Driver behaviour detection and vehicle rating using multi-UAV coordinated vehicular networks

Vishal Sharma, Hsing Chung Chen*, Rajesh Kumar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)


Road accidents account for more than 2% of the total deaths across the globe with more than a million deaths each year due to road mishaps and improper traffic management. Traffic management is a major problem faced by modern cities due to a large number of vehicles operating at the same time. One of the major issues for road mishaps is driver's behaviour and skills. Thus, tracking vehicles and analyzing the driver behaviour is required for proper regulation of traffic. Some of the solutions are provided using infrastructure-based vehicular ad hoc networks (VANETs). However, their operations are constrained by the traffic itself, thus, limiting their scope. A new solution by forming VANETs using multiple unmanned aerial vehicles (UAVs) is proposed which is independent of using road side units (RSUs) for communications. The proposed approach is analyzed using simulations as well as real-time dataset.

Original languageEnglish
Pages (from-to)3-32
JournalJournal of Computer and System Sciences
Early online date09 Nov 2016
Publication statusPublished - 01 Jun 2017
Externally publishedYes


  • Behaviour detection
  • UAVs
  • VANETs

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Networks and Communications
  • Computational Theory and Mathematics
  • Applied Mathematics


Dive into the research topics of 'Driver behaviour detection and vehicle rating using multi-UAV coordinated vehicular networks'. Together they form a unique fingerprint.

Cite this