End to End Autonomous Driving System using Out-layer Removal (Out-layer를 제거한 End to End 자율주행 시스템)

Seung- Hyuk Jung (정승혁); 윤동호; Hong Sung Hoon (홍성훈)

doi:10.20465/KIOTS.2023.9.1.065

End to End Autonomous Driving System using Out-layer Removal

Journal of Internet of Things and Convergence
Abbr : JKIOTS
2023, 9(1), pp.65-70
DOI : 10.20465/KIOTS.2023.9.1.065
Publisher : The Korea Internet of Things Society
Research Area : Engineering > Computer Science > Internet Information Processing
Received : December 21, 2022
Accepted : January 23, 2023
Published : February 28, 2023

Seung- Hyuk Jung ¹, 윤동호 ², Hong Sung Hoon ¹

¹전남대학교
²한국생산기술연구원

Accredited

ABSTRACT

In this paper, we propose an autonomous driving system using an end-to-end model to improve lane departure and misrecognition of traffic lights in a vision sensor-based system. End-to-end learning can be extended to a variety of environmental conditions. Driving data is collected using a model car based on a vision sensor. Using the collected data, it is composed of existing data and data with outlayers removed. A class was formed with camera image data as input data and speed and steering data as output data, and data learning was performed using an end-to-end model. The reliability of the trained model was verified. Apply the learned end-to-end model to the model car to predict the steering angle with image data. As a result of the learning of the model car, it can be seen that the model with the outlayer removed is improved than the existing model.

KEYWORDS

Autonomous Vehicle, Computer Vision, Deep Learning, Out Layer Removal, Autonomous Driving

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* References for papers published after 2023 are currently being built.

[journal] Y. LeCun / 2015 / Deep learning / Nature 521(7553) : 436~444

[journal] A. Krizhevsky / 2017 / ImageNet classification with deep convolutional neural networks / Communications of the ACM 60(6) : 84~90

[web] / http://www.image-net.org/challenges/LSVRC / http://www.image-net.org/challenges/LSVRC

[journal] O. Russakovsky / 2015 / ImageNet Large Scale Visual Recognition Challenge / International Journal of Computer Vision 115(3) : 211~252

[journal] Rashmi / 2013 / Algorithm and Technique on Various Edge Detection : A Survey / Signal & Image Processing An International Journal 4(3) : 65~75

[journal] P. Mukhopadhyay / 2015 / A survey of Hough Transform / Pattern Recognition 48(3) : 993~1010

[web] / https://blog.naver.com/autoa2z/222069303400 / https://blog.naver.com/autoa2z/222069303400

[confproc] C. Chen / 2015 / DeepDriving : Learning Affordance for Direct Perception in Autonomous Driving / 2015 IEEE International Conference on Computer Vision (ICCV) / IEEE

[confproc] Pomerleau, D. A / 1988 / Alvinn : An autonomous land vehicle in a neural network / Advances in neural information processing systems 1

[confproc] Y. LeCun / 2015 / Off-road obstacle avoidance through end-to-end learning / Proceedings of the 18th International Conference on Neural Information Processing Systems (NIPS'05) : 739~746

[confproc] H. Xu / 2017 / End-to-End Learning of Driving Models from Large-Scale Video Datasets / 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) / IEEE

[journal] S. Baluja / 1996 / Evolution of an artificial neural network based autonomous land vehicle controller / IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) / Institute of Electrical and Electronics Engineers (IEEE) 26(3) : 450~463

[confproc] J. Koutník / 2013 / Evolving large-scale neural networks for vision-based reinforcement learning / Proceedings of the 15th annual conference on Genetic and evolutionary computation / ACM

[journal] A. E. Sallab / 2017 / Deep Reinforcement Learning framework for Autonomous Driving / Electronic Imaging 29(19) : 70~76

[other] M. Bojarski / 2016 / End to End Learning for Self-Driving Cars / arXiv

[confproc] A. Kendall / 2019 / Learning to Drive in a Day / 2019International Conference on Robotics and Automation (ICRA) / IEEE

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Journal of Internet of Things and Convergence 2023 KCI Impact Factor : 0.89

End to End Autonomous Driving System using Out-layer Removal

ABSTRACT

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Citation status

* References for papers published after 2023 are currently being built.

Journal of Internet of Things and Convergence 2023 KCI Impact Factor : 0.89

End to End Autonomous Driving System using Out-layer Removal

ABSTRACT

KEYWORDS

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* References for papers published after 2023 are currently being built.