多Agent的航空器滑行策略优化

快速发展的民航事业导致很多机场容量不足。为缓解大型机场交通拥堵的现状,研究了航空器滑行策略优化问题。滑行路径优化是指在特定的时间段内,根据机场资源信息和地面运行管理系统对进离场航空器在跑道和停机位之间的距离进行优化管理。通过深入剖析机场地面的网络结构,综合考虑滑行冲突、地面运行规则等因素,提出了多Agent滑行策略优化方法,该方法提升了机场资源利用率;基于地面网络链路结构的概念,建立了航空器滑行策略优化模型;结合多Agent的基本理论,设计了跑道出口选择概率函数和多Agent系统滑行路径优化结构,以寻求航空器的最优滑行路径。以国内某大型机场的实际情况为研究背景进行了航空器滑行策略实验,结果表明,与以往的算法相比,多Agent滑行策略优化方法的效果更为显著。设置跑道口的速度和同一交叉口航空器的最小间隔距离,通过对跑道出口的选择和Agent间的交互协商,航空器能够对原滑行路径进行有效调整,并缩短其在机场场面上的滑行时间。与最短路径算法相比,多Agent滑行策略方法在航空器的总滑行距离、航空器在滑行道上的密度以及平均等待时间方面的优化效果更好,且其对滑行道资源的分配更合理。其中,航空器在节点处的平均等待时间减少了8.26%。所提策略可有效缓解机场交通拥堵的现状,提高场面运行效率,对减少航空器延误和保障机场的运营安全具有重要意义。

Optimization of Aircraft Taxiing Strategy Based on Multi-agent

The rapid development of civil aviation has led to the shortage of capacity in many airports.In order to alleviate the current situation of large airports,the problem of aircraft taxiing strategy optimization was studied.Taxiing path optimization is the optimal management of the distance between the runway and the gate of the arriving and departing flights according to the airport resource information and the ground operation management system during a specific time period.Through in-depth analysis the structure of the airport ground network,comprehensive consideration of factors such as taxiing conflict and ground operation rules,a multi-agent taxiing strategy optimization method is proposed to improve the utilization rate of airport resources.The aircraft taxiing strategy optimization model is established,based on the concept of ground network link structure.Combined with the basic theory of multi-agent,the selection probability function of runway exit and the multi-agent path optimization algorithm are designed to seek the optimal taxiing path of aircraft.The aircraft taxiing strategy experiment is carried out,based on the actual situation of a large domestic airport.The results show that the optimization effect of multi-agent taxiing strategy is more signifi-cant compared with the previous algorithms.Set the speed at the runway entrance and the minimum interval distance of the aircraft at the same intersection.the aircraft can effectively adjust the original taxiing path and shorten the taxiing time on the airport scene through the interaction of the runway exit selection and the interactive negotiation among agents.The total taxiing distance of the aircraft,the density and the average waiting time of the aircraft on the taxiway are significantly better than the contrast optimization algorithm,and the taxiway resource allocation is more reasonable compared with the shortest path algorithm.And the average waiting time of aircraft at the node is reduced by 8.26%.Alleviate the current situation of airport traffic congestion and improve the operating efficiency of scene,which is of great significance for reducing aircraft delay and airport operation safety.