Impact of the Degree of Data Aggregation on the Travel Time Measurement-based Studies

Abstract

This study investigates the impact of different Intelligent Transportation System (ITS) technologies and various degrees of data aggregation on travel time measurements. The study was motivated by the belief that commonly conducted travel-time-based before-and-after studies can deliver misleading results if not enough attention is given to the data collection and aggregation method. Travel time data are first obtained from GPS-equipped probe vehicles, Bluetooth devices, and Sensys systems. The collected data are controlled at different levels of data aggregation for each travel time measurement method. After deployment of the SynchroGreen adaptive system, the GPS and Sensys-based studies produced similar travel time savings for all westbound segments, though not for all eastbound segments. Conversely, the Bluetooth-based study produced travel time savings for all eastbound segments though not for all westbound segments. Also, the results from two periods (before and after school started) were significantly different when the travel time data were aggregated at the most detailed level, which cannot be shown with the low level of data aggregation. This finding emphasized the importance of data collection and reduction design when conducting before-and-after studies of ITS deployments.