Behaviour recognition of ground vehicle using airborne monitoring of unmanned aerial vehicles

Hyondong Oh, Seungkeun Kim, Hyo-Sang Shin, Antonios Tsourdos and Brian A. White

International Journal of Systems Science, 2014, vol. 45, issue 12, 2499-2514

Abstract: This paper proposes a behaviour recognition methodology for ground vehicles moving within road traffic using unmanned aerial vehicles in order to identify suspicious or abnormal behaviour. With the target information acquired by unmanned aerial vehicles and estimated by filtering techniques, ground vehicle behaviour is first classified into representative driving modes, and then a string pattern matching theory is applied to detect suspicious behaviours in the driving mode history. Furthermore, a fuzzy decision-making process is developed to systematically exploit all available information obtained from a complex environment and confirm the characteristic of behaviour, while considering spatiotemporal environment factors as well as several aspects of behaviours. To verify the feasibility and benefits of the proposed approach, numerical simulations on moving ground vehicles are performed using realistic car trajectory data from an off-the-shelf traffic simulation software.

Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2013.772677 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:45:y:2014:i:12:p:2499-2514

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20

DOI: 10.1080/00207721.2013.772677

Access Statistics for this article

International Journal of Systems Science is currently edited by Visakan Kadirkamanathan

More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().