The prediction of short-term traffic flow is critical for improving service levels for drivers and
passengers as well as enhancing the efficiency of traffic management in the urban …

With the rapid development of social economy, the traffic volume of urban roads has raised
significantly, which has led to increasingly serious urban traffic congestion problems, and …

Abstract Short-term Electric Vehicle (EV) charging demand prediction is an essential task in
the fields of smart grid and intelligent transportation systems, as understanding the …

Road transportation is the largest and complex nonlinear entity of the traffic management
system. Accurate prediction of traffic-related information is necessary for an effective …

Connected vehicles and fully automated driving systems are the main objectives of the
future transportation system. A safe interactive system that interacts with people and things is …

Traffic flow prediction with high accuracy is definitely considered as one of most important
parts in the Intelligent Transportation Systems. As interfering by some external factors, the …

Traffic flow forecasting is a necessary part in the intelligent transportation systems in
supporting dynamic and proactive traffic control and making traffic management plan …

Traffic flow prediction is an important research problem in many of the Intelligent
Transportation Systems (ITS) applications. The use of Autoregressive Integrated Moving …

Short-term traffic flow analysis is the core part of the intelligent transportation system, and
also the critical basis for traffic management and control system to guide traffic flow. Real …

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 …