Guest Editorial Introduction to the Special Issue on Data Science for Intelligent Transportation Systems

被引：1

作者：

Ahmed, Syed Hassan ^{[1
]}

Piuri, Vincenzo ^{[2
]}

Yang, Laurence T. ^{[3
]}

Wei, Wei ^{[4
]}

机构：

[1] JMA Wireless, Liverpool, NY 13088 USA

[2] Univ Milan, Dept Comp Sci, I-20133 Milan, Italy

[3] St Francis Xavier Univ, Dept Comp Sci, Antigonish, NS B2G 2W5, Canada

[4] Xian Univ Technol, Sch Comp Sci & Engn, Xian 710048, Peoples R China

来源：

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | 2022年 / 23卷 / 09期

关键词：

Command centres - Core components - Dataflow - Engineering challenges - Intelligent transportation systems - Large amounts of data - Road traffic management - Roadside units - Science methods - Traffic management systems;

D O I：

10.1109/TITS.2022.3199824

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Intelligent transportation system (ITS) is a key enabler for future road traffic management systems. The core components of ITS include vehicles, roadside units, and traffic command centers. They generate a large amount of data flow that is made up of both mobility and service-related data. Therefore, some data science methods to handle the transportation data are very necessary for ITS. Although some attempts have been done to explore data science methods for ITS, there exist various scientific and engineering challenges including software and hardware development, computational complexity, data multi-source heterogeneity, and privacy protection. Consequently, to fully explore the benefits of ITS applications like connected and autonomous vehicles, traffic control and prediction, road safety, and accident prediction, advanced data science methodologies and applications are in great need.

引用

页码：16484 / 16491

页数：8

共 33 条

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