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Research Article | Open Access

Improving the representation of traffic states: A novel method for link selection of urban road networks

Syed Muzammil Abbas Rizvi( )Bernhard Friedrich
Institute of Transportation and Urban Engineering, Technical University of Braunschweig, Braunschweig 38106, Germany
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Abstract

The macroscopic fundamental diagram (MFD) represents the aggregated traffic states of a road network. However, the uniqueness of an empirically estimated MFD cannot be guaranteed due to the problem of link selection. Instationarity and varying flow patterns make it difficult to select link flows that are representative of the traffic state in the whole network. This study developed a new method for selecting links equipped with loop detectors that represent a particular traffic state of a road network. The method utilizes a metric of heterogeneity characterizing the role of a network link over the time of day. The dispersion metric indicates the heterogeneity in traffic states and the dynamic role of each time interval. It ranks links based on the heterogeneity-weighted saturation level, with the highest-rank links representing the most homogeneous subset of sample links. This study compared classical and proposed dynamic weights using loop detector data from Zurich and London and a simulated network. Sample links were selected based on different saturation levels, and the saturation level was associated with the heterogeneity level to identify the links creating heterogeneity in the road network.

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Journal of Intelligent and Connected Vehicles
Pages 266-278

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Cite this article:
Rizvi SMA, Friedrich B. Improving the representation of traffic states: A novel method for link selection of urban road networks. Journal of Intelligent and Connected Vehicles, 2024, 7(4): 266-278. https://doi.org/10.26599/JICV.2023.9210047

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Received: 13 December 2023
Revised: 21 February 2024
Accepted: 29 April 2024
Published: 31 December 2024
© The author(s) 2023.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).