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 …
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 …
S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles
X Wang, K Tang, X Dai, J Xu, Q Du, R Ai… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In public roads, autonomous vehicles (AVs) face the challenge of frequent interactions with
human-driven vehicles (HDVs), which render uncertain driving behavior due to varying …
human-driven vehicles (HDVs), which render uncertain driving behavior due to varying …
Learning in Cooperative Multiagent Systems Using Cognitive and Machine Models
Developing effective multi-agent systems (MASs) is critical for many applications requiring
collaboration and coordination with humans. Despite the rapid advance of multi-agent deep …
collaboration and coordination with humans. Despite the rapid advance of multi-agent deep …
Towards socially responsive autonomous vehicles: A reinforcement learning framework with driving priors and coordination awareness
The advent of autonomous vehicles (AVs) alongside human-driven vehicles (HVs) has
ushered in an era of mixed traffic flow, presenting a significant challenge: the intricate …
ushered in an era of mixed traffic flow, presenting a significant challenge: the intricate …
Prediction-Aware and Reinforcement Learning-Based Altruistic Cooperative Driving
Autonomous vehicle (AV) navigation in the presence of Human-driven vehicles (HVs) is
challenging, as HVs continuously update their policies in response to AVs. In order to …
challenging, as HVs continuously update their policies in response to AVs. In order to …
Enhancing Social Decision-Making of Autonomous Vehicles: A Mixed-Strategy Game Approach With Interaction Orientation Identification
The integration of Autonomous Vehicles (AVs) into existing human-driven traffic systems
poses considerable challenges, especially within environments where human and machine …
poses considerable challenges, especially within environments where human and machine …
[PDF][PDF] Active uncertainty learning for human-robot interaction: An implicit dual control approach
Predictive models are effective in reasoning about human motion, a crucial part that affects
safety and efficiency in human-robot interaction. However, robots often lack access to certain …
safety and efficiency in human-robot interaction. However, robots often lack access to certain …
Responsibility-associated multi-agent collision avoidance with social preferences
This paper introduces a novel social preference-aware decentralized safe control framework
to address the responsibility allocation problem in multi-agent collision avoidance …
to address the responsibility allocation problem in multi-agent collision avoidance …
Learning-based social coordination to improve safety and robustness of cooperative autonomous vehicles in mixed traffic
It is expected that autonomous vehicles (AVs) and heterogeneous human-driven vehicles
(HVs) will coexist on the same road. The safety and reliability of AVs will depend on their …
(HVs) will coexist on the same road. The safety and reliability of AVs will depend on their …