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 …
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 …
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 …
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 interaction-aware guidance for trajectory optimization in dense traffic scenarios
B Brito, A Agarwal… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Autonomous navigation in dense traffic scenarios remains challenging for autonomous
vehicles (AVs) because the intentions of other drivers are not directly observable and AVs …
vehicles (AVs) because the intentions of other drivers are not directly observable and AVs …
Interaction-aware decision-making for automated vehicles using social value orientation
Motion control algorithms in the presence of pedestrians are critical for the development of
safe and reliable Autonomous Vehicles (AVs). Traditional motion control algorithms rely on …
safe and reliable Autonomous Vehicles (AVs). Traditional motion control algorithms rely on …
Toward intelligent connected E-mobility: Energy-aware cooperative driving with deep multiagent reinforcement learning
In recent years, electrified mobility (e-mobility), especially connected and autonomous
electric vehicles (CAEVs), has been gaining momentum along with the rapid development of …
electric vehicles (CAEVs), has been gaining momentum along with the rapid development of …
Deep reinforcement learning for human-like driving policies in collision avoidance tasks of self-driving cars
R Emuna, A Borowsky, A Biess - arXiv preprint arXiv:2006.04218, 2020 - arxiv.org
The technological and scientific challenges involved in the development of autonomous
vehicles (AVs) are currently of primary interest for many automobile companies and …
vehicles (AVs) are currently of primary interest for many automobile companies and …
Sustainable Smart Cities through Multi-Agent Reinforcement Learning-Based Cooperative Autonomous Vehicles
As urban centers evolve into smart cities, sustainable mobility emerges as a cornerstone for
ensuring environmental integrity and enhancing quality of life. Autonomous vehicles (AVs) …
ensuring environmental integrity and enhancing quality of life. Autonomous vehicles (AVs) …
Learning interaction-aware guidance policies for motion planning in dense traffic scenarios
B Brito, A Agarwal, J Alonso-Mora - arXiv preprint arXiv:2107.04538, 2021 - arxiv.org
Autonomous navigation in dense traffic scenarios remains challenging for autonomous
vehicles (AVs) because the intentions of other drivers are not directly observable and AVs …
vehicles (AVs) because the intentions of other drivers are not directly observable and AVs …
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