An Advanced Driver Assistance System Using Computer Vision and Deep-Learning

The key motivating factor for the underlying research work is to tackle the autonomous driving problem. The proposed research work attempts to design a model to effectively assist the drivers of vehicles. It uses computer vision algorithms to detect lanes, deep-learning to identify obstacles like ot...

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Bibliographic Details
Published in:2018 Second International Conference on Intelligent Computing and Control Systems (ICICCS) pp. 183 - 189
Main Authors: Trivedi, Yash, Negandhi, Prashil
Format: Conference Proceeding
Language:English
Published: IEEE 01.06.2018
Subjects:
Automation
Automobiles
Computational modeling
computer vision
Control systems
decision trees
deep learning
Image edge detection
machine learning
Roads
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Summary:The key motivating factor for the underlying research work is to tackle the autonomous driving problem. The proposed research work attempts to design a model to effectively assist the drivers of vehicles. It uses computer vision algorithms to detect lanes, deep-learning to identify obstacles like other vehicles and decision trees to take driving decisions. The driver assistance system has the ability to perform in both autonomous and assisting capabilities. The autonomous mode should be deployed on highways and the assisting mode on congested city roads. In the autonomous mode the system controls the car while in the assisting mode the system ensures that the driver practices safe driving by providing valuable prompts.
DOI:10.1109/ICCONS.2018.8662951