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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/16068

Title: Behaviour recognition of ground vehicle using airborne monitoring of unmanned aerial vehicles
Authors: Oh, Hyondong
Kim, Seungkeun
Shin, Hyo-Sang
Tsourdos, Antonios
White, Barry A.
Keywords: Bahaviour recognition
Unmanned aerial vehicles
Trajectory classification
Tracking filter
String matching
Decision-making
Issue Date: 2014
Publisher: © Taylor and Francis
Citation: OH, H. ... et al, 2014. Behaviour recognition of ground vehicle using airborne monitoring of unmanned aerial vehicles. International Journal of Systems Science, 45 (12), pp. 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.
Description: This is an Accepted Manuscript of an article published by Taylor & Francis Group in International Journal of Systems Science on 4 Mar 2013, available online at: http://www.tandfonline.com/10.1080/00207721.2013.772677
Version: Accepted for publication
DOI: 10.1080/00207721.2013.772677
URI: https://dspace.lboro.ac.uk/2134/16068
Publisher Link: http://dx.doi.org/10.1080/00207721.2013.772677
ISSN: 0020-7721
Appears in Collections:Published Articles (Aeronautical and Automotive Engineering)

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