In the field of traffic simulation, the calibration of uncertain inputs against real data is usually
taken to cover both the epistemic uncertainty regarding the un-modeled details of the …

In the field of traffic simulation, the calibration of uncertain inputs against real data is usually
taken to cover the epistemic uncertainty regarding the un-modeled details of the phenomena …

Automated calibration of microscopic traffic flow models is all but simple for a number of
reasons, including the computational complexity of black-box optimization and the …

In 1997, Wolpert and Macready derived “No free lunch theorems for optimization.” They
basically state that “the expected performance of any pair of optimization algorithms across …

Simulating driving behavior in high accuracy allows short-term prediction of traffic
parameters, such as speeds and travel times, which are basic components of Advanced …

Digital Twins (DTs) are steadily gaining popularity for the study of large systems in real time.
In order to build an efficient and reliable DT, it is crucial to perform calibration prior to its use …

This study proposes and applies a methodology to calibrate microscopic traffic flow
simulation models. The proposed methodology has the capability to calibrate …

In this paper, a multistep sensitivity analysis (SA) approach for model calibration is proposed
and applied to a complex traffic simulation model with more than 100 parameters …

Parameter calibration of traffic microsimulation models usually takes the form of a simulation-
based optimization problem, that is, an optimization in which every objective function …

Parameter identification of microscopic driving models is a difficult task. This is caused by
the fact that parameters—such as reaction time, sensitivity to stimuli, etc.—are generally not …