
handle: 1959.4/unsworks_81684
With the rapid increase of vehicles in recent years, traffic surveillance becomes a crucial issue of traffic management. Since the traditional static sensor-based surveillance system can only passively monitor traffic, this paper considers the usage of unmanned aerial vehicles (UAVs), which can proactively conduct traffic surveillance thanks to the excellent mobility of UAVs. Specifically, we consider the navigation problem of a network of UAVs to effectively monitor a group of ground targets which move along a curvy road. A surveillance optimization problem is stated, and a distributed navigation algorithm for the UAV network is developed. It is proved that the proposed algorithm is locally optimal. Simulations confirm the effectiveness of the proposed navigation algorithm.
anzsrc-for: 1507 Transportation and Freight Services, anzsrc-for: 35 Commerce, anzsrc-for: 4605 Data Management and Data Science, anzsrc-for: 46 Information and Computing Sciences, 3509 Transportation, anzsrc-for: 0905 Civil Engineering, anzsrc-for: 4603 Computer vision and multimedia computation, 3 Good Health and Well Being, 35 Commerce, anzsrc-for: 4602 Artificial Intelligence, anzsrc-for: 3509 Transportation, Management, 004, 620, 4605 Data Management and Data Science, 46 Information and Computing Sciences, 4602 Artificial Intelligence, Logistics and Supply Chains, anzsrc-for: 0801 Artificial Intelligence and Image Processing, Tourism and Services
anzsrc-for: 1507 Transportation and Freight Services, anzsrc-for: 35 Commerce, anzsrc-for: 4605 Data Management and Data Science, anzsrc-for: 46 Information and Computing Sciences, 3509 Transportation, anzsrc-for: 0905 Civil Engineering, anzsrc-for: 4603 Computer vision and multimedia computation, 3 Good Health and Well Being, 35 Commerce, anzsrc-for: 4602 Artificial Intelligence, anzsrc-for: 3509 Transportation, Management, 004, 620, 4605 Data Management and Data Science, 46 Information and Computing Sciences, 4602 Artificial Intelligence, Logistics and Supply Chains, anzsrc-for: 0801 Artificial Intelligence and Image Processing, Tourism and Services
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
