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：碰撞和冲突避免系统的安全评估对汽车行业及其他利益相关者至关重要。需要此类评估的一类系统是驾驶员监控系统（DMS），当驾驶员长时间偏离道路视线时，该系统会进行干预（例如警告或提示）。尽管使用计算机仿真评估安全系统日益普遍，但该方法尚未广泛应用于影响驾驶员行为的系统（如DMS）。能够考虑碰撞成因机制并生成虚拟碰撞的模型是评估这些系统的关键，然而目前此类模型很少，且现有模型缺乏基于真实数据的充分验证。本研究旨在通过验证一个基于四种与驾驶员行为相关的碰撞成因机制（a. 视线偏离道路、b. 车头时距过短、c. 未以最大可能减速度制动、d. 疲劳（碰撞前无反应））的追尾碰撞成因模型来填补这一研究空白。碰撞前运动学数据来自德国GIDAS深度碰撞数据库。我们识别并解决了验证过程中的挑战，其中最关键的是开发了一种方法将生成的碰撞转换为模拟GIDAS中的碰撞严重程度分布。该步骤的必要性在于：GIDAS不包含仅财产损失（PDO）碰撞，而生成的碰撞覆盖全部严重程度范围（包括大量低严重度碰撞，其中多为PDO）。结果表明，所提出模型是一个较优的碰撞生成器。我们进一步证明该模型是虚拟仿真中评估DMS的有效方法：它揭示了缩短最大持续视线偏离时间对安全性的积极影响。如预期所示，消除长时间视线偏离显著降低了碰撞发生数量并减小了平均delta-v。