Classification of Tours in the U.S. National Household Travel Survey through Clustering Techniques

Miriam Pirra, Marco Diana
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引用次数: 8

Abstract

AbstractTours are increasingly being considered as an appropriate unit of observation of mobility behaviors and are one of the key ideas underpinning contemporary activity-based modeling approaches. Identifying typologies of tours would benefit both modelers and decision makers, striving to set up more tailored actions aimed at promoting environmentally benign travel choices. Different a priori classifications based on activity kinds have been proposed, none of which seems clearly preferable on empirical grounds. This paper takes a complementary approach and defines a data-driven segmentation through a cluster analysis of tours that were derived from the trip records from a United States national survey. The socioeconomic characterization of each cluster is finally carried out to link travelers’ profiles with specific kinds of tours. Four main tour clusters have thus been identified: nonwork tours for compulsory activities done by young individuals, tours done by elder or retired persons, short and second...
利用聚类技术对美国家庭旅游调查中的旅游进行分类
图被越来越多地认为是观察移动行为的适当单位,是支撑当代基于活动的建模方法的关键思想之一。确定旅游的类型将有利于建模者和决策者,努力建立更有针对性的行动,旨在促进环境友好的旅游选择。根据活动种类提出了不同的先验分类,但从经验的角度来看,似乎没有一种分类更可取。本文采用了一种补充方法,并通过对来自美国全国调查的旅行记录的旅行进行聚类分析,定义了数据驱动的分割。最后对每个集群的社会经济特征进行分析,将旅行者的个人资料与特定类型的旅游联系起来。因此,确定了四种主要的旅游集群:由年轻人进行的强制性活动的非工作旅游,由老年人或退休人员进行的旅游,短期旅游和次级旅游。
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