In this paper, we review trajectory data-based traffic flow studies that have been conducted
over the last 15 years. Our purpose is to provide a roadmap for readers who have an interest …

Intelligent transportation systems based on automated data collection frameworks are widely
used by the major transit companies around the globe. This paper describes the current …

Traffic energy consumption estimation is significant for the sustainable transportation.
However, it is difficult to directly employ macro traffic flow data to accurately estimate the …

Fusing freeway traffic data such as spot speeds and travel times from a variety of traffic
sensors (loops, cameras, automated vehicle identification systems) into a coherent …

High-speed railway (HSR) systems have been developing rapidly in China and various
other countries throughout the past decade; as a result, the question of how to efficiently …

There has been significant interest in plug-in hybrid electric vehicles (PHEVs) as a means to
decrease dependence on imported oil and to reduce greenhouse gases as well as other …

The development of technologies related to connected and automated vehicles (CAVs)
allows for a new approach to collect vehicle trajectory. However, trajectory data collected in …

Abstract This paper studies Deep Convolutional Neural Networks (DCNNs) for the accurate
estimation of space–time traffic speeds given sparse data on freeways. Several aspects are …

Microscopic emission models estimate second-by-second emissions and fuel consumption
for individual vehicles based on vehicle trajectories. A vehicle trajectory describes how the …

While lane-changing movements are performed on the entire motorway network for various
reasons, such as overtaking, their intensity is substantially greater near complex segments …