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Ιδρυματικό Αποθετήριο [SANDBOX]
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| URI | http://purl.tuc.gr/dl/dias/CD04E4F5-76D4-45F3-A401-A184C1EB6194 | - |
| Αναγνωριστικό | https://doi.org/10.1016/j.trc.2018.05.020 | - |
| Αναγνωριστικό | https://www.sciencedirect.com/science/article/pii/S0968090X18305321 | - |
| Γλώσσα | en | - |
| Μέγεθος | 24 pages | en |
| Τίτλος | A data fusion approach for real-time traffic state estimation in urban signalized links | en |
| Δημιουργός | Rostami-Shahrbabaki Majid | en |
| Δημιουργός | Safavi Ali Akbar | en |
| Δημιουργός | Papageorgiou Markos | en |
| Δημιουργός | Παπαγεωργιου Μαρκος | el |
| Δημιουργός | Papamichail Ioannis | en |
| Δημιουργός | Παπαμιχαηλ Ιωαννης | el |
| Εκδότης | Elsevier | en |
| Περίληψη | Real-time estimation of the traffic state in urban signalized links is valuable information for modern traffic control and management. In recent years, with the development of in-vehicle and communication technologies, connected vehicle data has been increasingly used in literature and practice. In this work, a novel data fusion approach is proposed for the high-resolution (second-by-second) estimation of queue length, vehicle accumulation, and outflow in urban signalized links. Required data includes input flow from a fixed detector at the upstream end of the link as well as location and speed of the connected vehicles. A probability-based approach is derived to compensate the error associated with low penetration rates while estimating the queue tail location, which renders the proposed methodology more robust to varying penetration rates of connected vehicles. A well-defined nonlinear function based on traffic flow theory is developed to attain the number of vehicles inside the queue based on queue tail location and average speed of connected vehicles. The overall scheme is thoroughly tested and demonstrated in a realistic microscopic simulation environment for three types of links with different penetration rates of connected vehicles. In order to test the efficiency of the proposed methodology in case that data are available at higher sampling times, the estimation procedure is also demonstrated for different time resolutions. The results demonstrate the efficiency and accuracy of the approach for high-resolution estimation, even in the presence of measurement noise. | en |
| Τύπος | Peer-Reviewed Journal Publication | en |
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2019-09-02 | - |
| Ημερομηνία Δημοσίευσης | 2018 | - |
| Θεματική Κατηγορία | Connected vehicle | en |
| Θεματική Κατηγορία | Data fusion | en |
| Θεματική Κατηγορία | Queue tail | en |
| Θεματική Κατηγορία | Spot detector | en |
| Θεματική Κατηγορία | Traffic state estimation | en |
| Θεματική Κατηγορία | Urban signalized link | en |
| Βιβλιογραφική Αναφορά | M. Rostami-Shahrbabaki, A.A. Safavi, M. Papageorgiou and I. Papamichail, "A data fusion approach for real-time traffic state estimation in urban signalized links," Transp. Res. Part C Emerg. Technol., vol. 92, pp. 525-548, July 2018. doi: 10.1016/j.trc.2018.05.020 | en |
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