Calibrating microscopic car-following (CF) models is crucial in traffic flow theory as it allows
for accurate reproduction and investigation of traffic behavior and phenomena. Typically, the …

To connect microscopic driving behaviors with the macro-correspondence (ie, the
fundamental diagram), this study proposes a flexible traffic stream model, which is derived …

Despite its importance in macroscopic traffic flow modeling, comprehensive method for the
calibration of fundamental diagram is very limited. Conventional empirical methods adopt a …

Calibration and validation techniques are crucial in assessing the descriptive and predictive
power of car-following models and their suitability for analyzing traffic flow. Using real and …

The paper develops procedures for calibrating the steady-state component of various car
following models using macroscopic loop detector data. The calibration procedures are …

This study addresses the problem of calibration of the Gipps microscopic traffic flow model.
The approach consists of first deriving traffic stream models, in the form of steady-state …

This paper proves that in traffic flow model calibration and validation the cumulative sum of a
variable has to be preferred to the variable itself as a measure of performance. As shown …

This paper shows that the behavior of driver models, either individually or entangled in
stochastic traffic simulation, is affected by the accuracy of empirical vehicle trajectories. To …

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 …

Calibrating the microsimulation traffic models can be defined as a black‐box optimisation
problem with some non‐concave objective functions. In this regard, the stochastic …