Measuring Truck Travel Time Reliability Using Truck Probe GPS Data. Issue 2 (3rd March 2016)

• Record Type: Journal Article
• Authors: Wang, Zun; Goodchild, Anne; McCormack, Edward
• Is Part Of: Journal of intelligent transportation systems. Volume 20:Issue 2(2016)
• Page Start: 103
• Page End: 112
• Publication Date: 2016-03-03
• Subjects: Coefficient of Variation -- Correlation -- GPS Spot Speed Distribution -- Truck Probe GPS Data -- Truck Travel Time Reliability; Intelligent transportation systems -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.312
• DOI: 10.1080/15472450.2014.1000455
• Languages: English
• ISSNs: 1547-2450

Abstract

Abstract : Truck probe data collected by global positioning system (GPS) devices has gained increased attention as a source of truck mobility data, including measuring truck travel time reliability. Most reliability studies that apply GPS data are based on travel time observations retrieved from GPS data. The major challenges to using GPS data are small, nonrandom observation sets and low reading frequency. In contrast, using GPS spot speed (instantaneous speed recorded by GPS devices) directly can address these concerns. However, a recently introduced GPS spot-speed-based reliability metric that uses speed distribution does not provide a numerical value that would allow for a quantitative evaluation. In light of this, the research described in this article improves the current GPS spot speed distribution-based reliability approach by calculating the speed distribution coefficient of variation. An empirical investigation of truck travel time reliability on Interstate 5 in Seattle, WA, is performed. In addition, correlations are provided between the improved approach and a number of commonly used reliability measures. The reliability measures are not highly correlated, demonstrating that different measures provide different conclusions for the same underlying data and traffic conditions. The advantages and disadvantages of each measure are discussed and recommendations of the appropriate measures for different applications are presented.