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Measuring
Day-to-Day Variability in
Travel Behavior Using GPS Data
INTRODUCTION
Background
Day-to-day variability in travel behavior has been an issue of much interest to travel behavior researchers for several decades. More often than not, travel demand models are estimated on personal travel survey data sets that are collected for a one-day travel period. Researchers and planners have questioned whether a one-day data set captures the full range of travel that is undertaken by an individual as there are many activities (say, personal business, shopping, social visits, medical/dental, etc.) that are not necessarily done on a daily basis.
Despite the recognition of the presence of day-to-day variability in travel behavior, many planners have shied away from conducting multiday personal travel surveys because of the potential ill-effects of survey fatigue and low response rates that are typically attributed to longer survey durations. Then, it may be conjectured that an alternative travel data collection methodology that does not impose undue burden on survey respondents would offer great benefits for planners interested in collecting multiday travel data. The Federal Highway Administration (FHWA) recently conducted a pilot experiment in which one vehicle in each of 100 households in the Lexington, KY area was fit with a Global Positioning System (GPS) unit and a small hand-held computer.
These devices afforded
the opportunity to track the movements of individual vehicles over a target
period of six days, but for which some were tracked as along as eight or nine
days, while minimizing respondent burden. In addition, the GPS-based survey
is presumably more accurate than traditional personal recall surveys because
one may forget to report short, infrequent trips that occur during the day.
The GPS provides the added benefit of capturing route choice, path, and speed
information that is typically very difficult to collect in a traditional personal
recall survey. This research project focused on analyzing day-to-day variability
in travel behavior using the GPS-based data set.
Objectives
The specific objectives
of the research project were to:
Project Scope
The project scope included the following tasks:
The analysis performed
within the scope of this project is predominantly descriptive and aggregate
in nature. As the sample size employed in the experiment was rather small (100
households) and multi-day travel information was obtained for only one vehicle
in each household, it is not possible to estimate statistical models of variability
in travel and report results at a disaggregate level. For example, reporting
results broken down by trip purpose, gender, age group, and household size would
result in such small samples that statistical validity would be significantly
compromised and conclusions could not be drawn. As such, results are documented
in this report mostly at an aggregate level of analysis so that broad insights
into the day-to-day variability in travel behavior could be drawn.
Organization of the Report
Following this introductory chapter, a discussion regarding the importance of measuring and understanding day-to-day variability in travel is provided in the next chapter. The third chapter provides review of the literature on day-to-day variability in travel. The fourth chapter provides a brief overview of the GPS-based travel survey experiment conducted in Lexington, KY. The fifth chapter provides an overall summary description of the data sets and the survey sample obtained from the GPS experiment.
There are three chapters (Chapters 6 through 8) that are dedicated to reporting day-to-day variability in travel behavior found in the GPS-based data sets. These three chapters examine variability in several different trip making characteristics including trip frequencies, travel distances, travel times, and departure/arrival times.
The ninth chapter is a concluding chapter that provides a discussion of the research results and the implications for travel demand measurement and modeling.
