Sensitivity Analysis for a Cooperative Adaptive Cruise Control Car Following Model: Preliminary Findings

Abstract

Microscopic traffic simulations are powerful tools to evaluate transportation systems. For a simulation model to represent reality at a satisfactory level, models require calibration. Calibration implies that inputs to the model (e.g., driving behavior), must be set correctly so that modeled traffic conditions can mimic reality properly. However, calibration is a cumbersome process. As the complexity of the model increases, even running the simulation alone can be time-consuming. Sensitivity Analysis (SA) can be used in this regard. SA can be defined as the study of model parameters to determine which input parameter (or combination of them) influences the model output more than the rest of the parameters. This study provides a preliminary SA for the Cooperative Adaptive Cruise Controlled vehicle car-following model with the use of microscopic simulation environment SUMO (Simulation of Urban Mobility).