How do automated vehicle Penetration, Vehicle-Size Composition, and desired headway shape urban traffic conflict Patterns? An analysis using a calibrated microsimulation model.
Abstract
Automated vehicles (AVs) may improve urban road safety, yet aggressive calibration and mixed-traffic interactions may produce nonlinear patterns in TTC-defined surrogate events. This study examines how AV penetration, vehicle-size composition, and desired headway calibration shape simulated TTC-defined surrogate outcomes. Using SUMO microsimulation for Charlottenburg, Berlin, with TTC-based analysis, LightGBM modeling, and spatial hotspot mapping, we evaluate 12 scenarios varying AV penetration (0-100%) and the composition of small AV12 and larger AV46. Both AV classes share the same driving parameters and differ primarily in physical dimensions. The scenario matrix is evaluated at AV desired headways of τ = 0.6, 0.8, and 1.0 s, yielding 36 nominal scenario-headway combinations and 34 effective configurations; human-driven vehicle (HDV) headway remains fixed at 1.0 s. Under 0.6 s calibration, total TTC-defined conflict frequency declines with increasing AV penetration, reaching reductions of approximately 45% under full automation. However, mixed-traffic configurations at the 0.6 s headway produce a larger proportion of selected short-TTC events (TTC < 0.5 s). Sensitivity analysis using minTTC thresholds of 0.3, 0.5, and 0.75 s shows that the 0.6 s setting consistently produces the greatest concentration of short temporal margins, whereas 0.8 s represents an intermediate profile. Spatially, conflicts shift from network-wide dispersion under HDV-dominant conditions to localized concentration at critical junctions under AV-dominant traffic. Differences between AV12- and AV46-dominant configurations are comparatively small and vary across headway and TTC-threshold settings. LightGBM identifies relative speed and desired headway as the strongest predictive associations. The findings highlight the context- and calibration-dependent nature of simulated AV surrogate-safety outcomes, particularly the roles of market penetration, desired headway, and vehicle-size composition.