摘要
可变滑行时间是评估机场场面交通流特性的重要指标,影响机场运行效率、旅客满意度以及污染排放问题。针对国内某大型枢纽机场,根据元胞自动机原理和交通流拥塞规律,将机场滑行区域视作由节点和链路构成的网络拓扑,以滑行规则和飞机之间的冲突作为约束条件。构建飞机离场交通流的模型,使用蒙特卡洛算法得出最优滑行路径,结合航班数据进行仿真分析。研究结果表明,该模型减少了离港飞机的滑行等待时间,滑行效率提高了9.8%,充分调度和合理分配了机场地面资源。
Variable taxiing time is an important indicator to the characteristics of the airport traffic flow assessment, which affects the airport operating efficiency, the passenger satisfaction for the airline and the pollution emissions. For a large hub airport, according to the principle of cellular automata and the congestion of traffic flow, the airport taxiing area is regarded as the network topology of nodes and links, and the conflict between taxi rules and aircraft is taken as the constraint. The simulation analysis is carried out on the basis of constructing the model of airplane departure traffic flow, using Monte Carlo algorithm to get the optimal taxi path, combining the flight data. The results show that this model reduces the taxiing waiting time of the departing aircraft, and the taxiing efficiency is improved by 9.8%, and fully dispatches and rationally allocates airport ground resources.
作者
邢志伟
徐铭怡
罗晓
罗谦
Xing Zhiwei;Xu Mingyi;Luo Xiao;Luo Qian(College of Electronic Information and Automation,Civil Aviation University of China,Tianjin 300300,China;Engineering Technology Research Center,The Second Research Institute of CAAC,Chengdu 610041,China)
出处
《系统仿真学报》
CAS
CSCD
北大核心
2020年第2期323-331,共9页
Journal of System Simulation
基金
国家自然科学基金(U1533203)
关键词
可变滑行时间
离港交通流
机场网络图
元胞自动机
蒙特卡洛算法
运行优化
variable taxiing time
outbound traffic flow
airport network diagram
cellular automata
Monte Carlo algorithm
operational optimization