The ability to accurately predict the trajectory of surrounding vehicles is a critical hurdle to
overcome on the journey to fully autonomous vehicles. To address this challenge, we …

Self-supervised representation learning methods have achieved significant success in
computer vision and natural language processing (NLP), where data samples exhibit explicit …

In the field of autonomous vehicles (AVs), accurately discerning commander intent and
executing linguistic commands within a visual context presents a significant challenge. This …

In the burgeoning field of autonomous vehicles (AVs), trajectory prediction remains a
formidable challenge, especially in mixed autonomy environments. Traditional approaches …

Given the rapid advancement of autonomous driving technology, discerning public
willingness to pay and anticipated driving behavior for autonomous vehicles is crucial for …

In autonomous vehicle (AV) technology, the ability to accurately predict the movements of
surrounding vehicles is paramount for ensuring safety and operational efficiency …

Context information provided along with a dataset can be very helpful for solving a problem
because the additional knowledge is already available and does not need to be extracted …

Autonomous transportation systems such as road vehicles or vessels require the
consideration of the static and dynamic environment to dislocate without collision …