… 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 …

… a Kalman filtering method based on the idea of input-output models (42). First, the traffic
volume… Then, considering the estimated error, a Kalman filtering method is proposed to estimate …

… For urban arterial roads where medium and high traffic volume are expected (as in this study),
0 … Under the exceptional cases when the volume of traffic and the penetration rate of probe …

… In this paper, a new traffic state estimation model by using Lagrangian-space Kalman filter
is … to fit the Kalman filter framework. The corresponding state-updating matrices for various …

… An estimation engine is developed according to the Extended Kalman Filter (EKF) theory,
that tries to estimate the real state of the multi-region dynamic system based on traffic sensors …

… [35] proposed an SCTM framework that extends STM to consider the spatial–temporal
correlation between traffic volume and to support short-term traffic state forecasting. Although …

… amount of noisy real-time measurements. Although it was originally derived for linear systems,
the Kalman filter … , is the so-called Extended Kalman Filter (EKF). This methodology can be …

… We hence develop the Kalman filter for de-noising while preserving the useful signals by …
We reformulate the Kalman filter with a new cost function, and develop a robust traffic flow …

… ) be mitigated using intelligent transport systems (ITS), which yield congestion mitigation
solutions using real-time traffic status, such as traffic volume, vehicle speed, and traffic density. …

… This paper presents a novel dual Kalman filter for short-term traffic flow forecasting. Our key
… of the traditional Kalman filter and the RW model. In our mechanism, the Kalman filter can …