Measures promoting active mobility – walking or cycling – are often seen as an effective strategy to meet multiple urban objectives. The advantages of such behavioural changes cover multiple dimensions at public and individual level, including positive impacts on health, safety, climate, economy, environment and air quality. However, there is still a considerable potential for increasing the uptake of active mobility in urban areas. This paper explores the determinants of active mobility choice and compares the demographic, socio-economic and cultural factors that influence it. The methodology combines extensive survey data, an EU-wide transport model and detailed indicators of external costs of transport with a Gradient Boosting Machine Learning approach. The model based scenarios quantify the benefit in terms of external costs savings from increasing active mobility shares. Such savings – at EU level, can reach the amount of 15 billion euro per year for a shift of 10% of trips to active mobility modes.
