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@ARTICLE{Xiao:902571,
      author       = {Xiao, Yao and Xu, Jun and Chraibi, Mohcine and Zhang, Jun
                      and Gou, Chao},
      title        = {{A} generalized trajectories-based evaluation approach for
                      pedestrian evacuation models},
      journal      = {Safety science},
      volume       = {147},
      issn         = {0925-7535},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2021-04370},
      pages        = {105574 -},
      year         = {2022},
      abstract     = {The fundamental diagram and self-organized phenomena in
                      crowds are widely used to test the applicability of
                      evacuation models. These benchmarks are good indicators for
                      the validity of a model, whereas they are insufficient
                      descriptors for the realistic microscopic behaviors of
                      pedestrians. In recent years, the rapid increase of the
                      trajectory datasets which benefits from the development of
                      recognition technologies open the door to new possibilities
                      for an extensive quantitative validation of the models. In
                      this work, a trajectories-based analysis approach which
                      contains types of indexes is proposed. The indexes are a mix
                      of macroscopic type (fundamental diagram index, speed choice
                      index, and direction choice index) and microscopic type
                      (trajectories pattern index), distribution type (route
                      length distribution index, travel time distribution index)
                      and time-series type (starting position distance time-series
                      index, destination position distance time-series index.
                      Moreover, the Kolmogorov-Smirnov (K-S) test as well as the
                      dynamic time warping (DTW) method are introduced to quantify
                      the similarities of results on different types of indexes.
                      In brief, by comparing experimental and simulation
                      trajectories, we can measure a set of performance scores in
                      different perspectives. Here, the Social Force Model (SFM)
                      and Heuristics Model (HM) are respectively introduced and
                      evaluated. According to the proposed evaluation approach, we
                      show that the HM performs better than the SFM. Our analysis
                      approach is model agnostic and is defined in a general way,
                      such that it can be applied for trajectory sets from
                      different experiment settings. This work can help to improve
                      the accuracy of simulation models, and the pedestrian safety
                      in crowd activities and autonomous vehicle navigation will
                      be benefited.},
      cin          = {IAS-7},
      ddc          = {610},
      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},
      UT           = {WOS:000722140000005},
      doi          = {10.1016/j.ssci.2021.105574},
      url          = {https://juser.fz-juelich.de/record/902571},
}