Travel time studies with global positioning and geographic information systems: an integrated methodology

Abstract The paper describes a new methodology for performing travel time studies using global positioning system (GPS) and geographic information system (GIS) technologies. It documents the data collection, data reduction, and data reporting procedures, as well as analyses that illustrate the capabilities of the GPS/GIS methodology. The data collection procedure uses GPS receivers to automatically collect time, local coordinates, and speed at regular sampling periods, for example every one second. The data reduction procedure filters and aggregates GPS data to compute travel time and speed along highway segments. The data reporting procedure uses a GIS-based management information system to define queries, tabular reports, and color coded maps to document travel time data along these highway segments. These procedures have been implemented in three metropolitan areas in Louisiana: Baton Rouge, Shreveport, and New Orleans. In these cities, more than 180,000 segment travel time and speed records were derived between 1995 and 1996 from nearly three million GPS data points collected on 30,000 miles of travel time runs along 300 miles of urban highways. The three analyses included in the paper to assist in the process of understanding the GPS/GIS methodology are the following: segment lengths, sampling rates, and central tendency. The segment length analysis examines the effect of using different highway segment lengths and shows that relatively short segments (0.2–0.5 miles long) are needed to detect localized traffic effects. These traffic disturbances become visible only when segment lengths are at most half the length of the associated disturbance. This means that traditional link-based segments, which are typically longer than 0.5 miles, are not sufficient to characterize localized effects properly. The sampling rate analysis addresses the effect of collecting GPS data at different sampling periods and shows that for a segment to have GPS data associated with it, the GPS sampling period should be smaller than half the shortest travel time associated with the segment. The analysis also shows a tradeoff between sampling rates and segment speed reliability, and emphasizes the need for even shorter GPS sampling periods (1–2 s) in order to minimize errors in the computation of segment speeds. The central tendency analysis compares harmonic mean speeds and median speeds and shows that median speeds are more robust estimators of central tendency than harmonic mean speeds.