Risk Assessment Model for UAV Cost-Effective Path Planning in Urban Environments

被引:60
作者
Hu, Xinting [1 ]
Pang, Bizhao [2 ]
Dai, Fuqing [1 ]
Low, Kin Huat [3 ]
机构
[1] Civil Aviat Univ China, Sch Air Traff Management, Tianjin 300300, Peoples R China
[2] Nanyang Technol Univ, Air Traff Management Res Inst, Singapore 637460, Singapore
[3] Nanyang Technol Univ, Sch Mech & Aerosp Engn, Singapore 639798, Singapore
基金
国家重点研发计划;
关键词
Atmospheric modeling; Path planning; Urban areas; Risk management; Unmanned aerial vehicles; Computational modeling; Aircraft; Unmanned aerial vehicle; risk assessment model; risk cost map; path planning; urban environments;
D O I
10.1109/ACCESS.2020.3016118
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:150162 / 150173
页数:12
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