Aircraft taxiing in large airports is often delayed by traffic conflicts. The increased fuel consumption and pollutant emission lower the efficiency of airport surface operation and bring potential safety hazards. Previous studies on route planning for surface taxiing seldom involve refined delay analysis under different traffic conflict types and discussions on route planning at airports with various environmental parameters and under diverse aircraft types. In this study, dynamic models of crossing, head-on, and trailing conflicts during aircraft taxiing were constructed, and delays of these three conflict types were determined. The shortest route set of restricted routing was determined by the Yen algorithm according to the topological network, conflict-induced delay, and spatial distributions of taxiing at airports. Considering the three optimization objects, the aircraft route planning was optimized and determined from the shortest route set according to the differences in the environmental parameters and aircraft types. Experiment results show that the proposed method achieves 9.6–12.1% higher route planning precision in all traffic periods compared with previous route planning with considerations to taxiing conflict. This method also provides support to the dynamic decision of airport operation and control departments according to the environment and performance of aircraft.

飞机在大型机场滑行时常因交通冲突而延误。油耗和污染物排放的增加，降低了机场地面运行效率，带来了安全隐患。以往关于地面滑行路线规划的研究很少涉及不同交通冲突类型下的精细延迟分析，以及在不同环境参数和不同飞机类型下对机场路线规划的讨论。本研究构建了飞机滑行过程中交叉、迎面和尾随冲突的动态模型，并确定了这三种冲突类型的延误。根据拓扑网络、冲突引起的延迟和机场滑行的空间分布，由Yen算法确定受限路由的最短路线集。考虑到三个优化对象，根据环境参数和飞机类型的差异，从最短航线集优化确定飞机航线规划。实验结果表明，与之前考虑滑行冲突的路线规划相比，该方法在所有交通时段的路线规划精度均提高了 9.6-12.1%。该方法还为机场运行和控制部门根据飞机所处环境和性能动态决策提供了支持。与之前考虑滑行冲突的路线规划相比，所有交通时段的路线规划精度提高了 1%。该方法还为机场运行和控制部门根据飞机所处环境和性能动态决策提供了支持。与之前考虑滑行冲突的路线规划相比，所有交通时段的路线规划精度提高了 1%。该方法还为机场运行和控制部门根据飞机所处环境和性能动态决策提供了支持。