DDDAMS-based Crowd Control via UAVs and UGVs

• DOI: 10.1016/j.procs.2013.05.372
• Publication Date: 2013-06-01T15:15:28Z
• Authors: Zhenrui Wang; Mingyang Li; Amirreza M. Khaleghi; Dong Xu; Alfonso Lobos; Christopher Vo; Jyh-Ming Lien; Jian Liu; Young-Jun Son
• Keywords: Crowd Simulation; Sensor Fusion; Dynamic Bayesian network

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