Do Higher Automated Vehicle Shares Deliver Safer Roads? Microsimulation Evidence of Safety Effects Across Market Penetration

Abstract

Automated vehicles may improve urban road safety, yet aggressive calibration and mixed-traffic interactions may produce non-linear safety effects. This study examines how automated-vehicle penetration, fleet composition, and behavioral calibration shape traffic-safety outcomes. Using SUMO microsimulation for Charlottenburg, Berlin, with TTC-based surrogate-safety analysis, LightGBM modeling, and spatial hotspot mapping, the study evaluates scenarios varying automated-vehicle penetration, fleet composition, and time headway. Results reveal a non-linear safety transition: total conflict frequency declines with increasing automated-vehicle penetration, reaching reductions of approximately 45% under full automation. However, severe conflicts increase during the mixed-traffic phase under aggressive calibration. A time headway of 0.8 seconds provides the most balanced performance. Conflicts move from network-wide dispersion under human-driven conditions to concentration at critical junctions under automated-vehicle-dominant traffic.