Willingness to Pay for Express Lanes, Heterogeneity Effects, Reliability Measures, and Optimal Control Strategies from Passively Collected Data
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In March 2020, governments worldwide implemented various social restriction measures, including lockdowns, to mitigate the spread of the COVID-19 virus. This led to a profound shift in travel behavior, accompanied by a notable reduction in congestion. This dissertation investigates travel demand on Express Lanes (ELs) during two time periods: before the pandemic (from January 2020 to mid-March 2020) and during the pandemic (from mid-March 2020 to the end of May 2020). A large data set of trips observed on Express Lanes derived from transponders is combined with vehicle probe measures of travel times and used to estimate the willingness to pay (WTP) for travel time savings and reliability. This dissertation also addresses system-wide performance optimization by integrating multiple control strategies.
This dissertation is structured into four main chapters. The first chapter explores the change in travel behavior on Express Lanes and assesses changes in WTP before and during the pandemic across different temporal phases. The second chapter investigates the heterogeneity of among Express Lane users’ WTP under the impact of lockdown policy. The third chapter provides a comprehensive analysis of users’ value of travel time (VOT) and reliability (VOR) on the Express Lane before and during the pandemic. The fourth chapter extends the focus to system-wide optimization, presenting an integrated traffic management system that combines real-time ramp metering with dynamic toll pricing strategies to alleviate congestion and enhance freeway performance.