Autonomous driving has achieved significant milestones in research and development over
the last two decades. There is increasing interest in the field as the deployment of …

In the near future, autonomous vehicles (AVs) may cohabit with human drivers in mixed
traffic. This cohabitation raises serious challenges, both in terms of traffic flow and individual …

Despite the advances in the autonomous driving domain, autonomous vehicles (AVs) are
still inefficient and limited in terms of cooperating with each other or coordinating with …

In this work we put forward a predictive trajectory planning framework to help autonomous
vehicles plan future trajectories. We develop a partially observable Markov decision process …

Building autonomous vehicles (AVs) is a complex problem, but enabling them to operate in
the real world where they will be surrounded by human-driven vehicles (HVs) is extremely …

The ability to accurately predict others' behavior is central to the safety and efficiency of
robotic systems in interactive settings, such as human–robot interaction and multi-robot …

Many studies in the field of robot navigation have focused on environment representation
and localization. The goal of map representation is to summarize spatial information in …

The rapid growth in Autonomous Vehicle (AV) technology endeavors increased attention
towards road safety in recent days. Particularly, a higher number of road accidents occurs …

In this paper, we develop a socially cooperative optimal control framework to address the
motion planning problem for connected and automated vehicles (CAVs) in mixed traffic …

Addressing safe and efficient interaction between connected and autonomous vehicles
(CAVs) and human-driven vehicles (HDVs) in a mixed-traffic environment has attracted …