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基于元胞自动机的航空器起降间隔研究(研究生论坛)
引用本文:杨凯,康瑞. 基于元胞自动机的航空器起降间隔研究(研究生论坛)[J]. 四川大学学报(工程科学版), 2016, 48(Z2): 127-134
作者姓名:杨凯  康瑞
作者单位:四川大学计算机学院图形图像所,中国民航飞行学院 空中交通管理学院
基金项目:国家空管科研课题资助项目(GKG201403004)
摘    要:为研究机场跑道、滑行道结构、机型比例对航空器起降间隔的影响,在分析跑道、滑行道运行方式基础上,细化航空器起飞、着陆占用跑道滑跑、滑行过程,定义航空器元胞尺寸和速度位置演化规则,构造航空器滑行元胞自动机模型。计算机数值模拟得到滑行道位置、机型比例、机型组合改变时,起降间隔、间隔标准差的变化趋势。仿真结果表明,滑行道距离跑道头越近,起飞间隔越小;滑行道接近着陆航空器减速滑跑结束位置时,着陆间隔最小;滑行道距跑道头450m-800m时,平均间隔最小为135s, 800m-900m时,间隔标准差最小为20.9,与全中型机相比,全小型机时平均间隔减少17.8%,间隔标准差减少42.3%。该模型能量化机型、滑行道位置等关键因素对起降间隔的影响,能为提高机场吞吐量提供技术支持。

关 键 词:空中交通管理;元胞自动机;起降间隔;场面运行
收稿时间:2015-09-01
修稿时间:2016-02-03

Research on Taking off and Landing Space of Aircrafts Based on Cellular Automaton
Yang Kai and. Research on Taking off and Landing Space of Aircrafts Based on Cellular Automaton[J]. Journal of Sichuan University (Engineering Science Edition), 2016, 48(Z2): 127-134
Authors:Yang Kai and
Abstract:Considered the influence of airport runway taxiway structures and the proportion of the aircraft type on the taking off and landing space, based on analyzing the operation mode of the runway and taxiway, detailed aircraft rolling and taxiing procedure, defined the size of aircraft cell and evolution rules of speed and position ,an aircraft taxiing cellular automata model was built. The change trends of taking off and landing space and space standard deviation were obtained through computer numerical simulation by setting different values for parameters such as the taxiway location, aircraft type, combination of landing and taking off. The simulation results showed that the taking off space increased with the distance between runway threshold and taxiway increasing. If the taxiway was near the landing aircraft rolling end position, the landing space was minimum. If the distance from the runway threshold to taxiway was 450m-800m, average space for a minimum was 135s. If the distance was 800m-900m, space standard deviation was minimum of 20.9. Compared with situation of 100% medium aircraft, if proportion of small aircraft was 100%, the average space reduced 17.8% and space standard deviation reduced 42.3%. The model quantified the key factors acting the taking off and landing space, such as aircraft type, taxiway location, provided technical support for improving the throughput of airport.
Keywords:air traffic management   cellular automaton   taking off and landing space   surface operations
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