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The proliferation of devices equipped with Global Positioning System (GPS) technologies such as smartphones and in-vehicle navigation systems has given rise to an exciting opportunity to better understand traveler behavior. Devices providing the timestamped location of travelers at frequent intervals provide details on trip origins and destinations (OD), departure times, route/mode choices, and travel times. In this paper, we utilize such a GPS data set to develop visualization and analysis methods that allows transportation professionals to better understand the nature of congestion on specific road segments. This novel data set was obtained from INRIX, which operates a vast network of traffic sensors, and includes all available trips in Maryland for the month of July 2015: a total of 4.8 million trips, each with potentially thousands of waypoints. A real-world application was generated to illustrate the benefits of the visualization and analysis methods in understanding vehicular travel patterns.
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Petrone et al. (2018) studied this question.
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