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Vehicle trajectory data have become essential for many research fields, such as traffic flow, traffic safety, and automated driving. To make trajectory data useable for researchers, an overview of the included road secti...

Communication delays within connected and autonomous vehicles (CAVs) pose significant risks. It is imperative to address these issues to ensure the safe and effective operation of CAVs. However, the exploration of commun...

Understanding public perception of electric vehicles (EVs) is imperative for increasing EV adoption, which can significantly reduce greenhouse gas (GHG) emissions, thereby mitigating climate change and global warming. Wh...

While physics models for predicting system states can reveal fundamental insights owing to their parsimonious structure, they may not always yield the most accurate predictions, particularly for complex systems. As an al...

Mandatory lane changes (MLCs) pose significant challenges to trajectory planning at intersections, where vehicles are required to change lanes mid-block to reach designated turn lanes before the stop bar. MLCs often gene...

High-granularity vehicle trajectory data can help researchers develop traffic simulation models, understand traffic flow characteristics, and thus propose insightful strategies for road traffic management. This paper pro...

Artificial intelligence and advanced sensing technologies have significantly advanced the intelligent transportation system and autonomous vehicles. Perception, a critical component, extracts real-time traffic informatio...