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Classification of tours in the U.S. National Household Travel Survey through clustering techniques

机译:通过聚类技术对美国全国家庭旅行调查中的旅行进行分类

摘要

Tours 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 secondary tours within the travel day, and tours dominated by the working activity. Their relevance on a modeling and policy viewpoint is discussed
机译:越来越多地将旅行视为观察流动性行为的适当单位,并且是支撑基于当代活动的建模方法的关键思想之一。确定旅行的类型将使建模者和决策者都受益,他们将努力采取更具针对性的行动,以促进对环境无害的旅行选择。已经提出了基于活动种类的不同的先验分类,从经验的角度来看,没有一个分类显然是可取的。本文采用一种补充方法,并通过对旅行团进行聚类分析来定义数据驱动的细分,这些旅行团是从美国国家调查的旅行记录中得出的。最后,对每个集群进行社会经济表征,以将旅行者的个人资料与特定类型的旅行联系起来。因此,确定了四个主要的旅行团:年轻人进行的强制性活动的非工作旅行,老年人或退休人员的旅行,旅行日内的短期和次要旅行以及以工作活动为主的旅行。讨论了它们与建模和策略观点的相关性

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  • 作者

    Pirra Miriam; Diana Marco;

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  • 年度 2016
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