Analyzing Post-COVID Commuting Preferences and Frequencies in California: A Hybrid Multiple Discrete-Continuous Extreme Value Approach

Abstract

(142 WORDS)

Before the COVID-19 pandemic, commuting trips were a significant part of vehicle miles traveled (VMT) in the U.S. Although commuting decreased during the pandemic, California's highway traffic has nearly returned to pre-pandemic levels. This study examines post-pandemic commuting preferences using data from 1,458 California residents. A hybrid multiple discrete-continuous extreme value (HMDCEV) model was developed to simultaneously analyze the impacts of latent attitudes and both direct and indirect effects of observable variables on commuting choices and respective frequencies. Results indicate latent attitudes such as anti-car, car-captive, pro-biking and pro-environment, influence commuting preferences. Additionally, socio-demographics, residential characteristics, and employment characteristics play crucial roles. Driving alone in a private vehicle was found to be the most popular commuting mode, followed by telework, while ride-hailing was the least popular. These findings can help policymakers promote sustainable transportation by addressing both observable factors and underlying attitudes.