The volume and availability of data in the Intelligent Transportation System (ITS) result in the
need for data-driven approaches. Big Data algorithms are applied to further enhance the …

In the last few years, there has been an exponential increase in the usage of the
autonomous vehicles across the globe. It is due to an exponential increase in the popularity …

Accurate short-time traffic flow prediction has gained gradually increasing importance for
traffic plan and management with the deployment of intelligent transportation systems (ITSs) …

Abstract Intelligent Transportation Systems (ITS) have attracted an increasing amount of
attention in recent years. Thanks to the fast development of vehicular computing hardware …

Reliable traffic prediction is critical to improve safety, stability, and efficiency of intelligent
transportation systems. However, traffic prediction is a very challenging problem because …

This paper proposes a convolutional neural network (CNN)-based method that learns traffic
as images and predicts large-scale, network-wide traffic speed with a high accuracy …

This study aims to combine the modeling skills of deep learning and the domain knowledge
in transportation into prediction of metro passenger flow. We present an end-to-end deep …

Accurate and timely traffic flow information is important for the successful deployment of
intelligent transportation systems. Over the last few years, traffic data have been exploding …

Abstract Machine learning (ML) plays the core function to intellectualize the transportation
systems. Recent years have witnessed the advent and prevalence of deep learning which …

The accurate short-term traffic flow prediction can provide timely and accurate traffic
condition information which can help one to make travel decision and mitigate the traffic jam …