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 …

The purpose of this study is to summarize the pattern recognition (PR) and deep learning
(DL) artificial intelligence methods developed for the management of data in the last six …

The connected environment provides surrounding traffic information to drivers via different
driving aids that are expected to improve driving behavior and assist in avoiding safety …

Abstract Recently released Autonomous Vehicle (AV) trajectory datasets can potentially
catalyze research progress on AV-oriented traffic flow analysis. This paper aims to …

Previous empirical behavior analysis on Autonomous Vehicles (AV) mainly focused on
vehicles with Adaptive Cruise Control (ACC) system due to the lack of high-level AV dataset …

This study develops a Complete LAne-Changing Decision (CLACD) modeling framework
that explains both the mandatory and discretionary lane-changing behaviors, incorporates …

Shipping is one of the major transportation approaches around the world. With the growing
demands for global shipping service, vessel destination prediction has shown its significant …

This paper incorporates the driver compliance behaviour into a connected vehicle driving
strategy (CVDS) that can be integrated with traditional car-following (CF) models to better …

Urban road transportation performance is the result of a complex interplay between the
network supply and the travel demand. Fortunately, the framework around the macroscopic …

Numerous statistical and data-driven modeling frameworks have estimated rear-end
crashes and crash-prone events from macroscopic traffic states which are at the heart of …