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Data in Brief
Article . 2025
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Aerial video & trajectory dataset of vehicles on circular roadYouTubeGitHubZenodo

Authors: Kevin Riehl; Shaimaa K. El-Baklish; Anastasios Kouvelas; Michail A. Makridis;

Aerial video & trajectory dataset of vehicles on circular roadYouTubeGitHubZenodo

Abstract

This article presents aerial video and vehicle trajectory data collected during a phantom traffic jam experiment with the Swiss television (SRF) at the driving test centre TCS Derendingen, Solothurn, from March 12th 2024. 14 vehicles were recorded for a total duration of 40 minutes with a drone from above, and vehicle trajectories were extracted using computer vision and Kalman filtering methodology. The observed vehicles differ by their power train (combustion, electric, hybrid), gearbox (manual, automatic), and equipment with advanced driver assistance systems.The data provided in this article offers a valuable resource for researchers, industry representatives, public authorities, and other parties interested in mixed-traffic dynamics, traffic flow theory, computer vision. This dataset can for instance be used: (i) to explore how gearbox, powertrain, and assistance systems affect the propagation of traffic jams on highways, and (ii) to provide a benchmark dataset for visual vehicle trajectory extraction using computer vision methods.

Keywords

Vehicle trajectory, Q1-390, Science (General), Oriented object detection, Computer applications to medicine. Medical informatics, R858-859.7, Computer vision, Deep learning, Intelligent transportation systems, Remote sensing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold