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Traffic Light Detection and Recognition for Self Driving Cars using Deep Learning: Survey

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Traffic Light Detection and Recognition for Self Driving Cars using Deep Learning: Survey


Aswathy Madhu | Sruthy S



Aswathy Madhu | Sruthy S "Traffic Light Detection and Recognition for Self Driving Cars using Deep Learning: Survey" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2, February 2020, pp.624-627, URL: https://www.ijtsrd.com/papers/ijtsrd30030.pdf

Self-driving cars has the potential to revolutionize urban mobility by providing sustainable, safe, and convenient and congestion free transportability. Autonomous driving vehicles have become a trend in the vehicle industry. Many driver assistance systems (DAS) have been presented to support these automatic cars. This vehicle autonomy as an application of AI has several challenges like infallibly recognizing traffic lights, signs, unclear lane markings, pedestrians, etc. These problems can be overcome by using the technological development in the fields of Deep Learning, Computer Vision due to availability of Graphical Processing Units (GPU) and cloud platform. By using deep learning, a deep neural network based model is proposed for reliable detection and recognition of traffic lights (TL).

Driver Assistance Systems (DAS), Graphical Processing Units (GPU), Traffic Lights (TL)


IJTSRD30030
Volume-4 | Issue-2, February 2020
624-627
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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