Analysis of the factors affecting the evolution of the severity stages of traffic conflicts in long tunnels

Rear-end conflicts in long freeway tunnels are safety–critical yet difficult to study using crash data alone, because crashes are rare and tunnels impose constrained sight distance and abrupt environmental changes that can accelerate risk escalation. This study examines how conflict severity evolves as vehicles approach a critical interaction point and whether the underlying mechanisms vary across stages. We analyze trajectory-based rear-end conflicts extracted from continuous video monitoring in two long tunnels on Guangxi expressways and reconstruct each conflict at four spacing-to-leader stages (80, 60, 40, and 20 m). Methodologically, we first conduct horizontal stage-wise estimation using ordered logit, random-parameters ordered logit, and a heterogeneous-means extension. We then perform sensitivity analyses under alternative outcome definitions, balancing schemes, and stage definitions. Finally, we implement a longitudinal Bayesian hierarchical ordered-logit model to link coefficients across stages and decompose them into an overall stage trend and stage-specific deviations. Results show that heterogeneity-aware models outperform the basic ordered logit, and that the effects of relative-motion indicators and traffic-state factors change as the conflict point nears, revealing distinct upstream and near-conflict sensitivities. The sensitivity analyses indicate that the principal stage-wise mechanisms remain stable across reasonable modeling choices. The Bayesian results further show that common variables do not evolve uniformly across stages: some effects are governed mainly by smooth cross-stage trends, whereas others retain clearer local departures, thereby distinguishing structurally stable evolution from stage-specific adjustment. Overall, the proposed horizontal–longitudinal framework provides an interpretable basis for distance-aware tunnel warning logic and stage-sensitive safety management in long tunnels.