… of the Kalman filter model for traffic volume forecasting is discussed first, and the wavelet
Kalman filter … of DWT analysis and Kalman filter theory in short-term traffic volume forecasting. …

… -adaption of Kalman filter theory is poor and time-lag [13]. In view of this shortcoming, this
paper proposes the Kalman filtering algorithm for studying shortterm traffic volume forecasting …

… This paper addresses the design and operation of a Kalman filter" that processes traffic
sensor data in order to model and predict highway traffic volume. This data was given in the form …

… obtain the link traffic counts data). In these three scenarios, the traffic counts are available on
… Here, we assume traffic counts are available on all links (Scenario 1); counts are available …

… coming under Intelligent Transportation Systems (ITS). … Prediction of traffic volume is an
important research problem … reported for prediction of traffic volume are regression, neural …

… based on Kalman filter theory. The prediction problem is reformulated as a filtering one by
using … Stephanedes, “Dynamic prediction of traffic volume through Kalman filtering theory,” …

… On the other hand, the most ubiquitous traffic measurement is traffic counts. Therefore, the
two first measures of effectiveness are based on fit of estimated (predicted) speeds and counts …

… employing Kalman filtering theory are proposed for predicting short-term traffic volume. …
Owing to its desirable characteristics Kalman filtering theory is employed for developing the …

… Wakahara, ”Real-time urban traffic amount prediction models for dynamic route guidance
systems,” EURASIP Journal on Wireless Communications and Networking, no. 85, May 2014. […

… traffic data. Second, this ARIMA model is combined with the Kalman filter to construct a road
traffic … The state variables in the experiments are the historical road traffic volume and speed …