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 this, it is possible, from both an engineering and insurance perspective, to assess changes in the design of vehicles and transport systems in terms of their impact on functionality and road safety. 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：本文发展了一种方法,使交通系统微型模型能够用于交通事故统计研究。我们的方法旨在不仅使人们了解历史损失,而且了解今后可能发生的系统变化中可能发生的事故。通过这个方法,从工程和保险的角度,可以评估车辆和运输系统设计的变化对功能和道路安全的影响。从结构上,我们把总损失分布大致描述为一种中差混合。这也产生了可使用的价值评估程序,而不是Monte Carlo模拟程序。具体地说,我们根据开放源代码的交通模拟器SUMO设计了一个执行程序,并说明了反事实案例研究方法的潜力。