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Real-time road occupancy and traffic measurements using unmanned aerial vehicle and fundamental traffic flow diagrams

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Abstract

The technologies and sensors developed for standard traffic streams often fail to accurately measure the heterogeneous traffic with no lane discipline. This research proposes an efficient framework to measure traffic flow parameters in real-time using an unmanned aerial vehicle (UAV). The proposed framework in this research estimates road area occupancy from the images extracted from the video recorded using a UAV by applying the image segmentation technique. The road area occupancy is converted into traffic density using an occupancy-density model developed for the local heterogeneous traffic. A speed-density fundamental diagram is developed, which estimates the average speed corresponding to the measured traffic density. The fundamental relation between flow rate, average speed, and density is applied to compute traffic flow rate using the estimated average speed and density. The proposed framework is computationally less demanding in comparison with other computer vision and artificial intelligence–based techniques. The proposed framework accurately measured road area occupancy with an average accuracy of 97.6%. Traffic density was measured with an average accuracy of 88.8%. Similarly, the average speed and flow rate were measured with an average accuracy of 85.4% and 84.2%, respectively.

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Data availability

The data and material will be made available on request through the corresponding author.

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Code availability

The programming code will be made available on request through the corresponding author.

Funding

This research was partly carried out with the support of Exascale Open Data Analytics Lab, National Center for Big Data & Cloud Computing (NCBC), and funded by the Higher Education Commission of Pakistan. Part of this research was supported by Zayed University Research Cluster grant #R17075.

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Authors and Affiliations

  1. Department of Urban & Infrastructure Engineering, NED University of Engineering & Technology, Karachi, Pakistan

    Afzal Ahmed & Adnan Qadir

  2. Zayed University, Dubai, United Arab Emirates

    Fatima Outay

  3. Department of Computer Science and Information Technology, NED University of Engineering & Technology, Karachi, Pakistan

    Muhammad Umer Farooq & Muhammad Ali Ismail

  4. Exascale Open Data Analytics Lab, NED University of Engineering & Technology, Karachi, Pakistan

    Sehrish Saeed

  5. Transportation Research Institute (IMOB), Hasselt University, Diepenbeek, Belgium

    Muhammad Adnan

Authors
  1. Afzal Ahmed
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  2. Fatima Outay
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  3. Muhammad Umer Farooq
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  4. Sehrish Saeed
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  5. Muhammad Adnan
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  6. Muhammad Ali Ismail
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  7. Adnan Qadir
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Correspondence to Afzal Ahmed.

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Ahmed, A., Outay, F., Farooq, M.U. et al. Real-time road occupancy and traffic measurements using unmanned aerial vehicle and fundamental traffic flow diagrams. Pers Ubiquit Comput 27, 1669–1680 (2023). https://doi.org/10.1007/s00779-023-01737-w

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  • DOI: https://doi.org/10.1007/s00779-023-01737-w

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