Exploring applications of deep reinforcement learning for real-world autonomous driving systems

@inproceedings{Talpaert2019ExploringAO,
  title={Exploring applications of deep reinforcement learning for real-world autonomous driving systems},
  author={V. Talpaert and Ibrahim Sobh and B. R. Kiran and P. Mannion and S. Yogamani and Ahmad El Sallab and P. P{\'e}rez},
  booktitle={VISIGRAPP},
  year={2019}
}
Deep Reinforcement Learning (DRL) has become increasingly powerful in recent years, with notable achievements such as Deepmind's AlphaGo. It has been successfully deployed in commercial vehicles like Mobileye's path planning system. However, a vast majority of work on DRL is focused on toy examples in controlled synthetic car simulator environments such as TORCS and CARLA. In general, DRL is still at its infancy in terms of usability in real-world applications. Our goal in this paper is to… Expand
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