IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v180y2024ics0965856423003695.html
   My bibliography  Save this article

An efficient pavement distress detection scheme through drone–ground vehicle coordination

Author

Listed:
  • Zhao, Yiyue
  • Zhang, Wei
  • Yang, Ying
  • Sun, Huijun
  • Wang, Liang

Abstract

Efficient road maintenance is imperative for infrastructure longevity and safety. Conventional ground vehicle-based methods for detecting pavement distress, however, encounter limitations in practice when dealing with complex road structures. Drones, endowed with greater spatial freedom, can access road segments that are hard-to-reach to ground vehicles, thereby enhancing detection efficiency and expanding detection coverage. By harnessing the complementary strengths of both detection modalities, we propose a scheme that capitalizes on the cooperative coordination of drones and ground vehicles for effective pavement distress detection. Our proposed scheme is evaluated using realistic road networks in practice. Results reveal that the coordinated detection scheme strikes a favorable balance between fixed device-related expenses and detection efficiency. This scheme offers promising policy implications, streamlining maintenance across diverse road networks and meeting extensive infrastructure needs, offering policymakers an efficient and viable scheme for road infrastructure maintenance.

Suggested Citation

  • Zhao, Yiyue & Zhang, Wei & Yang, Ying & Sun, Huijun & Wang, Liang, 2024. "An efficient pavement distress detection scheme through drone–ground vehicle coordination," Transportation Research Part A: Policy and Practice, Elsevier, vol. 180(C).
  • Handle: RePEc:eee:transa:v:180:y:2024:i:c:s0965856423003695
    DOI: 10.1016/j.tra.2023.103949
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856423003695
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tra.2023.103949?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.

    Citations

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


    Cited by:

    1. Niu, Baozhuang & Zhang, Jianhua & Xie, Fengfeng, 2024. "Drone logistics’ resilient development: impacts of consumer choice, competition, and regulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 185(C).

    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:eee:transa:v:180:y:2024:i:c:s0965856423003695. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.