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Dec 9, 2020 · The proposed method is worked effectively to train an agent to control the simulated car in Unity ML-agents Highway, which is a simulating ...
An approach by using of Policy Gradient to control a simulated car via reinforcement learning to solve the difficult problems of accurate detection of ...
We investigate the use of Deep Q-Learning to control a simulated car via reinforcement learning. We start by im- plementing the approach of [5] ourselves, and ...
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In this paper, a Deep Reinforcement Learning (DRL) method is exploited to model the decision making and interaction between vehicles on highway driving.
Request PDF | On Jan 1, 2021, Anh Huynh and others published A Method of Deep Reinforcement Learning for Simulation of Autonomous Vehicle Control | Find, read
Mar 15, 2024 · This study proposes a deep reinforcement learning-based lane-changing model to train autonomous vehicles to complete lane-changing in the interaction with ...
Jan 13, 2022 · This paper proposes the using of algorithms based on Deep Learning (DL) in the control layer of an autonomous vehicle.
The use of Deep Q-Learning to control a simulated car via reinforcement learning is investigated, and an agent is successfully able to train an agent to ...
This thesis offers a structured review of the latest literature on Deep Reinforcement Learning (DRL) within the realm of autonomous vehicle Path Planning and ...
Oct 17, 2024 · Our proposed approach helps bridge the gaps between different platforms and the Simulation to Reality (Sim2Real) gap, allowing the trained agent ...