{"title":"利用深度学习进行道路识别和车道检测","authors":"Md. Fazlul Karim Patwary, Moumita Chanda, Sadiya Rahman, Md. Tanvir Ahmed","doi":"10.59185/dg8xmp38","DOIUrl":null,"url":null,"abstract":"An autonomous vehicle needs to be familiar with its surroundings. The safety of thetransportation system is greatly enhanced by advanced driving assistance systems (ADASs). Road detectionis one of the steps that a driving car must do. Is it possible for a computer to recognize a road in a singlephotograph for this purpose? This question is addressed using the lane detecting techniques. Roads andlanes are tough for machine learning to differentiate because of training a machine to recognize a road.Over the past few decades, a number of lane identification technologies have been created and integratedinto various autonomous cars. It is still very difficult to create lane recognition technology that caneffectively identify a road lane in a range of road conditions. This research provides a composite approachfor road detection from image processing using convolutional neural networks by testing 150 photographsthat include a road, jungle, muddy road, and barriers. It will decide if an image contains a road or not. Inthis essay, we first establish whether a road exists. The second step is to find a lane on the finished road.The benefit of the proposed technology is that if there is a road, the automobile can continue to moveforward; otherwise, it will stop.","PeriodicalId":50178,"journal":{"name":"Journal of Information Technology","volume":null,"pages":null},"PeriodicalIF":5.8000,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Road Recognition and Lane Detection using Deep Learning\",\"authors\":\"Md. Fazlul Karim Patwary, Moumita Chanda, Sadiya Rahman, Md. Tanvir Ahmed\",\"doi\":\"10.59185/dg8xmp38\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An autonomous vehicle needs to be familiar with its surroundings. The safety of thetransportation system is greatly enhanced by advanced driving assistance systems (ADASs). Road detectionis one of the steps that a driving car must do. Is it possible for a computer to recognize a road in a singlephotograph for this purpose? This question is addressed using the lane detecting techniques. Roads andlanes are tough for machine learning to differentiate because of training a machine to recognize a road.Over the past few decades, a number of lane identification technologies have been created and integratedinto various autonomous cars. It is still very difficult to create lane recognition technology that caneffectively identify a road lane in a range of road conditions. This research provides a composite approachfor road detection from image processing using convolutional neural networks by testing 150 photographsthat include a road, jungle, muddy road, and barriers. It will decide if an image contains a road or not. Inthis essay, we first establish whether a road exists. The second step is to find a lane on the finished road.The benefit of the proposed technology is that if there is a road, the automobile can continue to moveforward; otherwise, it will stop.\",\"PeriodicalId\":50178,\"journal\":{\"name\":\"Journal of Information Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2023-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Information Technology\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.59185/dg8xmp38\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Information Technology","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.59185/dg8xmp38","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Road Recognition and Lane Detection using Deep Learning
An autonomous vehicle needs to be familiar with its surroundings. The safety of thetransportation system is greatly enhanced by advanced driving assistance systems (ADASs). Road detectionis one of the steps that a driving car must do. Is it possible for a computer to recognize a road in a singlephotograph for this purpose? This question is addressed using the lane detecting techniques. Roads andlanes are tough for machine learning to differentiate because of training a machine to recognize a road.Over the past few decades, a number of lane identification technologies have been created and integratedinto various autonomous cars. It is still very difficult to create lane recognition technology that caneffectively identify a road lane in a range of road conditions. This research provides a composite approachfor road detection from image processing using convolutional neural networks by testing 150 photographsthat include a road, jungle, muddy road, and barriers. It will decide if an image contains a road or not. Inthis essay, we first establish whether a road exists. The second step is to find a lane on the finished road.The benefit of the proposed technology is that if there is a road, the automobile can continue to moveforward; otherwise, it will stop.
期刊介绍:
The aim of the Journal of Information Technology (JIT) is to provide academically robust papers, research, critical reviews and opinions on the organisational, social and management issues associated with significant information-based technologies. It is designed to be read by academics, scholars, advanced students, reflective practitioners, and those seeking an update on current experience and future prospects in relation to contemporary information and communications technology themes.
JIT focuses on new research addressing technology and the management of IT, including strategy, change, infrastructure, human resources, sourcing, system development and implementation, communications, technology developments, technology futures, national policies and standards. It also publishes articles that advance our understanding and application of research approaches and methods.