Global sensitivity analysis techniques to simplify the calibration of traffic simulation models. Methodology and application to the IDM car-following model

2014 ◽  
Vol 8 (5) ◽  
pp. 479-489 ◽  
Author(s):  
Biagio Ciuffo ◽  
Vincenzo Punzo ◽  
Marcello Montanino
Keyword(s):  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
Traffic Simulation ◽  
Simulation Models ◽  
Car Following ◽  
Global Sensitivity ◽  
Analysis Techniques ◽  
Car Following Model

Analytical Variance-Based Global Sensitivity Analysis in Simulation-Based Design Under Uncertainty

2004 ◽  
Author(s):  
Wei Chen ◽  
Ruichen Jin ◽  
Agus Sudjianto
Keyword(s):  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
Simulation Models ◽  
Design Under Uncertainty ◽  
Global Sensitivity ◽  
Functional Relationships ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Input Variables ◽  
The Impact

The importance of sensitivity analysis in engineering design cannot be over-emphasized. In design under uncertainty, sensitivity analysis is performed with respect to the probabilistic characteristics. Global sensitivity analysis (GSA), in particular, is used to study the impact of variations in input variables on the variation of a model output. One of the most challenging issues for GSA is the intensive computational demand for assessing the impact of probabilistic variations. Existing variance-based GSA methods are developed for general functional relationships but require a large number of samples. In this work, we develop an efficient and accurate approach to GSA that employs analytic formulations derived from metamodels of engineering simulation models. We examine the types of GSA needed for design under uncertainty and derive generalized analytical formulations of GSA based on a variety of metamodels commonly used in engineering applications. The benefits of our proposed techniques are demonstrated and verified through both illustrative mathematical examples and the robust design for improving vehicle handling performance.

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