Short-term traffic flow forecasting is a fundamental and challenging task due to the stochastic
dynamics of the traffic flow, which is often imbalanced and noisy. This paper presents a …

Accurate and timely traffic flow forecasting is essential for many intelligent transportation
systems. However, it is quite challenging to develop an efficient and robust forecasting …

Traffic flow forecasting plays a vital role in the transportation domain. Existing studies usually
manually construct correlation graphs and design sophisticated models for learning spatial …

Accurate and reliable traffic flow forecasting is of importance for urban planning and
mitigation of traffic congestion, and it is also the basis for the deployment of intelligent traffic …

Traffic flow forecasting is the cornerstone of the development of intelligent transportation
systems. Accurate forecasting is conducive to the control and management of urban traffic …

One contemporary policy to deal with traffic congestion is the design and implementation of
forecasting methods that allow users to plan ahead of time and decision makers to improve …

Traffic flow prediction has various applications such as in traffic systems and autonomous
driving. Road conditions have become increasingly complex, and this, in turn, has increased …

Deep learning approaches have reached a celebrity status in artificial intelligence field, its
success have mostly relied on Convolutional Networks (CNN) and Recurrent Networks. By …

Forecasting short-term traffic flow is one critical component in traffic management to improve
operational efficiency. Data driven method, which trains the predictor with historical data …

In this paper, we study how to jointly predict travel demands and traffic flows for all regions of
a city at a future time interval. From an empirical analysis of traffic data, we outline three …