DDDAMS-based Crowd Control via UAVs and UGVs

详细信息    查看全文

• 作者：Zhenrui Wang^a ; Mingyang Li^a ; Amirreza M. Khaleghi^a ; Dong Xu^a ; Alfonso Lobos^a ; Christopher Vo^b ; Jyh-Ming Lien^b ; Jian Liu^a ; Young-Jun Son^a ; ^{son@sie.arizona.edu}
• 关键词：Crowd control ; UAV ; UGV ; multi-scale ; agent-based simulation
• 刊名：Procedia Computer Science
• 出版年：2013
• 出版时间：2013
• 年：2013
• 卷：18
• 期：Complete
• 页码：2028-2035
• 全文大小：760 K

文摘

Unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) collaboratively play central roles in intelligence gathering and control in urban/border surveillance and crowd control. In this paper, we first propose a comprehensive planning and control framework based on dynamic-data-driven, adaptive multi-scale simulation (DDDAMS). We then discuss proposed algorithms enabling DDDAMS capability based on several methods such as 1) Bayesian-based information aggregation/disaggregation, 2) dynamic information updating based on observation/simulation, 3) temporal and spatial data fusion for enhanced performance, 4) multi-resolution strategy in temporal tracking frequency, and 5) cached intelligent observers. Finally, preliminary results based on the proposed framework, algorithms, and testbeds are discussed.