An advanced driver assistance system using computer vision and deep-learning

被引：0

作者：

Trivedi, Yash ^{[1
]}

Negandhi, Prashil ^{[1
]}

机构：

[1] DJ Sanghvi Coll Engn, Dept Comp Engn, Mumbai, Maharashtra, India

来源：

PROCEEDINGS OF THE 2018 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICICCS) | 2018年

关键词：

computer vision; machine learning; deep learning; decision trees;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：183 / 189

页数：7