Gabriel Fonseca Silva, Paulo Ricardo Knob, Rubens Halbig Montanha, Soraia Raupp Musse
{"title":"Evaluating and Comparing Crowd Simulations: Perspectives from a Crowd Authoring Tool","authors":"Gabriel Fonseca Silva, Paulo Ricardo Knob, Rubens Halbig Montanha, Soraia Raupp Musse","doi":"arxiv-2408.15762","DOIUrl":null,"url":null,"abstract":"Crowd simulation is a research area widely used in diverse fields, including\ngaming and security, assessing virtual agent movements through metrics like\ntime to reach their goals, speed, trajectories, and densities. This is relevant\nfor security applications, for instance, as different crowd configurations can\ndetermine the time people spend in environments trying to evacuate them. In\nthis work, we extend WebCrowds, an authoring tool for crowd simulation, to\nallow users to build scenarios and evaluate them through a set of metrics. The\naim is to provide a quantitative metric that can, based on simulation data,\nselect the best crowd configuration in a certain environment. We conduct\nexperiments to validate our proposed metric in multiple crowd simulation\nscenarios and perform a comparison with another metric found in the literature.\nThe results show that experts in the domain of crowd scenarios agree with our\nproposed quantitative metric.","PeriodicalId":501174,"journal":{"name":"arXiv - CS - Graphics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Graphics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.15762","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Crowd simulation is a research area widely used in diverse fields, including
gaming and security, assessing virtual agent movements through metrics like
time to reach their goals, speed, trajectories, and densities. This is relevant
for security applications, for instance, as different crowd configurations can
determine the time people spend in environments trying to evacuate them. In
this work, we extend WebCrowds, an authoring tool for crowd simulation, to
allow users to build scenarios and evaluate them through a set of metrics. The
aim is to provide a quantitative metric that can, based on simulation data,
select the best crowd configuration in a certain environment. We conduct
experiments to validate our proposed metric in multiple crowd simulation
scenarios and perform a comparison with another metric found in the literature.
The results show that experts in the domain of crowd scenarios agree with our
proposed quantitative metric.