Macro-level correlates of speeding: a socio-economic and geographic analysis in Italy

Speeding remains a critical factor in road traffic crashes, yet its prevalence is influenced by more than just individual driver choices. This study analyzes speeding in Italy from a macro-level perspective, examining how socio-economic, geographic, and mobility factors affect speed safety performance indicators (SSPIs) such as speed limit compliance and operating speeds. Using a stratified random sampling method, free-flow speed data was collected from 310,101 vehicles across 88 observation points, representing diverse road types and 20 provinces across Italy. This data, used to calculate the SSPIs, was analyzed alongside macro-level statistics through cluster analysis and regression models to identify regional patterns and predictive relationships. Results indicate that road type is a powerful predictor of speed compliance, with higher-speed roads like motorways and expressways showing greater compliance than urban roads, suggesting that road design credibility influences driver behavior. The predictive models explained a significant portion of the variance in speed limit compliance (31%), operating speed (87.4%), and speed variation (63%). Key findings indicate that demographic factors, such as a higher proportion of early middle-aged drivers, correlate with better compliance and more stable driving. Furthermore, higher educational attainment and employment rates were associated with more consistent driving speeds. The study highlights that urbanization increases speed variation, while public transport availability is linked to lower operating speeds. A cluster analysis identified six distinct regional profiles, emphasizing the need for tailored, context-specific road safety strategies rather than uniform national policies. This research advocates for addressing macro-level factors to develop more effective road safety interventions.