Travel to Common Destinations: An Exploration Using Multiday GPS Data. Issue 1 (January 2014)

• Record Type: Journal Article
• Authors: Dill, Jennifer; Broach, Joseph
• Is Part Of: Transportation research record. Volume 2413:Issue 1(2014)
• Page Start: 84
• Page End: 91
• Publication Date: 2014-01
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.3141/2413-09
• Languages: English
• ISSNs: 0361-1981

Abstract

Decisions involving common travel patterns over time, such as traveling to and from the same destination multiple times per week or month, are likely different from decisions involving unique circumstances. Understanding of travel decisions involving common destinations could help with the development of programs, services, and infrastructure aimed at changing travel behavior. This paper explores how common travel destinations can be defined through the use of stated and revealed data (a 5-day GPS trip log). Revealed common destinations were identified through hierarchical agglomerative clustering. A 200-m maximum threshold for defining clusters was found to be appropriate in this context. Three ways of defining "common" were explored through the use of the revealed GPS data on the basis of the number of trips that ended at the cluster or the number of days that trips ended at the cluster. The analysis of travel to and from the revealed common destinations identified some potential for variability that depended on the definition. Common destinations defined by stated data (participant survey data collected before the GPS data were collected) were linked to 46% of all nonhome trip ends. The availability of these stated common destinations will reduce the need to collect information on trip purpose through the use of follow-up surveys or through the imputation of trip purpose with land use data when GPS travel surveys are processed. The analysis also provided insight into the usefulness of multiday data, thus confirming other research.