机场净空区无人机扰航监管演化博弈研究

为确定无人机(UAV)操控者不安全飞行的影响因素及其演化路径,提升对机场净空区无人机扰航的监管水平,综合采用演化博弈理论和系统动力学(SD),探讨无人机扰航监管中行为选择的情境条件。从机场净空区无人机扰航事件的成因出发,构建机场安全监管部门和无人机操控者的博弈支付矩阵,分析博弈系统均衡点的局部稳定性;在此基础上建立SD模型,仿真分析不同参数变化对演化趋势和结果的动态影响。结果表明:对无人机操控者不安全飞行加强追踪、加大处罚力度,能够增加无人机安全飞行的概率;从监管涉及的主体和对象入手提高安全监管的有效性,有利于长效促进无人机安全飞行,减少机场净空区无人机扰航事件。

Evolutionary game research of supervision on unmanned aerial vehicle interference with flights in airfield clearance area

In order to determine the influencing factors and evolution paths of the unsafe flight of the UAV operator,and to improve the supervision level on the UAV interference with flights in airfield clearance area,the situational conditions of behavior selection were analyzed through the evolutionary game theory and SD. Based on the cause analysis of UAV interference with flights,the game pay matrix of airport safety regulator and UAV operator was built,and the local stability of equilibrium point of game system was analyzed. On this basis,a SD model was established to simulate and analyze the dynamic effects of different parameters on evolution results. The results show that it is possible to increase the probability of UAV safe flight by increasing the intensity of tracking of and punishment for UAV operator’s unsafe flight,and that the effectiveness of safety supervision can be improved from the perspective of the subject and object involved in supervision,which can promote the UAV safe flight and reduce the disturbance of UAV in the airport clearance area in the long run.