ProactiveCrowd: Modelling Proactive Steering Behaviours for Agent‐Based Crowd Simulation

Simple item page
dc.contributor.authorLuo, Linboen_US
dc.contributor.authorChai, Chengen_US
dc.contributor.authorMa, Jianfengen_US
dc.contributor.authorZhou, Suipingen_US
dc.contributor.authorCai, Wentongen_US
dc.contributor.editorChen, Min and Benes, Bedrichen_US
dc.date.accessioned2018-04-05T12:48:44Z
dc.date.available2018-04-05T12:48:44Z
dc.date.issued2018
dc.description.abstractHow to realistically model an agent's steering behaviour is a critical issue in agent‐based crowd simulation. In this work, we investigate some proactive steering strategies for agents to minimize potential collisions. To this end, a behaviour‐based modelling framework is first introduced to model the process of how humans select and execute a proactive steering strategy in crowded situations and execute the corresponding behaviour accordingly. We then propose behaviour models for two inter‐related proactive steering behaviours, namely gap seeking and following. These behaviours can be frequently observed in real‐life scenarios, and they can easily affect overall crowd dynamics. We validate our work by evaluating the simulation results of our model with the real‐world data and comparing the performance of our model with that of two state‐of‐the‐art crowd models. The results show that the performance of our model is better or at least comparable to the compared models in terms of the realism at both individual and crowd levels.How to realistically model an agent's steering behaviour is a critical issue in agent‐based crowd simulation. In this work, we investigate some proactive steering strategies for agents to minimize potential collisions. To this end, a behaviour‐based modelling framework is first introduced to model the process of how humans select and execute a proactive steering strategy in crowded situations and execute the corresponding behaviour accordingly. We then propose behaviour models for two inter‐related proactive steering behaviours, namely gap seeking and following. These behaviours can be frequently observed in real‐life scenarios, and they can easily affect overall crowd dynamics.en_US
dc.description.number1
dc.description.sectionheadersArticles
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume37
dc.identifier.doi10.1111/cgf.13303
dc.identifier.issn1467-8659
dc.identifier.pages375-388
dc.identifier.urihttps://doi.org/10.1111/cgf.13303
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13303
dc.publisher© 2018 The Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectbehavioural animation
dc.subjectanimation
dc.subjecthuman simulation
dc.subjectanimation
dc.subjectmotion planning
dc.subjectanimation
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: 3D Graphics and Realism—Animation, I.6.5 [Simulation and Modelling]: Model Development—Modelling methodologies
dc.titleProactiveCrowd: Modelling Proactive Steering Behaviours for Agent‐Based Crowd Simulationen_US
Files
Collections
37-Issue 1