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dc.contributor.authorLiu, Naen_US
dc.contributor.authorWang, Xingceen_US
dc.contributor.authorLiu, Shaolongen_US
dc.contributor.authorWu, Zhongkeen_US
dc.contributor.authorHe, Jialeen_US
dc.contributor.authorCheng, Pengen_US
dc.contributor.authorMiao, Chunyanen_US
dc.contributor.authorThalmann, Nadia Magnenaten_US
dc.identifier.citationLiu, N., Wang, X., Liu, S., Wu, Z., He, J., Cheng, P., Miao, C. & Thalmann, N. M. (2019). Hierarchical planning-based crowd formation. Computer Animation and Virtual Worlds, 30(6), e1875-.
dc.description.abstractTeam formation with realistic crowd simulation behavior is a challenge in computer graphics, multiagent control, and social simulation. In this study, we propose a framework of crowd formation via hierarchical planning, which includes cooperative-task, coordinated-behavior, and action-control planning. In cooperative-task planning, we improve the grid potential field to achieve global path planning for a team. In coordinated-behavior planning, we propose a time–space table to arrange behavior scheduling for a movement. In action-control planning, we combine the gaze-movement angle model and fuzzy logic control to achieve agent action. Our method has several advantages. (1) The hierarchical architecture is guaranteed to match the human decision process from high to low intelligence. (2) The agent plans his behavior only with the local information of his neighbor; the global intelligence of the group emerges from these local interactions. (3) The time–space table fully utilizes three-dimensional information. Our method is verified using crowds of various densities, from sparse to dense, employing quantitative performance measures. The approach is independent of the simulation model and can be extended to other crowd simulation tasks.en_US
dc.relation.ispartofComputer Animation and Virtual Worldsen_US
dc.rights© 2019 John Wiley & Sons, Ltd. All rights reserved.en_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.titleHierarchical planning-based crowd formationen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.subject.keywordsFuzzy Logic Controlen_US
dc.subject.keywordsGaze-movement Angleen_US
dc.description.acknowledgementThe authors sincerely thank the referees and anonymous reviewers for their helpful comments and suggestions. This research was supported by the National Key Research and Development Program of China (2017YFB1002604, 2017YFB100-2600, and 2017YFB1402100), the National Key Cooperation between the BRICS of China (2017YFE0100500), and the Beijing Municipal Natural Science Foundation of China (4172033).en_US
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