Improved Travel Time Estimation for Reliable Performance Measure Development for Closed Highways

Abstract

Accurate travel time information not only is valuable for travelers but is critical to transportation agencies for quantifying the performance of their systems. Interest has been increasing in the development of reliable approaches for estimating travel time from various sensor data. Unlike the extensively studied estimation approaches based on point sensor measurements, the use of probe data from closed highway systems has been limited. To complement current understanding, this study developed an approach that used probe data from an electronic toll collection (ETC) system on closed freeways to estimate travel time. This approach differs from studies relying on automatic vehicle identification systems deployed on main lines as well as those estimated from point detectors. The proposed approach breaks down individual journey time into section travel time and fuses the probe data from vehicles that have used the links. The results, which are based on real-world case studies, illustrate the potential of mining ETC data for travel time estimation for both incident-free and incident conditions. In addition, the estimated results capture traffic dynamics better than instantaneous travel time estimates based on point sensor data. More accurate information is thus provided for deriving reliable performance measures to depict travel time reliability.