Evidence map›Paper›PMID 40307272›Full record

ArticleScientific data2025

Dense Crowd Dynamics and Pedestrian Trajectories: A Multiscale Field Dataset from the Festival of Lights in Lyon.

Oscar Dufour, Huu-Tu Dang, Jakob Cordes, Raphael Korbmacher, Mohcine Chraibi, Benoit Gaudou, Alexandre Nicolas, Antoine Tordeux

Abstract read
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Oscar DufourUniversité Claude Bernard Lyon 1, CNRS, Institut Lumière Matière, UMR5306, F-69100, Villeurbanne, France. oscar.dufour@univ-lyon1.fr.
Huu-Tu DangUMR 5505 IRIT, Université Toulouse Capitole, Toulouse, France.
Jakob CordesInstitute of Advanced Simulation, Forschungszentrum Jülich GmbH, Jülich, Germany.
Raphael KorbmacherFakultät für Maschinenbau und Sicherheitstechnik, Bergische Universität Wuppertal, Wuppertal, Germany.
Mohcine ChraibiInstitute of Advanced Simulation, Forschungszentrum Jülich GmbH, Jülich, Germany. m.chraibi@fz-juelich.de.ORCID http://orcid.org/0000-0002-0999-6807
Benoit GaudouUMR 5505 IRIT, Université Toulouse Capitole, Toulouse, France. benoit.gaudou@ut-capitole.fr.
Alexandre NicolasUniversité Claude Bernard Lyon 1, CNRS, Institut Lumière Matière, UMR5306, F-69100, Villeurbanne, France. alexandre.nicolas@cnrs.fr.ORCID http://orcid.org/0000-0002-8953-3924
Antoine TordeuxFakultät für Maschinenbau und Sicherheitstechnik, Bergische Universität Wuppertal, Wuppertal, Germany. tordeux@uni-wuppertal.de.ORCID http://orcid.org/0000-0001-5077-0327

Funding

Agence Nationale de la Recherche (French National Research Agency) ANR-20-CE92-0033Deutsche Forschungsgemeinschaft (German Research Foundation) 446168800
6 · The paper itself

Abstract

The dynamics of dense crowds have received considerable attention from researchers seeking fundamental understanding or aiming to develop data-driven algorithms to predict pedestrian trajectories. However, current research mainly relies on data collected in controlled settings. We present one of the first comprehensive field datasets describing dense pedestrian dynamics at different scales, from contextualized macroscopic crowd flows over hundreds of meters to microscopic trajectories (around 7000 individual trajectories). In addition, a sample of GPS traces, some statistics of contacts and pushes, and a list of non-standard crowd phenomena observed in the video recordings are provided. The data were collected during the 2022 Festival of Lights in Lyon, France, as part of the French-German MADRAS project and cover densities up to 4 pedestrians per square meter. We suggest using this extensive dataset, acquired in complex real-world settings, to benchmark models of pedestrian dynamics.

Identifiers

PMID40307272
PMCPMC12043992

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.