IDEAS home Printed from https://ideas.repec.org/a/wly/apsmbi/v28y2012i4p297-315.html
   My bibliography  Save this article

Real‐time road traffic forecasting using regime‐switching space‐time models and adaptive LASSO

Author

Listed:
  • Yiannis Kamarianakis
  • Wei Shen
  • Laura Wynter

Abstract

Smart transportation technologies require real‐time traffic prediction to be both fast and scalable to full urban networks. We discuss a method that is able to meet this challenge while accounting for nonlinear traffic dynamics and space‐time dependencies of traffic variables. Nonlinearity is taken into account by a union of non‐overlapping linear regimes characterized by a sequence of temporal thresholds. In each regime, for each measurement location, a penalized estimation scheme, namely the adaptive absolute shrinkage and selection operator (LASSO), is implemented to perform model selection and coefficient estimation simultaneously. Both the robust to outliers least absolute deviation estimates and conventional LASSO estimates are considered. The methodology is illustrated on 5‐minute average speed data from three highway networks. Copyright © 2012 John Wiley & Sons, Ltd.

Suggested Citation

  • Yiannis Kamarianakis & Wei Shen & Laura Wynter, 2012. "Real‐time road traffic forecasting using regime‐switching space‐time models and adaptive LASSO," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 28(4), pages 297-315, July.
  • Handle: RePEc:wly:apsmbi:v:28:y:2012:i:4:p:297-315
    DOI: 10.1002/asmb.1937
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asmb.1937
    Download Restriction: no

    File URL: https://libkey.io/10.1002/asmb.1937?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
    ---><---

    Citations

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


    Cited by:

    1. Hyun-Joo Lee & Eujin-Julia Kim & Sang-Woo Lee, 2017. "Examining Spatial Variation in the Effects of Japanese Red Pine ( Pinus densiflora ) on Burn Severity Using Geographically Weighted Regression," Sustainability, MDPI, vol. 9(5), pages 1-18, May.
    2. George Chalamandaris & Nikos E. Vlachogiannakis, 2018. "Are financial ratios relevant for trading credit risk? Evidence from the CDS market," Annals of Operations Research, Springer, vol. 266(1), pages 395-440, July.
    3. Tuo Sun & Shihao Zhu & Ruochen Hao & Bo Sun & Jiemin Xie, 2022. "Traffic Missing Data Imputation: A Selective Overview of Temporal Theories and Algorithms," Mathematics, MDPI, vol. 10(14), pages 1-22, July.
    4. Ma, Tao & Zhou, Zhou & Abdulhai, Baher, 2015. "Nonlinear multivariate time–space threshold vector error correction model for short term traffic state prediction," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 27-47.

    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:wly:apsmbi:v:28:y:2012:i:4:p:297-315. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1526-4025 .

    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.