Evaluating Pedestrian Congestion Based on Missing Sensing Data

Xiaolu Jia; Claudio Feliciani; Sakurako Tanida; Daichi Yanagisawa; Katsuhiro Nishinari

doi:10.20965/jdr.2024.p0336

Special Issue on Crowd Management and its Applications

Evaluating Pedestrian Congestion Based on Missing Sensing Data

Xiaolu Jia , Claudio Feliciani, Sakurako Tanida, Daichi Yanagisawa, Katsuhiro Nishinari

Author information

Xiaolu Jia Corresponding author
https://orcid.org/0000-0002-8012-0015
Department of Aeronautics and Astronautics, School of Engineering, The University of Tokyo
Research Center for Advanced Science and Technology, The University of Tokyo
Claudio Feliciani
https://orcid.org/0000-0003-0718-8707
Department of Aeronautics and Astronautics, School of Engineering, The University of Tokyo
Research Center for Advanced Science and Technology, The University of Tokyo
Sakurako Tanida
https://orcid.org/0000-0003-4674-2811
Department of Aeronautics and Astronautics, School of Engineering, The University of Tokyo
Research Center for Advanced Science and Technology, The University of Tokyo
Daichi Yanagisawa
https://orcid.org/0000-0001-7497-8413
Department of Aeronautics and Astronautics, School of Engineering, The University of Tokyo
Research Center for Advanced Science and Technology, The University of Tokyo
Katsuhiro Nishinari
https://orcid.org/0000-0003-3069-1757
Department of Aeronautics and Astronautics, School of Engineering, The University of Tokyo
Research Center for Advanced Science and Technology, The University of Tokyo

Keywords: pedestrian congestion, congestion evaluation, missing data, pedestrian density, congestion number

JOURNAL OPEN ACCESS

2024 Volume 19 Issue 2 Pages 336-346

DOI https://doi.org/10.20965/jdr.2024.p0336

Details

Abstract

Accurately evaluating pedestrian congestion is crucial for evidence-based improvements in various walking environments. Tracking pedestrian movements in real-world settings often leads to incomplete data collection. Despite this challenge, pedestrian congestion with missing data has not been extensively addressed in existing research. This study examined the impact of missing data on density, speed, and congestion number in the course of evaluating pedestrian congestion. While density is the most commonly used index, speed and congestion number proved more robust.

Corresponding author

Funder information

1.Fund name: Japan Science and Technology Agency

2.Fund name: Japan Society for the Promotion of Science

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