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  4. Linking trajectory data collected with a swarm of drones to the underlying urban network for macroscopic traffic parameter estimation
 
conference paper not in proceedings

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

Landtmeters, Joachim
•
Manos Barmpounakis, Emmanouil  
•
Geroliminis, Nikolaos  
July 6, 2020
The 3rd Symposium on Management of Future Motorway and Urban Traffic Systems (MFTS2020)

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.

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Type
conference paper not in proceedings
Author(s)
Landtmeters, Joachim
Manos Barmpounakis, Emmanouil  
Geroliminis, Nikolaos  
Date Issued

2020-07-06

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LUTS  
Event nameEvent placeEvent date
The 3rd Symposium on Management of Future Motorway and Urban Traffic Systems (MFTS2020)

Luxembourg, Luxembourg

July 6-8, 2020

RelationURL/DOI

IsSupplementedBy

https://https://open-traffic.epfl.ch
Available on Infoscience
March 12, 2021
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/175920
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