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| dc.contributor.author | Ahmed, Nadim | |
| dc.contributor.author | Salehin, Sultanus | |
| dc.contributor.author | Choudhury, Tashfique Hasnine | |
| dc.contributor.author | Rossi, Alfa | |
| dc.date.accessioned | 2020-12-25T05:34:34Z | |
| dc.date.available | 2020-12-25T05:34:34Z | |
| dc.date.issued | 2019-11-15 | |
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| dc.identifier.uri | http://hdl.handle.net/123456789/733 | |
| dc.description | Supervised by Dr. Golam Sarowar Associate Professor, Department of Electrical and Electronic Engineering, Islamic University of Technology (IUT), Boardbazar, Gazipur-1704. | en_US |
| dc.description.abstract | Our dissertation describes in-depth the algorithm intended to identify lane lines on streets and highways in different conditions. Lane detection enhances the protection of the independent system to some extent. The autonomous or self-sufficient vehicle is an independent device that senses conditions and determines accordingly without any human intervention. Our emphasis was on the use of a vehicle prototype to recognize lanes that could be used later on a standard vehicle. To capture real-time video, PiCamera is embedded with a RaspberryPi 3.0 Model B for processing purposes. RaspberryPi along with battery, motors are mounted in a prototype constructed using CNC machine with sheer perfection. The real-time video captured by Picamera is sufficient enough to evaluate the performance of the algorithms used. The algorithms that have been used are the concepts of OpenCV, Hough transformation, canny edge detection algorithm and elementary algebra to compute and draw the lines. Python 2.7 was used to write the code for the relevant algorithm. The accuracy level of the algorithm used is quite astonishing. Our research works significantly in the field of autonomous vehicles. The comprehensive approach shown here offers a fairly precise and efficient solution for tracking lines. This can make a big difference in the driving experience in every way possible if used properly. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Department of Electrical and Electronic Engineering, Islamic University of Technology,Board Bazar, Gazipur, Bangladesh | en_US |
| dc.title | Real-Time Lane Detection and Motion Planning for Autonomous Vehicle | en_US |
| dc.type | Thesis | en_US |
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