Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
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| URI | http://purl.tuc.gr/dl/dias/B38ECD21-C0D9-4E6C-B588-D1CEC0EC0E63 | - |
| Αναγνωριστικό | https://doi.org/10.1016/j.trc.2022.103904 | - |
| Αναγνωριστικό | https://www.sciencedirect.com/science/article/pii/S0968090X22003175 | - |
| Γλώσσα | en | - |
| Μέγεθος | 43 pages | en |
| Τίτλος | Macroscopic traffic flow modelling of large-scale freeway networks with field data verification: State-of-the-art review, benchmarking framework, and case studies using METANET | en |
| Δημιουργός | Wang Yibing | en |
| Δημιουργός | Yu Xianghua | en |
| Δημιουργός | Guo Jinqiu | en |
| Δημιουργός | Papamichail Ioannis | en |
| Δημιουργός | Παπαμιχαηλ Ιωαννης | el |
| Δημιουργός | Papageorgiou Markos | en |
| Δημιουργός | Παπαγεωργιου Μαρκος | el |
| Δημιουργός | Zhang Lihui | en |
| Δημιουργός | Hu Simon | en |
| Δημιουργός | Li Yongfu | en |
| Δημιουργός | Sun Jian | en |
| Εκδότης | Elsevier | en |
| Περίληψη | Macroscopic traffic flow models are of paramount importance to traffic surveillance and control. Before their employments in applications, the models need to be calibrated and validated against real traffic data. The model calibration determines an optimal set of model parameters that minimizes the discrepancy between the modeling results and real traffic data. The model validation is furthermore performed to corroborate the accuracy of a calibrated model using data other than used for calibration. The model calibration aims to reflect traffic reality, while model validation focuses on the prediction of future traffic using calibrated models. This paper delivers a comprehensive review of state-of-the-art works on macroscopic model calibration and validation, proposes a benchmarking framework on traffic flow modeling, and has conducted a large number of case studies based on the framework using macroscopic traffic flow model METANET with respect to the urban expressway network in Shanghai. In comparison to previous works, quite more comprehensive results on model calibration have been presented in this paper, in consideration of congestion tracking, traffic flow inhomogeneity, capacity drop, stop-and-go waves, scattering, adverse weather conditions, and accidents. The paper has also reported many results of model validation with respect to the same field examples. The results demonstrate that METANET is able to model complex traffic flow dynamics in large-scale freeway networks with sufficient accuracy. The paper is closed with discussion on limitations and future works. | en |
| Τύπος | Ανασκόπηση | el |
| Τύπος | Review | en |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2024-01-18 | - |
| Ημερομηνία Δημοσίευσης | 2022 | - |
| Θεματική Κατηγορία | Freeway traffic flow model calibration and validation | en |
| Θεματική Κατηγορία | Congestion tracking | en |
| Θεματική Κατηγορία | Traffic flow inhomogeneity | en |
| Θεματική Κατηγορία | Weather conditions | en |
| Θεματική Κατηγορία | Accidents | en |
| Θεματική Κατηγορία | Capacity drop | en |
| Βιβλιογραφική Αναφορά | Y. Wang, X. Yu, J. Guo, I. Papamichail, M. Papageorgiou, L. Zhang, S. Hu, Y. Li, and J. Sun, “Macroscopic traffic flow modelling of large-scale freeway networks with field data verification: State-of-the-art review, benchmarking framework, and case studies using METANET,” Transp. Res. Part C Emerging Technol., vol. 145, Dec. 2022, doi: 10.1016/j.trc.2022.103904. | en |
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