… to deal with the nonlinearity of traffic but is also more complex than the Kalman Filters. In [33]…
speed of the filter. Because the goal of this paper is to enable real-time filtering for large-…

… We develop a Kalman filter for predicting traffic flow at urban arterials based on data obtained
from connected vehicles. The proposed algorithm is computationally efficient and offers a …

… extended) Kalman filtering is a technique that combines suitably two sources of knowledge,
namely, real measurement data and process model; the combination is regulated by the filter’…

… percentage with respect to traffic levels and time of day are … of AKF and KF for different traffic
levels and time of day groups, … find that for volatile traffic condition at higher traffic levels (G3, …

… The approach proposed in this work employs Ensemble Kalman Filtering (EnKF), which
enables the use of fully nonlinear evolution equations such as the discretization of the new flow …

… A normal distribution for the model variables is a useful property for the available statistical
tools such as some of the Kalman filter extensions used in this research (the UKF does not …

… A simple, general and complete approach to the design of freeway traffic state estimator has
been developed in this paper based on the extended Kalman filter methodology. A number …

… -term traffic volume prediction model using the Kalman filter … and validated using traffic volume
dataset collected from a real … traffic volumes compare very closely with the observed traffic …

… and prediction of the Kalman filter forecasting model, which was established above, in this
paper, we want to make a simulation for the traffic volume forecasting by using traffic flow data …