Traffic state prediction is a key component in intelligent transport systems (ITS) and has
attracted much attention over the last few decades. Advances in computational power and …

We develop a deep learning model to predict traffic flows. The main contribution is
development of an architecture that combines a linear model that is fitted using ℓ 1 …

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 …

Since the early 1980s, short-term traffic forecasting has been an integral part of most
Intelligent Transportation Systems (ITS) research and applications; most effort has gone into …

This paper proposes a new method in construction fuzzy neural network to forecast travel
speed for multi-step ahead based on 2-min travel speed data collected from three remote …

Traffic speed prediction is a long-standing and critically important topic in the area of
Intelligent Transportation Systems (ITS). Recent years have witnessed the encouraging …

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 …

Intelligent Transportation System (ITS) has been emerged an important component and
widely adopted for the smart city as it overcomes the limitations of the traditional …

This paper proposes a novel neural network (NN) training method that employs the hybrid
exponential smoothing method and the Levenberg-Marquardt (LM) algorithm, which aims to …

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 …