Simulation of Self Driving Car Using Deep Learning

被引：5

作者：

Lade, Sangita ^{[1
]}

Shrivastav, Parth ^{[1
]}

Waghmare, Saurabh ^{[1
]}

Hon, Sudarshan ^{[1
]}

Waghmode, Sushil ^{[1
]}

Teli, Shubham ^{[1
]}

机构：

[1] Vishwakarma Inst Technol, Dept Comp Engn, Pune, Maharashtra, India

来源：

2021 INTERNATIONAL CONFERENCE ON EMERGING SMART COMPUTING AND INFORMATICS (ESCI) | 2021年

关键词：

simulation; Nvidia-model; self-driving; image augmentation; CNN;

D O I：

10.1109/ESCI50559.2021.9396941

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

According to the WHO, around 1.35 million people die every year in road traffic crashes. Year by year there are advancements in technology which has paved a way for the inclusion of artificial intelligence even into automobiles. In this paper, we have provided an extensive study on the implementation of self-driving cars based on deep learning. For ease and safety, we will be simulating the car in the simulator provided by Udacity. The data for training the model is recorded in the simulator and imported into the project for training the model. Finally, we have implemented and compared various existing deep learning models and showcased the results in the section IV. We have obtained accuracy of 96.83% for model A and 76.67% for model B.

引用

页码：175 / 180

页数：6

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