基于涟漪扩散算法的航空器滑行路径优化

Optimization of Aircraft Taxiing Path Based on Ripple Spreading Algorithms

针对当前机场场面交通拥挤、航班不正常率日益增高的现状,研究了航空器滑行路径优化问题。结合场面运行规则,提出基于真实滑行路径的多目标涟漪扩散算法以优化进离港航班的滑行路径。构建基于冲突解决的场面优化模型,以天津滨海国际机场为例进行20架航班的仿真验证,将通过广播式自动相关监视系统采集的真实路径集合与改进的涟漪扩散算法获得的帕累托最优路径集合进行比较分析。结果表明:与真实路径相比,20架航班的总滑行时间从7107.1s降至6852.1s,减少255s,总完成时间从7153.2s降至6894.1s,减少259.1s,共6架航班的滑行时间得到明显优化。通过案例仿真结果发现,通过改进的涟漪扩散算法得到的帕累托最优滑行路径以符合真实滑行规则为前提,可以有效的优化机场场面滑行路径。

In response to the current situation of airport surface traffic congestion and increasing flight irregularity rates,the optimization of aircraft taxiing paths was studied in this paper.Combined with the surface operation rules and based on the real taxi path,an improved multi-objective ripple spreading algorithm was used to optimize the taxi path of the arriving and departing aircraft.A scene optimization model was built based on conflict resolution to avoid possible conflicts in the scene and judge the effect of path optimization.Twenty flights were simulated in Tianjin Bin⁃hai International Airport.The real path set collected by ADS-B and the Pareto optimal path set obtained by the im⁃proved ripple diffusion algorithm were compared and analyzed.The results show that,compared with the real path set,the total taxiing time of 20 flights decreases from 7107.1s to 6852.1s with a reduction of 255s,the total comple⁃tion time decreases from 7153.2s to 6894.1s with a reduction of 259.1s,and the taxiing time of 6 flights is signifi⁃cantly optimized.Through the simulation results,it is found that the pareto optimal taxiing path obtained by the im⁃proved ripple spreading algorithms on the premise of meeting the real taxiing rules can effectively optimize the airport scene taxiing path.