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Measuring Day-to-Day Variability in
Travel Behavior Using GPS Data


Data Description

The field experiment yielded a total of four databases containing personal travel data and vehicle movement profiles. The four databases are as follows:

In addition to the detailed travel-related information, data was also available for selected socio-economic variables. Information on household size, number of children under 16 years, vehicle ownership, number of licensed drivers, age and gender of drivers, and household income were also available in the data sets.

As this report focuses on day-to-day variability in travel, the recall data set is not used within the scope of this study. The recall data set provides travel behavior information only for a 24-hour period and is therefore not suitable for studying day-to-day variability in travel. As such, the analysis done for this study utilized the PDA, GPS, and match data sets.

Sample Description

A total of 100 households participated in the Lexington, KY GPS experiment. Data collection devices were installed in one vehicle for each household. Any licensed driver in the household was permitted and encouraged to use the GPS-fitted vehicle.

Within the context of this study, one driver in each household was identified as a primary driver. The driver who provided travel information for the most number of days in each household was chosen as the primary driver. If two household members provided travel information for the same number of days, then the driver that made the larger number of number of trips using the GPS-fitted vehicle was designated as the primary driver for each household. Thus, there are 100 primary drivers in the final sample used for analysis in this study.

It is to be noted that the sample of primary drivers used in this study may differ from that used in other publications [Zhou and Golledge, 2000; Battelle, 1997; and Murakami and Wagner, 1999] and this is likely to contribute to differences in analysis results. In this study, the desire to maximize the amount of travel information available for day-to-day variability analysis motivated the use of number of days and trip frequency as the criteria for identifying primary drivers. Information on the socio-economic and demographic characteristics of the 100 primary drivers identified in this study is shown in Table 1.

For the sample for which information is available, it is found that their characteristics are consistent with expectations. The average household size is 2.94 persons per household with more than 50 percent of the households having 3 or more persons. 28 households reported incomes less than $35,000 per year. The average car ownership is 2.17 vehicles per household with most of the households having 2 or more cars which is consistent with the household size distribution. There is an even split in the sample between males and females. Battelle [1997] reports that most of the drivers are well educated with about 40 percent having a college education. Only 10 primary drivers are less than 26 years of age, while 12 drivers are greater than 65 years of age. 40 percent of the households reported having at least one child less than 16 years of age. Based on these characteristics, one can see that the sample is a rather selective one with households exhibiting mature lifecycle stages, greater household sizes, and higher car ownership levels.

Table 1. Descriptive Characteristics of Survey Sample

Characteristic Value (N=100)
Mean household size 2.94
    1 person hhld 13
    2 person hhld 35
    3 person hhld 15
    4+ person hhld 37
Income Level

   Low (< $35K)


   Medium ($35K - $75K)


   High (> $75K)

Mean Vehicle Ownership 2.17
    1 car hhld 21
    2 car hhld 47
    3 car hhld 27
    4+ car hhld 5
    Male 44
    Female 42
Mean Age (in years) 46.3
    Less than 26 years 10
    26 to 45 years 32
    46 to 55 years 23
    56 to 65 years 9
    Greater than 65 years 12
No. of Children <16 years 0.68
    0 child hhld 60
    1 child hhld 21
    2 child hhld 11
    3 child hhld 7
    4+ child hhld 1

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