self-learning-longitudinal-control-for-on-road-vehicles.pdf
Reinforcement Learning is a promising tool to automate controller tuning. However, significant extensions are required for real-world applications to enable fast and robust learning. This work proposes several additions to the state of the art and proves their capability in a series of real world ex...
| Language: | English |
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| Published: |
KIT Scientific Publishing
2023
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| Online Access: | https://doi.org/10.5445/KSP/1000156966 |
| Summary: | Reinforcement Learning is a promising tool to automate controller tuning. However, significant extensions are required for real-world applications to enable fast and robust learning. This work proposes several additions to the state of the art and proves their capability in a series of real world experiments. |
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