PLEdestrians: A Least-Effort Approach to Crowd Simulation

dc.contributor.authorGuy, Stephen J.en_US
dc.contributor.authorChhugani, Jatinen_US
dc.contributor.authorCurtis, Seanen_US
dc.contributor.authorDubey, Pradeepen_US
dc.contributor.authorLin, Mingen_US
dc.contributor.authorManocha, Dineshen_US
dc.contributor.editorMZoran Popovic and Miguel Otaduyen_US
dc.date.accessioned2014-01-29T07:51:21Z
dc.date.available2014-01-29T07:51:21Z
dc.date.issued2010en_US
dc.description.abstractWe present a new algorithm for simulating large-scale crowds at interactive rates based on the Principle of Least Effort. Our approach uses an optimization method to compute a biomechanically energy-efficient, collision-free trajectory that minimizes the amount of effort for each heterogeneous agent in a large crowd. Moreover, the algorithm can automatically generate many emergent phenomena such as lane formation, crowd compression, edge and wake effects ant others. We compare the results from our simulations to data collected from prior studies in pedestrian and crowd dynamics, and provide visual comparisons with real-world video. In practice, our approach can interactively simulate large crowds with thousands of agents on a desktop PC and naturally generates a diverse set of emergent behaviorsen_US
dc.description.seriesinformationEurographics/ ACM SIGGRAPH Symposium on Computer Animationen_US
dc.identifier.isbn978-3-905674-27-9en_US
dc.identifier.issn1727-5288en_US
dc.identifier.urihttps://doi.org/10.2312/SCA/SCA10/119-128en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.2.11 [Artificial Intelligence]: Distributed Artificial Intelligence-Multiagent systemsen_US
dc.titlePLEdestrians: A Least-Effort Approach to Crowd Simulationen_US
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