Affiliations: [a] Air Traffic Control and Navigation College, Air Force Engineering University, Xi’an, China
| [b]
Xijing University, Xi’an, China
| [c] Computer Science and Engineering College, Anhui University of Science and Technology, Huainan, China
Correspondence:
[*]
Corresponding author. Gan Xusheng, Air Traffic Control and Navigation College, Air Force Engineering University, Xi’an, China. E-mail: ganxusheng123@163.com.
Abstract: To provide real-time safety assessment for low-altitude unmanned aerial vehicle (UAV) air traffic management, and to ensure the UAVs safe operation in low-altitude airspace, a risk assessment framework is proposed. It considers the accidents probability and the accidents hazards. Firstly, accidents probability model based on the System Theoretic Process Analysis-Bayesian Network (STPA-BN) algorithm is built. Potential system hazards are effectively identified and analyzed through the STPA process. The accidents cause identified based on the STPA process is taken as the root node. The relevant failure probability table is given respectively. It constitutes the BN used to analyze the system accidents probability. This method uses a combination of qualitative and quantitative methods to calculate the accidents probability. Then, based on the UAV fall model, considering the uncertainty of the UAV operation process, the UAV fall point distribution is determined based on the Monte-Carlo method, and the impact area of the fall is calculated. Thus the system risk value is obtained. Finally, through case analysis, the validity and rationality of the proposed risk assessment framework are verified.
Keywords: Unmanned aerial vehicle system, air
traffic management, risk assessment
