Captive drivers or multimodal passengers? Segmenting car use for targeted mobility policies

Private car use generates major environmental and social externalities, particularly in urban areas. In response, policymakers have increasingly implemented measures aimed at reducing automobile usage and promoting more sustainable mobility patterns. However, many of these initiatives continue to rely on a one-size-fits-all approach, despite the heterogeneity of car users in terms of socioeconomic characteristics, residential context and travel behaviour. Such approaches may be less effective because they focus on average effects while overlooking differences across user groups. This study analyses this heterogeneity in the Barcelona Metropolitan Region in order to move beyond the notion of the “average user”. Using data from a 2021 travel survey, we perform a latent class analysis (LCA) based on current levels of car and public transport use, as well as several satisfaction indicators. The LCA identifies four distinct user profiles that vary mainly in driving frequency and satisfaction with public transport supply and quality. Key segmentation variables include gender, age, employment status, educational attainment, county of residence, income and residential accessibility. This paper highlights socioeconomic, housing and mobility factors associated with car use and offers actionable insights for developing targeted policies to reduce private vehicle use in one of Europe’s densest urban areas.