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...

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Bibliographic Details
Published in:SHS web of conferences 2020, Vol.77, p.4002
Main Authors: Mahmoud, Yaqub, Okuyama, Yuichi, Fukuchi, Tomohide, Kosuke, Tanaka, Ando, Iori
Format: Article
Language:English
Subjects:
Algorithms
Automobiles
Autonomous vehicles
Cameras
Deep learning
Neural networks
Response rates
Sensors
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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.
ISSN:2261-2424
2416-5182
2261-2424
DOI:10.1051/shsconf/20207704002