An Exploratory Study of Two Efficient Approaches for the Sensitivity Analysis of Computationally Expensive Traffic Simulation Models

Abstract

One of the main challenges arising when calibrating a complex traffic simulation model concerns the selection of the most important input parameters. The quasi-optimized trajectory-based elementary effects (quasi-OTEE) and the Kriging-based sensitivity analysis (SA) are two recently developed efficient approaches for the SA of computationally expensive simulation models. In this paper, two experimental studies using two different traffic simulation models (i.e., Aimsun and VISSIM) are presented to compare these two approaches and to better understand their advantages and disadvantages. Results show that both approaches are able to identify, to a good degree, the important parameters. In particular, the quasi-OTEE is better for screening the parameters, whereas the Kriging-based SA has higher precision in ranking the parameters. These findings suggest the following rule of thumb for the SA of computationally expensive traffic simulation models: the quasi-OTEE SA can be used first to screen the parameters and to decide which parameters to discard. Then, the Kriging-based SA can be used to refine the analysis and calculate first-order indexes to identify the correct rank of the important parameters.