Decision-making of autonomous driving based on reinforcement learning
This project aims to utilize a particular machine learning technique called reinforcement learning (RL) in order to develop a particular technological aspect of autonomous vehicles (AV) called decision-making. A few commonly used RL algorithms such as PPO, SAC & TD3 will be implemented along wit...
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| 格式: | Final Year Project |
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Nanyang Technological University
2024
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sg-ntu-dr.10356-1778782024-06-03T08:38:18Z Decision-making of autonomous driving based on reinforcement learning Shi, Max Ziyi Lyu Chen School of Mechanical and Aerospace Engineering lyuchen@ntu.edu.sg Computer and Information Science Engineering This project aims to utilize a particular machine learning technique called reinforcement learning (RL) in order to develop a particular technological aspect of autonomous vehicles (AV) called decision-making. A few commonly used RL algorithms such as PPO, SAC & TD3 will be implemented along with optimization in order to build and train RL models that will allow a self-driving car in a simulated environment to operate autonomously. The models are evaluated based on quantitative metrics that ensures safety and dynamic performance of the AV. Bachelor's degree 2024-06-03T08:38:18Z 2024-06-03T08:38:18Z 2024 Final Year Project (FYP) Shi, M. Z. (2024). Decision-making of autonomous driving based on reinforcement learning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/177878 https://hdl.handle.net/10356/177878 en C050 application/pdf Nanyang Technological University |
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Computer and Information Science Engineering Shi, Max Ziyi Decision-making of autonomous driving based on reinforcement learning |
| description |
This project aims to utilize a particular machine learning technique called reinforcement learning (RL) in order to develop a particular technological aspect of autonomous vehicles (AV) called decision-making. A few commonly used RL algorithms such as PPO, SAC & TD3 will be implemented along with optimization in order to build and train RL models that will allow a self-driving car in a simulated environment to operate autonomously. The models are evaluated based on quantitative metrics that ensures safety and dynamic performance of the AV. |
| author2 |
Lyu Chen |
| author_facet |
Lyu Chen Shi, Max Ziyi |
| format |
Final Year Project |
| author |
Shi, Max Ziyi |
| author_sort |
Shi, Max Ziyi |
| title |
Decision-making of autonomous driving based on reinforcement learning |
| title_short |
Decision-making of autonomous driving based on reinforcement learning |
| title_full |
Decision-making of autonomous driving based on reinforcement learning |
| title_fullStr |
Decision-making of autonomous driving based on reinforcement learning |
| title_full_unstemmed |
Decision-making of autonomous driving based on reinforcement learning |
| title_sort |
decision-making of autonomous driving based on reinforcement learning |
| publisher |
Nanyang Technological University |
| publishDate |
2024 |
| url |
https://hdl.handle.net/10356/177878 |
| _version_ |
1800916333660995584 |