{"title":"人工智能在交通运输行业转型中的作用综述","authors":"Ruhul Amin Choudhury, Mandeep Singh, Rajeev Kumar, Renu Devi, Shubham Sharma, Jagpreet Singh, Abhinav Kumar, Mohamed Abbas","doi":"10.1007/s11831-024-10208-1","DOIUrl":null,"url":null,"abstract":"<div><p>With the rapid evolution of technologies like IoT (Internet of Things) and ML (Machine Learning), applications are becoming much smarter, thus giving more opportunity for the exploitation of various sectors. With such connectivity of devices giving rise to abundant amount of data thus boosting the deployment of Machine learning. Though Machine learning has found immense applicability in various sector, transportation is one such sectors that has attracted many researchers for transforming the paradigm of transportation into intelligence and enhancement. During the review, we considered the various layers of Machine learning in Transportation and reviewed them one by one. The application area of ML in transportation is reviewed thoroughly, discussing the recent advancements carried out in areas such as route optimization, logistics, accident detection, and many others. The purpose of the review is to present a self-contained critical review discussing every aspect of the deployment of the approach in Transportation. From the review, it is found that though ML is a strong aspect for the future revolution of transportation systems, there are some challenges, such as privacy concerns, that cannot be ignored and need good research to overcome these challenges.</p></div>","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"32 4","pages":"2347 - 2364"},"PeriodicalIF":12.1000,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Critical Review on the Role of Artificial Intelligence in Transforming the Transportation Sector\",\"authors\":\"Ruhul Amin Choudhury, Mandeep Singh, Rajeev Kumar, Renu Devi, Shubham Sharma, Jagpreet Singh, Abhinav Kumar, Mohamed Abbas\",\"doi\":\"10.1007/s11831-024-10208-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>With the rapid evolution of technologies like IoT (Internet of Things) and ML (Machine Learning), applications are becoming much smarter, thus giving more opportunity for the exploitation of various sectors. With such connectivity of devices giving rise to abundant amount of data thus boosting the deployment of Machine learning. Though Machine learning has found immense applicability in various sector, transportation is one such sectors that has attracted many researchers for transforming the paradigm of transportation into intelligence and enhancement. During the review, we considered the various layers of Machine learning in Transportation and reviewed them one by one. The application area of ML in transportation is reviewed thoroughly, discussing the recent advancements carried out in areas such as route optimization, logistics, accident detection, and many others. The purpose of the review is to present a self-contained critical review discussing every aspect of the deployment of the approach in Transportation. From the review, it is found that though ML is a strong aspect for the future revolution of transportation systems, there are some challenges, such as privacy concerns, that cannot be ignored and need good research to overcome these challenges.</p></div>\",\"PeriodicalId\":55473,\"journal\":{\"name\":\"Archives of Computational Methods in Engineering\",\"volume\":\"32 4\",\"pages\":\"2347 - 2364\"},\"PeriodicalIF\":12.1000,\"publicationDate\":\"2025-01-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Archives of Computational Methods in Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s11831-024-10208-1\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of Computational Methods in Engineering","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s11831-024-10208-1","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
A Critical Review on the Role of Artificial Intelligence in Transforming the Transportation Sector
With the rapid evolution of technologies like IoT (Internet of Things) and ML (Machine Learning), applications are becoming much smarter, thus giving more opportunity for the exploitation of various sectors. With such connectivity of devices giving rise to abundant amount of data thus boosting the deployment of Machine learning. Though Machine learning has found immense applicability in various sector, transportation is one such sectors that has attracted many researchers for transforming the paradigm of transportation into intelligence and enhancement. During the review, we considered the various layers of Machine learning in Transportation and reviewed them one by one. The application area of ML in transportation is reviewed thoroughly, discussing the recent advancements carried out in areas such as route optimization, logistics, accident detection, and many others. The purpose of the review is to present a self-contained critical review discussing every aspect of the deployment of the approach in Transportation. From the review, it is found that though ML is a strong aspect for the future revolution of transportation systems, there are some challenges, such as privacy concerns, that cannot be ignored and need good research to overcome these challenges.
期刊介绍:
Archives of Computational Methods in Engineering
Aim and Scope:
Archives of Computational Methods in Engineering serves as an active forum for disseminating research and advanced practices in computational engineering, particularly focusing on mechanics and related fields. The journal emphasizes extended state-of-the-art reviews in selected areas, a unique feature of its publication.
Review Format:
Reviews published in the journal offer:
A survey of current literature
Critical exposition of topics in their full complexity
By organizing the information in this manner, readers can quickly grasp the focus, coverage, and unique features of the Archives of Computational Methods in Engineering.