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Human driven vehicles (HDVs) with selfish objectives cause low traffic efficiency in an un-signalized intersection. On the other hand, autonomous vehicles can overcome this inefficiency through perfect coordination. In t...

In a mixed traffic environment consisting of connected autonomous vehicles (CAVs) and human-driven vehicles (HVs), platooning intensity serves as a critical metric, quantifying the strength of CAV clustering, with inhere...

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...

Recent studies and industry developments indicate that modular autonomous vehicles (MAVs) have the potential to enhance transportation systems by offering vehicles with adjustable capacities en route. However, the practi...

Unmanned aerial vehicles (UAVs) are increasingly crucial across various fields. There is a growing interest in using federated learning (FL) methods to enhance the efficiency of UAV operations. Nevertheless, incumbent me...

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...

This research presents a multi-objective optimization framework for incremental siting of capacitated vertiports that integrates real land use data and aims to maximize generalized cost savings while minimizing infrastru...

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...