Το έργο με τίτλο Calibration of a second-order traffic flow model using a metamodel-assisted Differential Evolution algorithm από τον/τους δημιουργό/ούς Porfyri Kalliroi, Nikolos Ioannis, Delis Anargyros, Papageorgiou Markos διατίθεται με την άδεια Creative Commons Αναφορά Δημιουργού-Μή Εμπορική Χρήση-Όχι Παράγωγα Έργα 4.0 Διεθνές
Βιβλιογραφική Αναφορά
K. N. Porfyri, I. K. Nikolos, A. I. Delis and M. Papageorgiou, "Calibration of a second-order traffic flow model using a metamodel-assisted Differential Evolution algorithm," in 2016 IEEE 19th International Conference on Intelligent Transportation Systems, November, pp. 366-371. doi: 10.1109/ITSC.2016.7795581
https://doi.org/10.1109/ITSC.2016.7795581
With the increasingly widespread use of traffic flow simulation models, several questions concerning the reliability, efficiency and accuracy of such models need to be addressed convincingly. In general, the most time-efficient traffic flow models are based on the macroscopic approach to describe traffic dynamics. Macroscopic models reproduce the evolution of aggregated traffic characteristics over time and space with respect to observable variables, such as flow andspeed, requiring much less computational time, compared to microscopic ones. This work assesses a second-order macroscopic gas-kinetic traffic flow (GKT) model and its numerical implementation using real traffic data from amotorway network in the U.K., where recurrent congestion originated from high on-ramp flows during the morning peak hours is observed. A parallel, metamodel-assisted Differential Evolution (DE) algorithm is employed for the calibration of themodel parameters, and numerical simulations demonstrate that the DE algorithm can be a very promising method for the calibration of such traffic flow models.