Multi-agent reinforcement learning for autonomous vehicles: A survey
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 …
traffic. This cohabitation raises serious challenges, both in terms of traffic flow and individual …
High-definition map representation techniques for automated vehicles
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 …
and localization. The goal of map representation is to summarize spatial information in …
Social coordination and altruism in autonomous driving
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 …
still inefficient and limited in terms of cooperating with each other or coordinating with …
Robustness and adaptability of reinforcement learning-based cooperative autonomous driving in mixed-autonomy traffic
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 real world where they will be surrounded by human-driven vehicles (HVs) is extremely …
Intelligent cooperative collision avoidance at overtaking and lane changing maneuver in 6G-V2X communications
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 …
towards road safety in recent days. Particularly, a higher number of road accidents occurs …
Active uncertainty reduction for safe and efficient interaction planning: A shielding-aware dual control approach
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 …
robotic systems in interactive settings, such as human–robot interaction and multi-robot …
A cooperative optimal control framework for connected and automated vehicles in mixed traffic using social value orientation
VA Le, AA Malikopoulos - 2022 IEEE 61st Conference on …, 2022 - ieeexplore.ieee.org
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 …
motion planning problem for connected and automated vehicles (CAVs) in mixed traffic …
Predictive trajectory planning for autonomous vehicles at intersections using reinforcement learning
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 …
vehicles plan future trajectories. We develop a partially observable Markov decision process …
Altruistic maneuver planning for cooperative autonomous vehicles using multi-agent advantage actor-critic
With the adoption of autonomous vehicles on our roads, we will witness a mixed-autonomy
environment where autonomous and human-driven vehicles must learn to co-exist by …
environment where autonomous and human-driven vehicles must learn to co-exist by …
Active uncertainty reduction for human-robot interaction: An implicit dual control approach
The ability to accurately predict human behavior is central to the safety and efficiency of
robot autonomy in interactive settings. Unfortunately, robots often lack access to key …
robot autonomy in interactive settings. Unfortunately, robots often lack access to key …