As automobiles become increasingly autonomous, there is growing interest in personalized
automation based on human behavior. However, there is an increasing need for behavioral …

Driving maneuver decision-making is critical to the development and mass deployment of
automated vehicles (AVs). The prevailing approaches are stuck with either specific …

Designing a secure and reliable decision-planning model for vehicle lane changing is of
utmost practical significance because it is one of the most frequent driving behaviors and …

This paper presents an approach for modeling driver lane change behavior using inverse
reinforcement learning (IRL). The driver behaviors are assumed to be the solution of an …

Autonomous driving technology has gained significant attention, offering opportunities to
modernize transportation systems worldwide. Deep reinforcement learning (DRL) has …

Quantitative assessment of driving performances and analysis of different driving styles are
significantly critical for the mass employment of automated vehicles (AVs). There-fore, this …