Traffic volume propagating from upstream road link to downstream road link is the key
parameter for designing intersection signal timing scheme. Recent works successfully used …

Abstract Autonomous Vehicles (AVs) have made remarkable developments and are
anticipated to replace human drivers. In transitioning from human-driven vehicles to fully …

Accurate prediction of ship emissions aids to ensure maritime sustainability but encounters
challenges, such as the absence of high-precision and high-resolution databases, complex …

Since the inception of the China–Europe Railway Express (CRE), rail transportation has
emerged as a predominant means of transporting goods across international borders. The …

Forecasting vehicles' future motion is crucial for real-world applications such as the
navigation of autonomous vehicles and feasibility of safety systems based on the Internet of …

Travel time reliability (TTR) is an essential measure of service for traffic performance
management, especially for congested freeway corridors. This paper proposes a systematic …

In this article, we propose a new method for OD (Origin–Destination)​ matrix prediction
based on traffic data using deep learning. The input values of the developed model were …

Due to the complexity of experiments to test driving behaviors and the high cost of data
collection for some types of vehicles, eg, heavy-duty freight vehicles, it is normally hard to …

With the advent of the Internet of Things (IoT), it has become possible to have a variety of
data sets generated through numerous types of sensors deployed across large urban areas …

Accurate spatial-temporal traffic modeling and prediction play an important role in intelligent
transportation systems (ITS). Recently, various deep learning methods such as graph …