The differences in the effects of risk factors between the classifications highlight the importance of using a reliable classification of injury severity. Additionally, the relationship between LHS and MAIS levels is quite different among countries, supporting the previous conclusion that bias is expected in the assessment of risk factors if an injury severity classification other than MAIS is used.
Simulation approaches constitute a well-established tool to model, understand and predict the behavior of transportation systems, and ultimately to assess the performance of transportation policies. Due to their multidimensionality nature, such systems are not often approachable through conventional analytic methods, making simulation modeling the only reliable tool of study. Nevertheless, simulation models can turn out to be computationally expensive when embedded with enough detail. An immediate answer to this shortcoming is the use of simulation metamodels that are designed to approximate the simulators' results.In this work, the authors propose a metamodeling approach based on active learning that seeks to improve the exploration process of the simulation input space and the associated output behavior. A Gaussian Process (GP) is used as a metamodel to approximate the function inherently defined by the simulation model itself. The GPs are able to nicely handle the uncertainty associated with their predictions, which eventually can be improved with active learning through simulation runs. This provides a practical and efficient way to analyze the simulator's behavior and therefore to assess the performance of policies regarding the underlying real-world systems and services.The authors illustrate the proposed methodology using an Emergency Medical Service (EMS) simulator. Two outputs are analyzed and compared, namely, the survival rate and response time averages. The medical emergency response time recommendation of eight minutes is explored as well its relation with the survival rate. The results show that this methodology is able to identify regions in the simulation input space that might affect the performance and success of medical policies with regards to emergency vehicle dispatching services.
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