This study tests the hypothesis that an analytically estimated driver reaction time required for asymptotic stability, based on the macroscopic Gazis-Herman-Rothery (GHR) model, serves as an indicator of the impact of traffic oscillations on rear-end crashes. If separate GHR models are fit discontinuously for different traffic regimes, the local drop in required reaction time between these regimes can also be estimated. This study evaluates the relationship between rear-end crash rates and that drop in required reaction time. Traffic data from 28 sensors were used to fit the GHR model. Rear-end crash rates, estimated from four years of crash data, exhibited a positive correlation with the drop in required reaction time at the congested regime’s density-breakpoint. A linear relationship provided the best fit. These results motivate follow-on research to incorporate macroscopically derived reaction time in road-safety planning. More generally, the study demonstrates a useful application of a discontinuous macroscopic traffic model.

本研究检验了一个假设，即基于宏观 Gazis-Herman-Rothery (GHR) 模型分析估计的渐近稳定性所需的驾驶员反应时间可作为交通波动对追尾事故影响的指标。如果单独的 GHR 模型不连续地适合不同的交通状况，则还可以估计这些交通状况之间所需反应时间的局部下降。本研究评估了追尾事故率与所需反应时间下降之间的关系。来自 28 个传感器的交通数据用于拟合 GHR 模型。根据四年的碰撞数据估计的追尾事故率与拥挤状态的密度断点处所需反应时间的下降呈正相关。线性关系提供了最佳拟合。这些结果促使后续研究将宏观衍生的反应时间纳入道路安全规划。更一般地说，该研究证明了不连续宏观交通模型的有用应用。