Using GPS data to understand driving behavior
Authors: Joe Grengs, Xiaoguang Wang, Lidia Kostyniuk.
This paper investigates driving behavior based on GPS data collected by the University of Michigan Transportation Research Institute (UMTRI). The database contains driving data for 78 drivers living in the Detroit metropolitan region in 2004, with automobile use tracked on a day-to-day basis for four weeks, with geographic positions captured every second by GPS. We combine the GPS data with geocoded street addresses of business establishments, land-use polygons, aerial photographs, census data, and road attributes. The paper has two main objectives. The first is to explain methodological challenges of converting an enormous set of geocoded data points into a meaningful database that describes the complexity of trips and tours. The second objective is to describe in a detailed manner the driving characteristics of a single driver over the course of a month of driving, to illustrate the kinds of valuable lessons that transportation analysts can learn from GPS data. We find that common travel patterns are more complex than generally understood from traditional travel surveys and that transportation engineers and planners can benefit from GPS data used as a new technology for travel study.