標題: A Survey on Deep Learning-Based Vehicular Communication Applications
作者: Lin, Chia-Hung
Lin, Yu-Chien
Wu, Yen-Jung
Chung, Wei-Ho
Lee, Ta-Sung
交大名義發表
電信工程研究所
National Chiao Tung University
Institute of Communications Engineering
關鍵字: Vehicular communications;Deep learning;Intelligent transportation systems;Traffic flow forecasting;Trajectory prediction
公開日期: 1-Jan-1970
摘要: Besides the use of information transmission, vehicular communications also perform an essential role in intelligent transportation systems (ITS) for exchanging critical driving information among end users, vehicles, and infrastructures. Moreover, to enhance the understanding of the local environment, increasingly more data are collected by sensors, inducing an extensive use of deep learning (DL)-based algorithms in ITS. To further promote the development of DL-based algorithms in ITS, in this paper, we present a concise introduction of DL technologies. Then, we conduct an in-depth investigation on two popular DL-based applications used in ITS, traffic flow forecasting and trajectory prediction, focusing onwhenandhowthe authors employ different DL models and training schemes in these tasks. Finally, we raise two existing problems while employing DL-based algorithms in practical ITS and further discuss certain recent advances in DL-based research to tackle these challenges. To encourage more researchers to focus on the development of DL-based algorithms in ITS for a better world, we hope this paper can be treated as an informational material for prospective researchers, which contains the essential background knowledge of DL-based ITS applications; we also hope this paper will encourage experienced researchers to counter the open challenges and achieve a technical breakthrough to ITS.
URI: http://dx.doi.org/10.1007/s11265-020-01587-2
http://hdl.handle.net/11536/155430
ISSN: 1939-8018
DOI: 10.1007/s11265-020-01587-2
期刊: JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY
起始頁: 0
結束頁: 0
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