A nonparametric online control chart for monitoring crowd density using relative density-ratio estimation

Wenhui Zhou, Yibin Xie and Zhibin Zheng

European Journal of Operational Research, 2025, vol. 325, issue 1, 132-146

Abstract: With the increasing incidence of fatal crowd stampede disasters at public events due to rapid urbanization and escalating population density, there is an urgent need for real-time monitoring of crowd flow to prevent such tragic incidents. This paper proposes a novel nonparametric online control chart for crowd density monitoring, called the RDR-CUSUM chart. This chart utilizes a new statistic based on the principles of cumulative sum (CUSUM) and relative density ratio (RDR). We present an RDR estimation method for deriving this statistic, which is enhanced by an S-M Invertor algorithm to ensure the efficiency required for real-time application. Numerical analyses demonstrate that the proposed chart can quickly respond to the distribution’s mean, variance, pattern, and different distribution parameter shifts. Moreover, the effectiveness of the method has been validated through two application examples, which illustrate its proficiency in detecting changes in crowd density and providing early warnings of potential crowd stampede disasters.

Keywords: Relative density ratio estimation; Crowd density monitoring; Log likelihood ratio test; Density ratio estimation; Cumulative sum control chart (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221725001997
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:325:y:2025:i:1:p:132-146

DOI: 10.1016/j.ejor.2025.03.006

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().