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|Title:||Risk assessment model for UAV cost-effective path planning in urban environments||Authors:||Hu, Xinting
Low, Kin Huat
|Keywords:||Engineering::Aeronautical engineering||Issue Date:||2020||Source:||Hu, X., Pang, B., Dai, F., & Low, K. H. (2020). Risk assessment model for UAV cost-effective path planning in urban environments. IEEE Access, 8, 150162-150173. doi:10.1109/access.2020.3016118||Journal:||IEEE Access||Abstract:||Increasing use of Unmanned Aerial Vehicle (UAV) in urban environments poses to an increased risk of fallen UAVs impacting people and vehicles on the ground, as well as colliding with manned aircraft in the vicinity of airports. Risk management of UAV flights for safe operations is essential. We proposed a comprehensive risk assessment model for UAV operation in urban environments. Three risk categories (people, vehicles, and manned aircraft) were considered and each risk cost was quantified using collision probability. We adjusted the risk costs in various magnitudes to a same scale and conducted a sensitivity analysis to determine the optimal coefficients of the three risk cost models. We then computed the total risk and generated a risk cost map for path planning. Modified path planning algorithms were used to produce a cost-effective path, and we compared their performances in terms of total risk cost and computational time. Lastly, we performed simulations to validate the feasibility and effectiveness of our proposed risk assessment model. The results show that the risk-cost-based path planning method can generate safer path for UAV operations than the traditional shortest-distance-based method. Our proposed model can be extended to complex urban environments by including more relevant parameters and data.||URI:||https://hdl.handle.net/10356/145809||ISSN:||2169-3536||DOI:||10.1109/ACCESS.2020.3016118||Rights:||© 2020 IEEE. This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given.||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||ATMRI Journal Articles|
Updated on Jun 17, 2021
Updated on Jun 17, 2021
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