  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.
