| Autor: |
Patrick Lau, Julian Halloy, Alan Ayala, Kwai Wong, Brendan Flood, Rocco Febbo |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
PEARC |
| DOI: |
10.1145/3311790.3396669 |
| Popis: |
The idea of a self-driving car is one which is actively studied and tested for use on the road. In addition, the machine learning tools required to create such a vehicle has become more and more available to the public as time goes on. With a number of different libraries and softwares available for free download to design and train neural networks and with affordable but powerful miniature computers on the market, one can explore the possibility of creating a self-driving vehicle. The goal of our project was to construct such a car on a small scale using parts and software that are accessible to anyone on an affordable budget ($250), and to test the effectiveness of DNN software neural networks on training such a car. This project serves as a simple testbed for experimenting different ideas in self driving vehicle. Core ideas of autonomous vehicles are explored with machine learning in mind. The paper details the challenges and experience of project and is the result of an REU project support by the NSF. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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