@inproceedings{24159,
  abstract     = {{The online fitting of a microscopic traffic simulation model to reconstruct the current state of a real traffic
area can be challenging depending on the provided data. This paper presents a novel method based on limited
data from sensors positioned at specific locations and guarantees a general accordance of reality and
simulation in terms of multimodal road traffic counts and vehicle speeds. In these considerations, the actual
purpose of research is of particular importance. Here, the research aims at improving the traffic flow by
controlling the Traffic Light Systems (TLS) of the examined area which is why the current traffic state and
the route choices of individual road users are the matter of interest. An integer optimization problem is derived
to fit the current simulation to the latest field measurements. The concept can be transferred to any road traffic
network and results in an observation of the current multimodal traffic state matching at the given sensor
position. First case studies show promosing results in terms of deviations between reality and simulation.}},
  author       = {{Malena, Kevin and Link, Christopher and Mertin, Sven and Gausemeier, Sandra and Trächtler, Ansgar}},
  booktitle    = {{VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems}},
  isbn         = {{978-989-758-513-5}},
  keywords     = {{Microscopic Traffic Simulation, Online State Estimation, Mixed Road Users, Sensor Fusion, Integer Programming, Route Choice, Vehicle2Infrastructure}},
  location     = {{Online Streaming}},
  pages        = {{386--395}},
  publisher    = {{SCITEPRESS}},
  title        = {{{Online State Estimation for Microscopic Traffic Simulations using Multiple Data Sources*}}},
  volume       = {{7}},
  year         = {{2021}},
}