![]() Sobol sequences and Gaussian process metamodels were recognized as the appropriate choices. Among these issues are the importance of selecting a proper sampling strategy based on low-discrepancy random number sequences and the importance of selecting a class of metamodels able to reproduce the inputs–outputs relationship in a robust and reliable way. Important issues concerning metamodel estimation were investigated and commented on in the specific application to the AIMSUN model. For this reason, the possibility of performing a sensitivity analysis was tested not on a model but on its metamodel approximation. The application of sensitivity analysis is crucial for the true comprehension and correct use of the traffic simulation model, although the main obstacle to an extensive use of the most sophisticated techniques is the high number of model runs such techniques usually require. This study adopted a metamodel-based technique for model sensitivity analysis and applied it to the AIMSUN mesoscopic model. Gaussian Process Metamodels for Sensitivity Analysis of Traffic Simulation Models: Case Study of AIMSUN Mesoscopic Model
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