
Description
This thesis aims to improve neural control policies for self-driving cars. State-of-the-art navigation software for self-driving cars is based on deep neural networks, where the network is trained on a dataset of past driving experience in various situations. With previous methods, the car can only make decisions based on short-term memory.
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Contributors
- Martin, Sarah (Author)
- Ben Amor, Hani (Thesis director)
- Fainekos, Georgios (Committee member)
- Barrett, The Honors College (Contributor)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2018-05
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