How Generative Adversarial Networks Promote the Development of Intelligent Transportation Systems: A Survey

doi:10.1109/JAS.2023.123744

CORC > 自动化研究所 > 中国科学院自动化研究所 > 学术期刊 > IEEE/CAA Journal of Automatica Sinica

	How Generative Adversarial Networks Promote the Development of Intelligent Transportation Systems: A Survey
	Hongyi Lin; Yang Liu; Shen Li; Xiaobo Qu
刊名	IEEE/CAA Journal of Automatica Sinica
	2023
卷号	10 期号:9 页码:1781-1796
关键词	Autonomous driving generative adversarial network (GAN) intelligent transportation system (ITS) traffic anomaly inspection traffic flow
ISSN号	2329-9266
DOI	10.1109/JAS.2023.123744
英文摘要	In current years, the improvement of deep learning has brought about tremendous changes: As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) have been widely employed in various fields including transportation. This paper reviews the development of GANs and their applications in the transportation domain. Specifically, many adopted GAN variants for autonomous driving are classified and demonstrated according to data generation, video trajectory prediction, and security of detection. To introduce GANs to traffic research, this review summarizes the related techniques for spatio-temporal, sparse data completion, and time-series data evaluation. GAN-based traffic anomaly inspections such as infrastructure detection and status monitoring are also assessed. Moreover, to promote further development of GANs in intelligent transportation systems (ITSs), challenges and noteworthy research directions on this topic are provided. In general, this survey summarizes 130 GAN-related references and provides comprehensive knowledge for scholars who desire to adopt GANs in their scientific works, especially transportation-related tasks.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/52368]
专题	自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Hongyi Lin,Yang Liu,Shen Li,et al. How Generative Adversarial Networks Promote the Development of Intelligent Transportation Systems: A Survey[J]. IEEE/CAA Journal of Automatica Sinica,2023,10(9):1781-1796.
APA	Hongyi Lin,Yang Liu,Shen Li,&Xiaobo Qu.(2023).How Generative Adversarial Networks Promote the Development of Intelligent Transportation Systems: A Survey.IEEE/CAA Journal of Automatica Sinica,10(9),1781-1796.
MLA	Hongyi Lin,et al."How Generative Adversarial Networks Promote the Development of Intelligent Transportation Systems: A Survey".IEEE/CAA Journal of Automatica Sinica 10.9(2023):1781-1796.