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 …

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 …

Microscopic simulation models have become widely applied tools in traffic engineering.
Nevertheless, parameter identification of these models remains a difficult task. This is …

Car following models have been studied with many diverse approaches for decades.
Nowadays, technological advances have significantly improved our traffic data collection …

This paper shows how traffic heterogeneity, and the way it is encoded into a model,
drastically affects a model ability to reproduce observed traffic. Being heterogeneity a major …

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 evermore widespread use of microscopic traffic simulation in the analysis of road
systems has refocused attention on submodels, including car-following models. The …

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 …

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 …

One of the most important tasks in the microscopic simulation of traffic flow, assigned to the
car following sub-model, is the modelling of the longitudinal movement of vehicles. The …