RACE-SM: Reinforcement Learning Based Autonomous Control for Social On-Ramp Merging
J Poots - arXiv preprint arXiv:2403.03359, 2024 - arxiv.org
Autonomous parallel-style on-ramp merging in human controlled traffic continues to be an
existing issue for autonomous vehicle control. Existing non-learning based solutions for …
existing issue for autonomous vehicle control. Existing non-learning based solutions for …
[HTML][HTML] A Review on Reinforcement Learning-based Highway Autonomous Vehicle Control
Autonomous driving is an active area of research in artificial intelligence and robotics.
Recent advances in deep reinforcement learning (DRL) show promise for training …
Recent advances in deep reinforcement learning (DRL) show promise for training …
Deep multi-agent reinforcement learning for highway on-ramp merging in mixed traffic
On-ramp merging is a challenging task for autonomous vehicles (AVs), especially in mixed
traffic where AVs coexist with human-driven vehicles (HDVs). In this paper, we formulate the …
traffic where AVs coexist with human-driven vehicles (HDVs). In this paper, we formulate the …
Multi-agent reinforcement learning for cooperative lane changing of connected and autonomous vehicles in mixed traffic
Autonomous driving has attracted significant research interests in the past two decades as it
offers many potential benefits, including releasing drivers from exhausting driving and …
offers many potential benefits, including releasing drivers from exhausting driving and …
Nash double Q-based multi-agent deep reinforcement learning for interactive merging strategy in mixed traffic
The interaction between ramp and mainline vehicles plays a crucial role in merging areas,
especially in the mixed-traffic environment. The driving behaviours of human drivers are …
especially in the mixed-traffic environment. The driving behaviours of human drivers are …
Autonomous lane merging: A comparison between reinforcement learning algorithms
PE Sharouni - 2021 - studenttheses.uu.nl
Despite the advancements of self-driving cars, autonomous on-ramp merging on highways
still proposes difficulties. To solve this merge problem a simulation was set up in the Unity …
still proposes difficulties. To solve this merge problem a simulation was set up in the Unity …
Graph-based multi agent reinforcement learning for on-ramp merging in mixed traffic
D Xu, B Zhang, Q Qiu, H Li, H Guo, B Wang - Applied Intelligence, 2024 - Springer
Abstract The application of Deep Reinforcement Learning (DRL) has significantly impacted
the development of autonomous driving technology in the field of intelligent transportation …
the development of autonomous driving technology in the field of intelligent transportation …
Harmonious lane changing via deep reinforcement learning
In this paper, we study how to learn a harmonious deep reinforcement learning (DRL) based
lane-changing strategy for autonomous vehicles without Vehicle-to-Everything (V2X) …
lane-changing strategy for autonomous vehicles without Vehicle-to-Everything (V2X) …
Developing a merge lane change decision policy for autonomous vehicles by deep reinforcement learning
B Fan, Y Zhou, H Mahmassani - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
With autonomous vehicles (AVs) being actively developed, it becomes possible to optimize
vehicle control policies and traffic management tools in a mixed vehicular environment. For …
vehicle control policies and traffic management tools in a mixed vehicular environment. For …
Social learning in Markov games: Empowering autonomous driving
In a multi-agent system (MAS), a social learning scheme allows independent agents to learn
through interactions with agents randomly selected from a pool. Such a scheme is important …
through interactions with agents randomly selected from a pool. Such a scheme is important …