Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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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 -