人工智能在交通运输行业转型中的作用综述

IF 12.1 2区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Ruhul Amin Choudhury, Mandeep Singh, Rajeev Kumar, Renu Devi, Shubham Sharma, Jagpreet Singh, Abhinav Kumar, Mohamed Abbas
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引用次数: 0

摘要

随着物联网(IoT)和机器学习(ML)等技术的快速发展,应用程序变得更加智能,从而为各个领域的开发提供了更多机会。设备的这种连接产生了大量的数据,从而促进了机器学习的部署。虽然机器学习在各个领域都有巨大的适用性,但交通运输是其中一个吸引了许多研究人员将交通运输范式转变为智能和增强的领域。在审查过程中,我们考虑了交通运输中机器学习的各个层面,并逐一进行了审查。本文全面回顾了机器学习在交通运输中的应用领域,讨论了在路线优化、物流、事故检测等领域取得的最新进展。审查的目的是提出一个独立的批判性审查,讨论该方法在运输中部署的各个方面。从回顾中可以发现,虽然ML是未来交通系统革命的一个强有力的方面,但也存在一些不可忽视的挑战,例如隐私问题,需要很好的研究来克服这些挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

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来源期刊
CiteScore
19.80
自引率
4.10%
发文量
153
审稿时长
>12 weeks
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.
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