UC Irvine

Emerging mobility technologies, like ride-hailing, are underrepresented in travel behavior surveys. Consequently, travel demand modelers have often resorted to simplistic solo-traveler assumptions or relied on aggregate trip size factors within activity- and agent-based models. To address this gap and help modelers understand ride-hail party size, this study analyzed data collected from a 2021 to 2022 household travel survey in the greater Twin Cities (Minneapolis–St. Paul, MN) region. Ride-hail trips were paired with person-, household-, and trip-level attributes to provide context for both single-party and multiparty ride-hailing. Binary logistic regression models indicated that shared micromobility users, households with more children, renters in large multifamily buildings, and individuals with at most a high school education were significantly more likely to use ride-hailing for group travel than for solo trips. A hurdle regression for party size count revealed that lower-income households, while less likely to use ride-hailing, were more likely to opt for group travel and form larger parties than other income cohorts. These findings offer insights into who takes ride-hailing for group travel, enabling policy makers to devise strategies targeting solo, unshared ride-hailing without negatively affecting large groups.