The paper develops a methodology to enable microscopic models of transportation systems to be accessible for a statistical study of traffic accidents. Our approach is intended to permit an understanding not only of historical losses, but also of incidents that may occur in altered, potential future systems. Through such a counterfactual analysis, it is possible, from an insurance, but also from an engineering perspective, to assess the impact of changes in the design of vehicles and transport systems in terms of their impact on road safety and functionality. Structurally, we characterize the total loss distribution approximatively as a mean-variance mixture. This also yields valuation procedures that can be used instead of Monte Carlo simulation. Specifically, we construct an implementation based on the open-source traffic simulator SUMO and illustrate the potential of the approach in counterfactual case studies.

翻译：本文开发了一种方法，使微观交通系统模型可用于交通事故的统计研究。我们的方法不仅旨在理解历史损失，还旨在理解可能发生在改变后的潜在未来系统中的事件。通过这种反事实分析，从保险以及工程的角度，可以评估车辆和运输系统设计变更对道路安全性和功能性的影响。在结构上，我们将总损失分布近似表征为均值-方差混合分布。这也产生了可替代蒙特卡洛模拟的估值方法。具体而言，我们基于开源交通模拟器SUMO构建了一个实现，并通过反事实案例研究展示了该方法的潜力。