A Multiobjective Reinforcement Learning Framework for Equitable Toll Design for Express Lanes

Authors

Venktesh Pandey Ph.D, North Carolina Agricultural and Technical State University

Document Type

Report

Publication Date

9-2023

Keywords

High-speed rail in USA, Intermodal choice, COVID-19 impact, Intention to use HSR; HSR passengers’ segments

Abstract

While high-speed rail (HSR) has achieved success in major cities in Europe and Asia, it is a new phenomenon in the US, and few studies on HSR in the US are available, especially from the users’ perspective. This study aims to fill the research gap by investigating the mode choice behavior in the Los Angeles and San Francisco corridor, where HSR may soon become a feasible option. The impact of COVID-19 was examined regarding how people view modes of domestic travel and how their views may change. The geographic locations of travelers and the possible HSR characteristics in the US were also explored. In addition, this study explored the meaningful segmentation of travelers, using transport culture, HSR prices, travel time, safety, and comfort jointly as the cluster variates. Survey data of US travelers was collected on MTurk, which was analyzed using logistics regression and twoway MANOVA. The results indicated that convenience in transport, travel frequency, income, gender, mobility issues, and total travel time were determinants in the choice between HSR and air service, while travel frequency and total travel time were important in the choice between HSR and car. Most US travelers changed their views following COVID19 regarding domestic travel and exhibited a higher intention to travel by trains and HSR. Geographic patterns were identified, such as people in the southern US were the most knowledgeable of HSR and had the greatest intention to use HSR, while people in the northeast exhibited the lowest intention. Four HSR user segments were identified, including Balanced, Comfort First, Price Sensitive, and Traditional Traveler segments, each with different characteristics regarding the use of HSR in the US. The findings indicate potential interest in HSR among US travelers and offer much-needed empirical evidence for the potential success of HSR in the US.

Recommended Citation

Pandey, Venktesh Ph.D, "A Multiobjective Reinforcement Learning Framework for Equitable Toll Design for Express Lanes" (2023). Center for Advanced Transportation Mobility. 30.
https://digital.library.ncat.edu/catm/30