A TTC–THW-Based Site–Time–Interaction Framework for Engineering Screening in Motorcycle-Dominated Mixed Traffic

Surrogate safety assessment in motorcycle-dominated mixed traffic requires screening methods that distinguish threshold-sensitive event prevalence from stable site, time, and interaction patterns. This study develops a TTC–THW-based site–time–interaction framework for engineering screening using 13.342 h of video from six Hanoi arterials, comprising 371,864 vehicles, 2,977,401 validated leader–follower observations, and 180,722 TTC-defined events. Primary window-level inference uses 799 complete non-overlapping 60 s windows; 3181 overlapping windows are retained only for sensitivity analysis. Increasing the TTC reference from 1.5 to 2.4 s raised the flagged-observation proportion from 12.04% to 17.99%, without changing the site ordering. A one-standard-deviation increase in median THW was associated with a 13.81% lower expected TTC-defined event rate per following exposure in the primary model (IRR=0.8619, 95% CI 0.8433–0.8809), with similar estimates under overlapping-window and AR(1) GEE specifications. Follower-clustered event models showed stable vehicle-pair contrasts across TTC-defined criticality cut-points of 0.6, 0.8, and 1.0 s; the MC–Car odds ratios were 1.440, 1.352, and 1.273, respectively, relative to Car–Car. Alternative THW boundaries and empirical tertiles retained the main temporal-compression contrasts. Downsampling from 7.5 to approximately 3.75 Hz reduced absolute event counts by about 30.6–30.7% but left comparative site rankings unchanged. The framework therefore provides trajectory-based interaction screening rather than crash-risk prediction or independently validated near-crash classification.