New metrics and estimates of travel time reliability using large passive datasets

This paper presents a comprehensive modeling framework and empirical analysis of the Value of Travel Time (VOT) and the Value of Travel Time Reliability (VOR) on Express Lanes. Using a large dataset from transponder-recorded trips, complemented by vehicle probe data, we explore the variability of travel time across different dimensions: day-to-day, intra-day, and intra-peak. Our study spans two distinct timeframes: pre-pandemic (January 2020 to mid-March 2020) and during the pandemic (mid-March 2020 to the end of May 2020), providing insights into travel behavior under both routine and unpredictable conditions. Our findings indicate that Express Lane users are more willing to pay for reduced travel time variability than for actual time savings. Additionally, both the Value of Time (VOT) and the Value of Reliability (VOR) increased during the pandemic, with VOR experiencing a particularly sharp rise. Furthermore, the results suggest that Express Lane users would show an even greater willingness to pay to reduce travel time variability if they were aware of the true value of reliability. The proposed methods and resulting analysis can assist toll operators and agencies in managing infrastructure effectively, without the need for survey data collection.