Traffic Flow Prediction With Big Data: A Deep Learning Approach
Lv, Yisheng1; Duan, Yanjie1; Kang, Wenwen1; Li, Zhengxi2; Wang, Fei-Yue1
Source PublicationIEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
2015-04-01
Volume16Issue:2Pages:865-873
SubtypeArticle
AbstractAccurate and timely traffic flow information is important for the successful deployment of intelligent transportation systems. Over the last few years, traffic data have been exploding, and we have truly entered the era of big data for transportation. Existing traffic flow prediction methods mainly use shallow traffic prediction models and are still unsatisfying for many real-world applications. This situation inspires us to rethink the traffic flow prediction problem based on deep architecture models with big traffic data. In this paper, a novel deep-learning-based traffic flow prediction method is proposed, which considers the spatial and temporal correlations inherently. A stacked autoencoder model is used to learn generic traffic flow features, and it is trained in a greedy layerwise fashion. To the best of our knowledge, this is the first time that a deep architecture model is applied using autoencoders as building blocks to represent traffic flow features for prediction. Moreover, experiments demonstrate that the proposed method for traffic flow prediction has superior performance.
KeywordDeep Learning Stacked Autoencoders (Saes) Traffic Flow Prediction
WOS HeadingsScience & Technology ; Technology
WOS KeywordNEURAL-NETWORK APPROACH ; MODELS ; MULTIVARIATE ; VOLUME ; REGRESSION ; ALGORITHM
Indexed BySCI
Language英语
WOS Research AreaEngineering ; Transportation
WOS SubjectEngineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS IDWOS:000352282500029
Citation statistics
Cited Times:563[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8129
Collection复杂系统管理与控制国家重点实验室_先进控制与自动化
Corresponding AuthorLv, Yisheng
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.North China Univ Technol, Beijing 100144, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Lv, Yisheng,Duan, Yanjie,Kang, Wenwen,et al. Traffic Flow Prediction With Big Data: A Deep Learning Approach[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2015,16(2):865-873.
APA Lv, Yisheng,Duan, Yanjie,Kang, Wenwen,Li, Zhengxi,&Wang, Fei-Yue.(2015).Traffic Flow Prediction With Big Data: A Deep Learning Approach.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,16(2),865-873.
MLA Lv, Yisheng,et al."Traffic Flow Prediction With Big Data: A Deep Learning Approach".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 16.2(2015):865-873.
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