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.

An increasing number of battery-electric vehicles (BEVs) have bidirectional charging technology that provides new benefits to motorists, homeowners, and power grid operators. A web-based survey investigates the willingness of over 300 Americans to pay for added bidirectional charging features, namely, vehicle-to-load (V2L), vehicle-to-home (V2H), and vehicle-to-grid (V2G) technologies, along with their expected use frequency. Summary statistics suggest that Americans are willing to pay (WTP) an average of $280 and $776 on top of the price of a new car for V2L and V2H, respectively. About 51.3% would let their power company discharge their vehicle via V2G during grid emergencies if compensated and guaranteed a minimum battery level. Interval regression and ordered probit equations explain how demographics, travel patterns, and attitudinal variables affect the response variables, including WTP for bidirectional charging features and expected reliance on technology. The statistically and practically significant relationships suggest that adults over 34 have lower WTP values for V2L and V2H, and those in households with more vehicles plan on more bi-directional charging, as expected. The findings have implications for policymakers, manufacturers, and stakeholders involved in the BEV ecosystem, informing their decision-making processes related to integrating and commercializing bidirectional charging technologies. These models may even help power grid planners understand who is likely to adopt V2G technology, enabling them to aggregate and shift BEV loads to help manage the grid in parallel and isolation.