Evaluating the full scale potential of urban mobility measures through a multi city cluster analysis of public transport interventions in Europe

Abstract The transition toward sustainable urban mobility requires a better understanding of how measures perform when implemented at scale. While many pilot projects have been tested across European cities, evidence on their full-scale potential remains limited. This study evaluates 78 mobility measures across ten cities through expert-based assessments on five criteria: congestion, road safety, modal share, accessibility, and user satisfaction. Using cluster analysis, supported by Elbow and Silhouette diagnostics, four distinct groups of measures were identified. Principal Component Analysis (PCA) was subsequently used to provide a two-dimensional visualization of the resulting cluster structure. The results reveal: (i) digital measures with high anticipated user-related ratings but lower anticipated system-impact ratings, (ii) transformative public transport and infrastructure measures with consistently high performance, (iii) administrative actions with comparatively lower anticipated direct-impact ratings, and (iv) “push” policies characterized by moderate-to-high anticipated system-impact ratings but comparatively lower anticipated user satisfaction. Overall, the findings highlight that large-scale interventions received the highest anticipated impact ratings across multiple dimensions, while the results also suggest differentiated trade-offs between system-oriented and user-oriented outcomes across intervention types.