Interval macroscopic models for traffic networks.

Gning, A. C. and Mihaylova, Lyudmila and Boel, R. (2011) Interval macroscopic models for traffic networks. IEEE Transactions on Intelligent Transportation Systems, 12 (2). pp. 523-526. ISSN 1524-9050

Full text not available from this repository.


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.

Item Type:
Journal Article
Journal or Publication Title:
IEEE Transactions on Intelligent Transportation Systems
Uncontrolled Keywords:
ID Code:
Deposited By:
Deposited On:
07 Jan 2011 16:04
Last Modified:
21 Nov 2022 20:13