Safety assessment of crash and conflict avoidance systems is important for both the automotive industry and other stakeholders. One type of system that needs such an assessment is a driver monitoring system (DMS) with some intervention (e.g., warning or nudging) when the driver looks off-road for too long. Although using computer simulation to assess safety systems is becoming increasingly common, it is not yet commonly used for systems that affect driver behavior, such as DMSs. Models that generate virtual crashes, taking crash-causation mechanisms into account, are needed to assess these systems. However, few such models exist, and those that do have not been thoroughly validated on real-world data. This study aims to address this research gap by validating a rear-end crash-causation model which is based on four crash-causation mechanisms related to driver behavior: a) off-road glances, b) too-short headway, c) not braking with the maximum deceleration possible, and d) sleepiness (not reacting before the crash). The pre-crash kinematics were obtained from the German GIDAS in-depth crash database. Challenges with the validation process were identified and addressed. Most notably, a process was developed to transform the generated crashes to mimic the crash severity distribution in GIDAS. This step was necessary because GIDAS does not include property-damage-only (PDO) crashes, while the generated crashes cover the full range of severities (including low-severity crashes, of which many are PDOs). Our results indicate that the proposed model is a reasonably good crash generator. We further demonstrated that the model is a valid method for assessing DMSs in virtual simulations; it shows the safety impact of shorter "longest" off-road glances. As expected, cutting away long off-road glances substantially reduces the number of crashes that occur and reduces the average delta-v.

翻译：碰撞与冲突规避系统的安全评估对汽车行业及其他利益相关方均至关重要。需要此类评估的系统之一是驾驶员监控系统(DMS)，当驾驶员视线偏离道路时间过长时，该系统会进行干预（如警告或轻推）。尽管使用计算机模拟评估安全系统日益普遍，但对于影响驾驶员行为（如DMS）的系统，这种方法尚未广泛应用。生成虚拟事故并考虑事故因果机制的模型是评估这些系统所必需的。然而，此类模型数量稀少，且现有模型未能在真实世界数据上得到充分验证。本研究旨在通过验证一种追尾事故因果模型来填补这一研究空白，该模型基于与驾驶员行为相关的四种事故因果机制：a）视线偏离道路，b）跟车距离过短，c）未以最大可能减速度制动，d）困倦（碰撞前未做出反应）。碰撞前运动学数据来自德国GIDAS深度事故数据库。验证过程中面临的挑战被识别并加以解决。最值得注意的是，开发了一种流程将生成的事故转化为模拟GIDAS中的事故严重程度分布。这一步骤的必要性在于，GIDAS不包含仅财产损失事故，而生成的事故覆盖了从低严重度（其中许多仅为财产损失）到高严重度的全部范围。结果表明，所提出的模型是一个相当好的事故生成器。我们进一步证实，该模型是一种在虚拟仿真中有效评估DMS的方法；它展示了缩短“最长”视线偏离道路时间对安全性的影响。正如预期，消除长时间视线偏离道路行为显著减少了事故数量，并降低了平均delta-v值。