文章基本信息

标题：Robust and real-time multi-lane and single lane detection in Indian highway scenarios
本地全文：下载
作者：A. Sai Hanuman ; G. Prasanna Kumar
期刊名称：E3S Web of Conferences
印刷版ISSN：2267-1242
电子版ISSN：2267-1242
出版年度：2021
卷号：309
页码：1-9
DOI：10.1051/e3sconf/202130901016
语种：English
出版社：EDP Sciences
摘要：In the Advanced Driver Assistance System (ADAS), lane detection plays a vital role to avoid road accidents of an Autonomous vehicle. Also, autonomous vehicles should be able to navigate by themselves, in-order to do, it needs to understand its surrounding conditions like a human. So that vehicle can determine its path in streets and highways it can maintain lane manoeuvre. Also, It has become the most fundamental aspect to consider in current ADAS research. One of the major hurdles in self-driving vehicle research is identifying the curved lanes, multiple lanes with challenging light, and weather conditions, especially in Indian highway scenarios. As it is a vision-based lane detection approach we are using OpenCV library which consists of multiple algorithms like the optimization of canny edge detection to find out the edges, features of the lane and Hough Transform for lane line generation and apply on the particular region of interest.