系统仿真学报 ›› 2019, Vol. 31 ›› Issue (8): 1548-1554.doi: 10.16182/j.issn1004731x.joss.17-0302

• 仿真建模理论与方法 • 上一篇    下一篇

离港值机排队聚集规律及队列模型研究

邢志伟1, 蒋骏贤1, 罗晓2, 罗谦2,*, 杨扬1,2   

  1. 1. 中国民航大学电子信息与自动化学院,天津 300300;
    2. 中国民航局第二研究所工程技术研究中心,四川 成都 610041
  • 收稿日期:2017-06-30 修回日期:2017-09-27 发布日期:2019-12-12
  • 作者简介:邢志伟(1970-),男,辽宁沈阳,博士后,教授,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(U1533203),中央高校基本科研业务费资助项目(201929)

Study on Model and Accumulation Rule for Departure Check-in Queues

Xing Zhiwei1, Jiang Junxian1, Luo Xiao2, Luo Qian2,*, Yang Yang1,2   

  1. 1. School of Electronic Information and Automation, Civil Aviation University Of China, Tianjin 300300, China;
    2. Engineering Technology Research Center, The Second Research Institute of CAAC, Chengdu 610041, China
  • Received:2017-06-30 Revised:2017-09-27 Published:2019-12-12

摘要: 前期结合人类行为动力学研究了离港旅客在航站楼的聚集规律,基此研究了国内离港旅客在非全开放值机岛的值机排队长度变化规律。引入时序概念对排队过程做离散化处理,得到了蛇形排队形式下的队列长度马尔科夫链,以单航班离港旅客聚集模型预测每个时序的聚集速率,并通过选定值机柜台服务率的合适值,建立了开放固定数量值机柜台情况下的多个邻近航班值机排队长度模型。通过对比模型预测的排队长度与实际数据,证明队列长度模型有较高预测精度以及排队聚集规律的合理性。

关键词: 航空运输, 队列长度模型, 离散化分析, 值机排队过程, 聚集规律

Abstract: The aggregation rule of departure passengers in the terminal building is studied in combination with human behavior dynamics. Based on this, the change rule of queuing length of departing passengers on non-full-open check-in island is studied. The queuing process is discretized by introducing the concept of time series, and the queue length Markov Chain is obtained in the serpentine queuing form. Then, the aggregation rate of each time series is predicted by the single-flight departure passenger aggregation model. By selecting the appropriate value of the check-in counter service rate, the check-in queuing length model of multiple adjacent flights is established under the circumstance of opening fixed number check-in counter. By comparing the queuing length predicted by the model with the actual data, relatively high prediction accuracy of the queuing length model and the rationality of queuing aggregation are proved.

Key words: air transportation, queuing length model, discretization analysis, check-in queuing process, accumulation rule

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