Intelligent Crowd Management Using a Virtual Coordinate System

Abstract

With the rapid growth of populations worldwide, the need for intelligent crowd management solutions has become increasingly critical. One of the key challenges in this field is accurately assessing and managing pedestrian movement. Traditional crowd management systems rely on localization maps, while topology maps provide an alternative approach to analyzing pedestrian dynamics. In this paper, we explore the integration of virtual coordinate systems (VCSs) with topology maps for enhanced crowd management. We propose a novel mobility model based on the Reference Point Mobility model to simulate pedestrian movement and generate datasets for experimental evaluation. Additionally, we assess the reliability of the VCS in detecting congestion by introducing a method that quantifies node density in a given area. This method estimates a node’s potential location based on the average number of hops between the node and anchor points. Our approach demonstrates promising results, achieving a maximum error rate of 12%.