中国民航大学学报 ›› 2019, Vol. 37 ›› Issue (6): 39-45.

• 民用航空 • 上一篇    下一篇

过站航班地面保障服务时间估计

邢志伟1,王超1,罗谦2,魏志强3   

  1. (1. 中国民航大学电子信息与自动化学院,天津 300300;2.中国民用航空局第二研究所,成都 610041;3. 江西省机场集团公司运行监控指挥中心,南昌 330000)
  • 出版日期:2019-12-31 发布日期:2020-01-02
  • 作者简介:邢志伟(1970—),男,辽宁新民人,教授,博士,研究方向为民航装备与系统、机场交通信息与控制.
  • 基金资助:
    国家自然科学基金项目(U1533203)

Ground service time estimation for transit flight

XING Zhiwei 1, WANG Chao1,2, LUO Qian2, WEI Zhiqiang3   

  1. (1. College of Aeronautical Automation, CAUC, Tianjin 300300, China; 2. Second Research Institute, CAAC, Chengdu 610041, China;3. Jiangxi Airports Group Company, Nanchang 330000, China)
  • Online:2019-12-31 Published:2020-01-02

摘要: 为了准确估计过站航班地面保障服务时间,实现航班推出控制的精准化,提出了基于马尔科夫蒙特卡洛(MCMC)的过站航班地面保障服务时间估计方法。根据实际流程和时间建模,将地面保障服务过程抽象为理想化马尔科夫过程。结合蒙特卡洛方法动态模拟各理想化环节的分布,利用皮尔逊卡方拟合方法检验分布的真实性。根据实际流程优化马尔科夫蒙特卡洛网状结构,并通过随机数获得结构的动态参数,由实际作业逻辑关系动态估计过站航班地面保障服务时间。结合国内某中部机场的实际运行数据仿真验证,结果表明:动态方法的平均绝对误差比静态方法少0.8 min,且误差波动较为平稳,从而验证方法的有效性。

关键词: 过站航班, 地面保障服务时间, 动态估计法, 马尔科夫蒙特卡洛, 皮尔逊卡方拟合验证, MCMC 标准差

Abstract: In order to accurately estimate the ground service time of transit flight and realize accurate flight push time control, a time estimation method based on MCMC for the transit flight ground service is proposed. Based on the actual process and time modeling, the ground service process is abstracted into an idealized Markov process. The Monte Carlo method is used to dynamically simulate the distribution of idealized links, and the Pearson chisquare fitting method is used to test the authenticity of the distribution. According to the actual process, the MCMC network structure is optimized, the dynamic parameters of the structure are obtained by random numbers,and the ground service time of the flight is dynamically estimated from the actual operational logic relation.Combined with the actual operation data of an airport in Central China, it is shown that the mean absolute error of the proposed dynamic method is 0.8 min shorter than that of the static method, and the error fluctuation is relatively more stable, thus proving the validity of the method.

Key words: transit flight, ground service time, dynamic estimation method, MCMC, Pearson chi fitting test, MCMC standard deviation

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