Optimizing Deep-Neural-Network-Driven Autonomous Race Car Using Image Scaling
In this work we propose scaling down the image resolution of an autonomous vehicle and measuring the performance difference using pre-determined metrics. We formulated a testing strategy and provided suitable testing metrics for RC driven autonomous vehicles. Our goal is to measure and prove that sc...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2020-01-01
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| Series: | SHS Web of Conferences |
| Online Access: | https://www.shs-conferences.org/articles/shsconf/pdf/2020/05/shsconf_etltc2020_04002.pdf |
| Summary: | In this work we propose scaling down the image resolution of an autonomous vehicle and measuring the performance difference using pre-determined metrics. We formulated a testing strategy and provided suitable testing metrics for RC driven autonomous vehicles. Our goal is to measure and prove that scaling down an image will result in faster response time and higher speeds. Our model shows an increase in response rate of the neural models, improving safety and results in the car having higher speeds. |
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| ISSN: | 2261-2424 |