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JDR Vol.19 No.2 pp. 336-346
(2024)
doi: 10.20965/jdr.2024.p0336

Paper:

Evaluating Pedestrian Congestion Based on Missing Sensing Data

Xiaolu Jia*,**,† ORCID Icon, Claudio Feliciani*,** ORCID Icon, Sakurako Tanida*,** ORCID Icon, Daichi Yanagisawa*,** ORCID Icon, and Katsuhiro Nishinari*,** ORCID Icon

*Department of Aeronautics and Astronautics, School of Engineering, The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

**Research Center for Advanced Science and Technology, The University of Tokyo
Tokyo, Japan

Corresponding author

Received:
October 8, 2023
Accepted:
November 21, 2023
Published:
April 1, 2024
Keywords:
pedestrian congestion, congestion evaluation, missing data, pedestrian density, congestion number
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.

Cite this article as:
X. Jia, C. Feliciani, S. Tanida, D. Yanagisawa, and K. Nishinari, “Evaluating Pedestrian Congestion Based on Missing Sensing Data,” J. Disaster Res., Vol.19 No.2, pp. 336-346, 2024.
Data files:
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Last updated on Jul. 19, 2024