2022/12/28 by Rafael Prieto-Curiel, Juan P. Ospina, Prieto-Curiel, Rafael +1 · 1 citation
Engineering · Medicine · Social Sciences · #Business #Car ownership #Computer science #Demographic economics #Dependency (UML) #Economic geography #Economics #Engineering #Environmental health #FOS: Physical sciences #Geography #Human Mobility and Location-Based Analysis #Medicine #Modal shift #Physics and Society (physics.soc-ph) #Population #Private transport #Public transport #Space (punctuation) #Sustainability #Sustainable transport #Transport engineering #Transportation Planning and Optimization #Urban Transport and Accessibility
paper · pdf · doi:10.48550/arxiv.2212.13956
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2022/12/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The use of cars in cities has many negative impacts on its population, including pollution, noise and the use of space. Yet, detecting factors that reduce automobile dependency is a serious challenge, particularly across different regions. Here we model the use of different modes of transport in a city by aggregating active mobility (A), public transport (B) and cars (C), thus expressing the modal share of a city by its ABC triplet. Data for nearly 800 cities across 60 countries is used to model car use and its relationship with city size and income. Our findings suggest that outside the US, longer distances experienced in large cities reduce the propensity of active mobility and of cars, but public transport is more prominent. For cities in the US, roughly 90% of its mobility depends on cars, regardless of city size. Further, income is strongly related to automobile dependency. Results show that a city with twice the income has 37% more journeys by car.