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

Document Type

Article

Source of Publication

Personal and Ubiquitous Computing

Publication Date

1-1-2023

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.

ISSN

1617-4909

Publisher

Springer Science and Business Media LLC

Disciplines

Computer Sciences

Keywords

Computer vision, Heterogeneous traffic, Image segmentation, Karachi, Pakistan, Traffic sensors

Scopus ID

85169002988

Indexed in Scopus

yes

Open Access

no

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