{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T05:25:31Z","timestamp":1740115531452,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"abstract":"<jats:p>A number of approaches have been presented to simulate heterogeneous pedestrian dynamical behaviors. However, most of the existing models are developed based on the assumption that the perception and decision-making of human in real time can be described using precise values. In this paper, a new approach which incorporates personality trait model with fuzzy logic theory to generate heterogeneous crowd behaviors is proposed. To reveal the influence of individual personality traits in crowd behaviors, we establish a model based on multi-agent system in which each virtual human is referred to as an agent. Then, we derive a fuzzy logic-based mapping between behavior parameters and personality descriptors corresponding to the well-established OCEAN personality model. Finally, a variety of simulation experiments were implemented. Experimental results show that the proposed approach can exhibit more reasonable and heterogeneous behaviors in various scenarios, which can improve the believability of simulation and analysis how different personalities influence the crowd phenomena.<\/jats:p>","DOI":"10.3233\/978-1-61499-828-0-238","type":"book-chapter","created":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T12:06:08Z","timestamp":1740053168000},"source":"Crossref","is-referenced-by-count":0,"title":["A Fuzzy Logic-Based Model for Heterogeneous Pedestrian Dynamical Behaviors"],"prefix":"10.3233","author":[{"family":"Xue Zhuxin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Fan Xiangtao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Jin Qingwen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Jian Hongdeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Liu Jian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining III"],"original-title":[],"deposited":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T12:44:27Z","timestamp":1740055467000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-827-3&spage=238&doi=10.3233\/978-1-61499-828-0-238"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-828-0-238","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2017]]}}}