基于空闲时间窗和多Agent的A-SMGCS航空器滑行路由规划

先进场面活动引导与控制系统(A-SMGCS)中的航空器滑行路由规划是一个典型NP难题。为解决航空器滑行路由规划的优化性和计算量之间的矛盾,提出一种基于空闲时间窗的路由规划方法,并利用多Agent系统(MAS)进行算法求解。首先,建立滑行资源图以对场面滑行区进行建模。其次,按照航班计划为航空器设置滑行优先级,并按优先级顺序依次规划路由,后规划的路由不破坏已有路由,即利用滑行路段的空闲时间窗进行规划。每次只需为一架航空器规划滑行路由,降低了问题的求解难度;通过搜索空闲时间窗获得路由使场面交通均衡分布,保证了路由规划的整体优化性。分析了空闲时间窗特性,指出空闲时间窗的可达性条件和避免同步资源交换冲突的条件。最后,设计MAS,把建立、维护和搜索空闲时间窗图的复杂集中式求解过程简化为通过路由管理Agent,航空器Agent和资源节点Agent相互协作实现对场面路由规划问题的分布式求解。仿真结果表明,设计的MAS能够快速找到空闲时间窗中的最优解;与固定预选滑行路径算法相比,航空器的平均滑行时间显著减少,最多可以节省19.6%的滑行时间。

Aircraft taxi routes planning based on free time windows and multi-agent for A-SMGCS

Aircraft taxi routes planning for advanced surface movement guidance and control system (A-SMGCS) is a typical NP-Hard problem. To solve the contradiction between taxi routes planning optimization and the great amount of calculation, a taxi routes planning method based on free time windows is proposed and a multi-agent system (MAS) is designed to implement the algorithm. Firstly, a taxi resource graph is established to model airport taxi area. Then, any aircraft is appointed a priority according to flight schedule. Aircraft taxi route is planned sequentially according to the order of aircraft priority. Aircraft can only use free time windows of a taxiway to plan taxi route and the previous planned taxi routes cannot be destroyed. The difficulty of solving aircraft taxi routes planning problem is reduced to that we only need to find a single aircraft taxi route every time. Overall optimization of the taxi route planning is guaranteed because airport surface traffic is balanced through searching free time windows to get taxi routes. Finally, since it is a complex centralized solution process to establish, maintain and search a free time window graph, an MAS is established which makes it simplified through the route management Agent, aircraft Agent and resource node Agent, collaboratively to solve aircraft taxi route planning problem distributively. Simulation results show that the MAS can quickly find the optimal solution of free time windows. Aircraft average taxiing time decreases significantly and up to 19.6% aircraft taxiing time can be saved compared to preselection fixed-path set algorithm.