights," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 595(C).
    3. Cheung, Sing Yiu & Coleri, Sinem & Dundar, Baris & Ganesh, Sumitra & Tan, Chin-Woo & Varaiya, Pravin, 2004. "Traffic Measurement and Vehicle Classification with a Single Magnetic Sensor," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt2gv111tv, Institute of Transportation Studies, UC Berkeley.
    4. Chen Feng Ng & Elaine F. Frey, 2013. "The recession and truck traffic on the Long Beach Freeway in Los Angeles," Economics Bulletin, AccessEcon, vol. 33(4), pages 2518-2527.
    5. Chow, Andy H.F. & Lu, Xiao-Yun & Qiu, Tony Z., 2009. "Empirical Analysis of Traffic Breakdown Probability Distribution with Respect to Speed and Occupancy," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt35j7r3t5, Institute of Transportation Studies, UC Berkeley.
    6. Shao, Jing & Yang, Hangjun & Xing, Xiaoqiang & Yang, Liu, 2016. "E-commerce and traffic congestion: An economic and policy analysis," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 91-103.
    7. Zheng, Zuduo & Ahn, Soyoung & Chen, Danjue & Laval, Jorge, 2011. "Applications of wavelet transform for analysis of freeway traffic: Bottlenecks, transient traffic, and traffic oscillations," Transportation Research Part B: Methodological, Elsevier, vol. 45(2), pages 372-384, February.

    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:cdl:itsrrp:qt5h70x5j9. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucbus.html .

    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.