| Issue |
SHS Web Conf.
Volume 77, 2020
The 2nd ACM Chapter International Conference on Educational Technology, Language and Technical Communication (ETLTC2020)
|
|
|---|---|---|
| Article Number | 04002 | |
| Number of page(s) | 6 | |
| Section | Topics in Computer Science | |
| DOI | https://doi.org/10.1051/shsconf/20207704002 | |
| Published online | 08 May 2020 | |
Optimizing Deep-Neural-Network-Driven Autonomous Race Car Using Image Scaling
School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Japan
* e-mail: m5222108@u-aizu.ac.jp
** e-mail: okuyama@u-aizu.ac.jp
*** e-mail: m5222102@u-aizu.ac.jp
**** e-mail: s1260138@u-aizu.ac.jp
† e-mail: s1260211@u-aizu.ac.jp
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.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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