Extracting the fundamental diagram from aerial footage
This work addresses traffic congestion monitoring for transportation networks, but it appears incremental as it applies existing techniques like vehicle detection and tracking to new data sources.
The paper tackled the problem of obtaining the fundamental diagram for traffic analysis by developing a method using aerial footage from drones, resulting in a demonstrated application in a real-world setting.
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.