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Interval macroscopic models for traffic networks.

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Interval macroscopic models for traffic networks. / Gning, A. C.; Mihaylova, Lyudmila; Boel, R.

In: IEEE Transactions on Intelligent Transportation Systems, Vol. 12, No. 2, 06.2011, p. 523-526.

Research output: Contribution to journalJournal article

Harvard

Gning, AC, Mihaylova, L & Boel, R 2011, 'Interval macroscopic models for traffic networks.', IEEE Transactions on Intelligent Transportation Systems, vol. 12, no. 2, pp. 523-526. https://doi.org/10.1109/TITS.2011.2107900

APA

Gning, A. C., Mihaylova, L., & Boel, R. (2011). Interval macroscopic models for traffic networks. IEEE Transactions on Intelligent Transportation Systems, 12(2), 523-526. https://doi.org/10.1109/TITS.2011.2107900

Vancouver

Gning AC, Mihaylova L, Boel R. Interval macroscopic models for traffic networks. IEEE Transactions on Intelligent Transportation Systems. 2011 Jun;12(2):523-526. https://doi.org/10.1109/TITS.2011.2107900

Author

Gning, A. C. ; Mihaylova, Lyudmila ; Boel, R. / Interval macroscopic models for traffic networks. In: IEEE Transactions on Intelligent Transportation Systems. 2011 ; Vol. 12, No. 2. pp. 523-526.

Bibtex

@article{be298364a3fa43b292f5436cf20cae0a,
title = "Interval macroscopic models for traffic networks.",
abstract = "The development of real-time traffic models is of paramount importance for the purposes of optimising traffic flow. Inspired by the compositional model (CM) [1] and the METANET model [2], [3], this paper proposes an interval approach for macroscopic traffic modeling. We develop an interval compositional model (ICM) and an interval implementation of METANET model (IMETANET) that provide a natural way of predicting traffic flows without the assumption of uniform distribution of vehicles in a cell. The interval macroscopic models are suitable for real-time applications in road networks and can be part of road traffic surveillance and control systems. The performance of the interval approaches are investigated for both the ICM and the IMETANET models. The efficiency of the interval models is demonstrated over simulated data and also over real traffic data from the United Kingdom, from MIDAS data sets.",
keywords = "Traffic modeling, interval methods, macroscopic models, compositional model, METANET model",
author = "Gning, {A. C.} and Lyudmila Mihaylova and R. Boel",
year = "2011",
month = "6",
doi = "10.1109/TITS.2011.2107900",
language = "English",
volume = "12",
pages = "523--526",
journal = "IEEE Transactions on Intelligent Transportation Systems",
issn = "1524-9050",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "2",

}

RIS

TY - JOUR

T1 - Interval macroscopic models for traffic networks.

AU - Gning, A. C.

AU - Mihaylova, Lyudmila

AU - Boel, R.

PY - 2011/6

Y1 - 2011/6

N2 - The development of real-time traffic models is of paramount importance for the purposes of optimising traffic flow. Inspired by the compositional model (CM) [1] and the METANET model [2], [3], this paper proposes an interval approach for macroscopic traffic modeling. We develop an interval compositional model (ICM) and an interval implementation of METANET model (IMETANET) that provide a natural way of predicting traffic flows without the assumption of uniform distribution of vehicles in a cell. The interval macroscopic models are suitable for real-time applications in road networks and can be part of road traffic surveillance and control systems. The performance of the interval approaches are investigated for both the ICM and the IMETANET models. The efficiency of the interval models is demonstrated over simulated data and also over real traffic data from the United Kingdom, from MIDAS data sets.

AB - The development of real-time traffic models is of paramount importance for the purposes of optimising traffic flow. Inspired by the compositional model (CM) [1] and the METANET model [2], [3], this paper proposes an interval approach for macroscopic traffic modeling. We develop an interval compositional model (ICM) and an interval implementation of METANET model (IMETANET) that provide a natural way of predicting traffic flows without the assumption of uniform distribution of vehicles in a cell. The interval macroscopic models are suitable for real-time applications in road networks and can be part of road traffic surveillance and control systems. The performance of the interval approaches are investigated for both the ICM and the IMETANET models. The efficiency of the interval models is demonstrated over simulated data and also over real traffic data from the United Kingdom, from MIDAS data sets.

KW - Traffic modeling

KW - interval methods

KW - macroscopic models

KW - compositional model

KW - METANET model

U2 - 10.1109/TITS.2011.2107900

DO - 10.1109/TITS.2011.2107900

M3 - Journal article

VL - 12

SP - 523

EP - 526

JO - IEEE Transactions on Intelligent Transportation Systems

JF - IEEE Transactions on Intelligent Transportation Systems

SN - 1524-9050

IS - 2

ER -