Planning Aircraft Taxiing Trajectories via a Multi-Ojective Immune Optimisation
Airport operations include departure sequencing, arrival sequencing, gate/stand allocation and ground movements (taxiing). During the past few decades, air traffic at major airports has been significantly increased and is expected to be so in the near future, which imposes a high requirement for more efficient cooperation across all airport operations. A very important element of this is an accurate estimation of the ground movement, which serves as a link to other operations. Previous researches have been concentrated on the estimation of aircraft taxi time. However, such a concept should be stretched more than just predicting time. It should also be able to estimate the associated cost, e.g. fuel burn, for it to achieve such an expected time. Hence, in this paper, an immune inspired multi-objective optimisation method is employed to investigate such trade-offs for different segments along taxiways, which leads to a set of different taxiing trajectories for each segment Each of these trajectories, on the one hand, provides an estimation of aircraft taxi time, and on the other hand, has great potential to be integrated into the optimal taxiway routing and scheduling process in a bid to find out the optimal taxiing not only in terms of reducing total taxi time but also in terms of lowering fuel consumption.
multi-objective immune algorithm aircraft ground movement optimal taxiing trajectories
Jun Chen Paul Stewart
School of Engineering University of Lincoln, Brayford Pool Lincoln, United Kingdom
国际会议
2011 Seventh International Conference on Natural Computation(第七届自然计算国际会议 ICNC 2011)
上海
英文
2282-2287
2011-07-26（万方平台首次上网日期，不代表论文的发表时间）