Traffic state estimation (TSE) is a critical task for intelligent transportation systems. However,
it is extremely challenging because the traffic data quality is often affected by the installation …

This review offers a comprehensive overview of current traffic modeling, estimation, and
control methods, along with resulting field experiments. It highlights key developments and …

Advancements in sensor technologies, vehicle automation, communication, and intelligent
transportation systems create unforeseen possibilities for the development of novel traffic …

Traffic incidents disrupt the normal flow of vehicles and induce nonrecurrent traffic
congestion. It has been well accepted that the shape of the spatiotemporal region impacted …

This paper addresses model-based approach considering online model parameters
estimation to estimate the real-time freeway traffic state for inhomogeneous traffic flow. Its …

Reliable, real-time prediction of delay and density is challenging as direct measurement of
these variables is difficult. Though studies yielding reasonably accurate predictions of delay …

There has been extensive research in traffic state estimation that accounts for the stochastic
nature of traffic flow models. However, these studies often exhibit limitations such as an …

Better traffic estimation can be achieved by integrating multiple data sources. However, it is
not an easy task due to many issues such as differences in formats, spatio-temporal …

Accurate traffic state estimation is essential for the successful application of intelligent
transportation systems (ITS). In the past, traffic state estimation methods based on the macro …

Near stationary traffic states are of great significance for the calibration of the fundamental
diagram and the quantification of capacity variation. In this paper, based on wavelet …