In the current age of the Fourth Industrial Revolution (4 IR or Industry 4.0), the digital world
has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data …

Traffic forecasting is important for the success of intelligent transportation systems. Deep
learning models, including convolution neural networks and recurrent neural networks, have …

Abstract Machine learning and artificial intelligence (ML/AI), previously considered black box
approaches, are becoming more interpretable, as a result of the recent advances in …

Traffic prediction plays a crucial role in alleviating traffic congestion which represents a
critical problem globally, resulting in negative consequences such as lost hours of additional …

Traffic flow prediction is important for urban planning and traffic congestion alleviation as
well as for intelligent traffic management systems. Due to the periodic characteristics and …

With the development of smart cities, new requirements have been put forward for the
control of carbon emissions (CEs) in the transportation system. Intelligent transportation …

The availability of digital technology in the hands of every citizenry worldwide makes an
available unprecedented massive amount of data. The capability to process these gigantic …

Traffic prediction plays an essential role in intelligent transportation system. Accurate traffic
prediction can assist route planing, guide vehicle dispatching, and mitigate traffic …

In recent decades, the development of transport infrastructure has had a great development,
although traffic problems continue to spread due to increase due to the increase in the …

Traffic forecasting has been regarded as the basis for many intelligent transportation system
(ITS) applications, including but not limited to trip planning, road traffic control, and vehicle …