IDEAS home Printed from https://ideas.repec.org/h/elg/eechap/21868_10.html
   My bibliography  Save this book chapter

Artificial intelligence and machine learning applications in freight transport

In: Handbook on Artificial Intelligence and Transport

Author

Listed:
  • Yijie Su
  • Hadi Ghaderi
  • Hussein Dia

Abstract

The advancement of technology and data analytics has led to an increasing interest in using artificial intelligence (AI) to address the challenges in freight transportation presented by surging demand and globally complex operations. This chapter aims to provide a systematic literature review of state-of-the-art AI applications in freight transport, based on a total of 101 journal articles published between 2012 and 2022. The bibliometric characteristics of the extant literature are analysed and discussed, providing insights into the cognitive structure of the discipline over the last decade. The related AI approaches are then introduced, followed by a classification of studies based on five distinct application areas. This chapter aims to establish a comprehensive understanding of existing AI applications with potential value for performing freight transport tasks more efficiently and safely. Finally, the chapter concludes with a discussion related to existing opportunities and barriers for the widescale deployment of AI-based applications in the freight industry.

Suggested Citation

  • Yijie Su & Hadi Ghaderi & Hussein Dia, 2023. "Artificial intelligence and machine learning applications in freight transport," Chapters, in: Hussein Dia (ed.), Handbook on Artificial Intelligence and Transport, chapter 10, pages 285-322, Edward Elgar Publishing.
  • Handle: RePEc:elg:eechap:21868_10
    as

    Download full text from publisher

    File URL: https://www.elgaronline.com/doi/10.4337/9781803929545.00019
    Download Restriction: no
    ---><---

    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:elg:eechap:21868_10. 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: Darrel McCalla (email available below). General contact details of provider: http://www.e-elgar.com .

    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.