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A data fusion approach for real-time traffic state estimation in urban signalized links

Rostami-Shahrbabaki Majid, Safavi Ali Akbar, Papageorgiou Markos, Papamichail Ioannis

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URIhttp://purl.tuc.gr/dl/dias/CD04E4F5-76D4-45F3-A401-A184C1EB6194-
Identifierhttps://doi.org/10.1016/j.trc.2018.05.020-
Identifierhttps://www.sciencedirect.com/science/article/pii/S0968090X18305321-
Languageen-
Extent24 pagesen
TitleA data fusion approach for real-time traffic state estimation in urban signalized linksen
CreatorRostami-Shahrbabaki Majiden
CreatorSafavi Ali Akbaren
CreatorPapageorgiou Markosen
CreatorΠαπαγεωργιου Μαρκοςel
CreatorPapamichail Ioannisen
CreatorΠαπαμιχαηλ Ιωαννηςel
PublisherElsevieren
Content SummaryReal-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
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2019-09-02-
Date of Publication2018-
SubjectConnected vehicleen
SubjectData fusionen
SubjectQueue tailen
SubjectSpot detectoren
SubjectTraffic state estimationen
SubjectUrban signalized linken
Bibliographic CitationM. 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.2018.05.020en

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