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@ARTICLE{Cordes:1024166,
      author       = {Cordes, Jakob and Schadschneider, Andreas and Nicolas,
                      Alexandre},
      title        = {{D}imensionless numbers reveal distinct regimes in the
                      structure and dynamics of pedestrian crowds},
      journal      = {PNAS nexus},
      volume       = {3},
      number       = {4},
      issn         = {2752-6542},
      address      = {Oxford},
      publisher    = {Oxford University Press},
      reportid     = {FZJ-2024-01997},
      pages        = {pgae120},
      year         = {2024},
      abstract     = {In Fluid Mechanics, dimensionless numbers like the Reynolds
                      number help classify flows. We argue that such a
                      classification is also relevant for crowd flows by putting
                      forward the dimensionless Intrusion and Avoidance numbers,
                      which quantify the intrusions into the pedestrians’
                      personal spaces and the imminency of the collisions that
                      they face, respectively.Using an extensive dataset, we show
                      that these numbers delineate regimes where distinct
                      variables characterize the crowd's arrangement, namely,
                      Euclidean distances at low Avoidance number and
                      times-to-collision at low Intrusion number. On the basis of
                      these findings, a perturbative expansion of the individual
                      pedestrian dynamics is carried out around the
                      non-interacting state, in quite general terms. Simulations
                      confirm that this expansion performs well in its expected
                      regime of applicability.},
      cin          = {IAS-7},
      ddc          = {600},
      cid          = {I:(DE-Juel1)IAS-7-20180321},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / DFG project
                      446168800 - Multi-Agent-Modellierung der Dynamik von dichten
                      Fußgängermengen: Vorhersagen $\&$ Verstehen (446168800)},
      pid          = {G:(DE-HGF)POF4-5111 / G:(GEPRIS)446168800},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {38577258},
      UT           = {WOS:001196541200001},
      doi          = {10.1093/pnasnexus/pgae120},
      url          = {https://juser.fz-juelich.de/record/1024166},
}