@article{ref1,
title="Macroscopic traffic characterization based on driver memory and traffic stimuli",
journal="Transportation engineering (Amsterdam)",
year="2023",
author="Khan, Zawar H. and Imran, Waheed and Gulliver, T. Aaron and Khattak, Khurram S. and Din, Ghayas Ud and Minallah, Nasru and Khan, Mushtaq A.",
volume="14",
number="",
pages="e100208-e100208",
abstract="A new macroscopic traffic flow model is proposed which incorporates traffic alignment behavior at transitions. In this model, velocity is a function of the distance headway and driver response time. It can be used to characterize the traffic flow for both uniform and non uniform headways. The well-known Zhang model characterizes this flow based on driver memory which can produce unrealistic results. The performance of the proposed Khan-Imran-Gulliver (KIG) and Zhang models is evaluated for an inactive bottleneck on a 2000 m circular road. The results obtained show that the traffic behavior with the KIG model is more realistic.<p /> <p>Language: en</p>",
language="en",
issn="2666-691X",
doi="10.1016/j.treng.2023.100208",
url="http://dx.doi.org/10.1016/j.treng.2023.100208"
}