Linking trajectory data collected with a swarm of drones to the underlying urban network for macroscopic traffic parameter estimation

Recently, an open-data initiative was announced with one of the most complete datasets to study urban congestion. The pNEUMA dataset consists of more than half a million trajectories in heterogeneous traffic. In order to utilize the dataset for macroscopic studies it is necessary to relate these trajectories to a road network as trajectory data is rarely linked to the underlying road network. This paper presents a framework to extract a full road network, map-match the trajectory data and measure macroscopic traffic characteristics by implementing virtual loops anywhere in the network. Some first findings reveal the influence of heterogeneous traffic on the Fundamental Diagram (FD) especially when it comes to the effect of Powered Two-Wheelers (PTW). Thus, a modification taking into account the different size of the vehicles is applied to treat large overestimation of density in homogenious traffic environments.