TY - JOUR
T1 - DDDAMS-based crowd control via UAVs and UGVs
AU - Wang, Zhenrui
AU - Li, Mingyang
AU - Khaleghi, Amirreza M.
AU - Xu, Dong
AU - Lobos, Alfonso
AU - Vo, Christopher
AU - Lien, Jyh Ming
AU - Liu, Jian
AU - Son, Young Jun
N1 - Funding Information: This work was supported by the Air Force Office of Scientific Research under FA9550-12-1-0238.
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - Agent-based simulation
KW - Crowd control
KW - Multi-scale
KW - UAV
KW - UGV
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U2 - 10.1016/j.procs.2013.05.372
DO - 10.1016/j.procs.2013.05.372
M3 - Conference article
SN - 1877-0509
VL - 18
SP - 2028
EP - 2035
JO - Procedia Computer Science
JF - Procedia Computer Science
T2 - 13th Annual International Conference on Computational Science, ICCS 2013
Y2 - 5 June 2013 through 7 June 2013
ER -