As a crucial component in intelligent transportation systems, traffic flow prediction has
recently attracted widespread research interest in the field of artificial intelligence (AI) with …

Accurate urban traffic prediction is a critical issue in Intelligent Transportation Systems (ITS).
It is challenging since urban traffic usually indicates high dynamic spatio-temporal …

Short-term traffic flow prediction is a critical aspect of Intelligent Transportation System.
Timely and accurate traffic forecasting results are necessary inputs for advanced traffic …

Several univariate and multivariate models have been proposed for performing short-term
forecasting of traffic flow. Two different univariate [historical average and ARIMA …

Short-term traffic flow prediction has long been regarded as a critical concern for intelligent
transportation systems. On the basis of many existing prediction models, each having good …

Short‐term traffic speed prediction is one of the most critical components of an intelligent
transportation system (ITS). The accurate and real‐time prediction of traffic speeds can …

The ability to accurately predict traffic speed in a large and heterogeneous road network has
many useful applications, such as route guidance and congestion avoidance. In principle …

For the first time, real-time high-fidelity spatiotemporal data on transportation networks of
major cities have become available. This gold mine of data can be utilized to learn about …

This paper formulates the traffic flow forecasting task by introducing a maximum correntropy
deduced Kalman filter. The traditional Kalman filter is based on minimum mean square error …

Short-term traffic prediction on freeways is one of the critical components of advanced
traveler information systems. The traditional methods of prediction have used univariate …