Abstract:Based on the analysis of one-week GPS-based travel diary data from the four largest metropolitan areas in California, this study estimates a latent-class cluster analysis and identifies four distinct groups of travelers with different levels of multimodality. These groups are characterized by their distinctive use of five travel modes (i.e., single-occupant vehicles, carpooling, public transit, biking, and walking) for both commuting and non-commuting trips. Two of these groups are more car-oriented and less multimodal (i.e., heavy car users and light car users), whereas the other two are less-car-oriented and display a higher level of multimodality (i.e., transit users and cyclists). Results from this study reveal the unique profile of each group of travelers in terms of their sociodemographic characteristics and built-environment attributes. This study further investigates the associations between ridehailing adoption and travel mode decisions, trip frequency and trip attributes. Transit riders are found to have the highest rate of ridehailing adoption and usage. They are also more prone to use pooled ridehailing services in comparison to other groups. Lastly, in terms of mode substitution, were ridehailing not available, respondents tend to choose the mode they use most frequently. In other words, car-based travelers are more likely to substitute ridehailing trips with car trips, whereas non-car-based travelers are more likely to replace ridehailing with less-polluting modes. Findings from this study will prove valuable to transit agencies and policymakers interested in studying how ridehailing can be integrated with other modes and how they can promote more multimodal and less car-dependent lifestyles.