ProactiveCrowd: Modelling Proactive Steering Behaviours for Agent‐Based Crowd Simulation
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 mo...
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| Vydané v: | Computer graphics forum Ročník 37; číslo 1; s. 375 - 388 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Oxford
Blackwell Publishing Ltd
01.02.2018
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| ISSN: | 0167-7055, 1467-8659 |
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| Abstract | 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. 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. |
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| AbstractList | 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. 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. 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. |
| Author | Luo, Linbo Chai, Cheng Ma, Jianfeng Zhou, Suiping Cai, Wentong |
| Author_xml | – sequence: 1 givenname: Linbo surname: Luo fullname: Luo, Linbo email: lbluo@xidian.edu.cn organization: Xidian University – sequence: 2 givenname: Cheng surname: Chai fullname: Chai, Cheng email: cchaixd@yahoo.com organization: Xidian University – sequence: 3 givenname: Jianfeng surname: Ma fullname: Ma, Jianfeng email: jfma@mail.xidian.edu.cn organization: Xidian University – sequence: 4 givenname: Suiping surname: Zhou fullname: Zhou, Suiping email: s.zhou@mdx.ac.uk organization: Middlesex University – sequence: 5 givenname: Wentong surname: Cai fullname: Cai, Wentong email: ASWTCAI@ntu.edu.sg organization: Nanyang Technological University |
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| SubjectTerms | animation Behavior behavioural animation Categories 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 Computer simulation human simulation Modelling motion planning Simulation Steering |
| Title | ProactiveCrowd: Modelling Proactive Steering Behaviours for Agent‐Based Crowd Simulation |
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