Efficient traffic monitoring is playing a fundamental role in successfully tackling congestion in transportation networks. Congestion is strongly correlated with two measurable characteristics, the demand and the network density that impact the overall system behavior. At large, this system behavior is characterized through the fundamental diagram of a road segment, a region or the network. In this paper we devise an innovative way to obtain the fundamental diagram through aerial footage obtained from drone platforms. The derived methodology consists of 3 phases: vehicle detection, vehicle tracking and traffic state estimation. We elaborate on the algorithms developed for each of the 3 phases and demonstrate the applicability of the results in a real-world setting.
@article{arxiv.2007.03227,
title = {Extracting the fundamental diagram from aerial footage},
author = {Rafael Makrigiorgis and Panayiotis Kolios and Stelios Timotheou and Theocharis Theocharides and Christos G. Panayiotou},
journal= {arXiv preprint arXiv:2007.03227},
year = {2020}
}