基于K-means的航空旅客空间行为模式研究

Research on Air Spatial Behavior Patterns of Passengers Based on K-means

航站楼内旅客空间行为模式研究,对航站楼满足不同属性旅客需求、提升服务水平至关重要。研究采用K-means聚类算法,对南京禄口国际机场T2航站楼国内出发旅客的空间选择行为进行大致细分。将国内出发旅客的行为路径聚类为5种空间行为模式,并分析了旅客性别、年龄、收入等基本属性在这5种空间行为模式上的不同分布,说明机场航站楼商业设施对女性旅客的吸引力更强;中青年旅客容易在非职能区域发生停留行为进而引发消费活动;未在机场乘过机的旅客对航站楼各类商业设施有强烈的兴趣;收入水平与旅客对机场非职能区域的选择概率之间呈正相关关系。研究通过分析航空旅客空间行为模式差异,对南京禄口国际机场提升机场管理水平和空间布局优化都有一定的实用价值。

The study of passenger spatial behavior patterns in the terminal building is essential for the terminal managers to meet the needs of passengers with different attributes and improve service levels. The research adopts the K-means clustering method to subdivide spatial selection behaviors of domestic departing passengers of Nanjing Lukou International Airport Terminal 2. In the process of segmenting passengers, it clusters behavioral paths of domestic departing passengers into five types of spatial behavior patterns and the different distributions of the basic attributes such as gender, age and income of passengers in these five types are analyzed. The research also shows that commercial facilities in terminals are more attractive to female passengers;young and middle-aged passengers are prone to stay in non-functional areas and engage in consumption activities;passengers who have not taken flights before have strong interest in various commercial facilities in terminals;and there is a positive correlation between income levels and passengers' choice probabilities of non-functional areas of terminals. Therefore, study on the differences in air passenger spatial behavior patterns has a practical value to improve the management level of Nanjing Lukou International Airport and optimize spatial layout.