Extracting the fundamental diagram from aerial footage

TL;DR

This paper presents a novel drone-based method for extracting the fundamental diagram of traffic flow by combining vehicle detection, tracking, and traffic state estimation from aerial footage, aiding congestion management.

Contribution

It introduces an innovative three-phase methodology for deriving the fundamental diagram from drone footage, integrating detection, tracking, and traffic estimation algorithms.

Findings

Effective extraction of fundamental diagrams from aerial footage

Demonstrated applicability in real-world traffic scenarios

Potential for improved traffic congestion monitoring

Abstract

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.