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Journal of Intelligent Transportation Systems
Technology, Planning, and Operations
Volume 18, 2014 - Issue 4: Dynamic Modeling for Intelligent Transportation System Applications
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Original Articles

A Novel Method to Predict Traffic Features Based on Rolling Self-Structured Traffic Patterns

Yu-Chiun ChiouDepartment of Transportation and Logistics Management, National Chiao Tung University, Taipei, Taiwan, Republic of ChinaCorrespondence[email protected]
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,
Lawrence W. LanDepartment of Transportation and Logistics Management, National Chiao Tung University, Taipei, Taiwan, Republic of ChinaView further author information
&
Chun-Ming TsengDepartment of Transportation and Logistics Management, National Chiao Tung University, Taipei, Taiwan, Republic of ChinaView further author information
Pages 352-366 | Published online: 29 Jul 2014

Citations (12)

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Read on this site (4)

Seiran Heshami & Lina Kattan. (2023) A stochastic microscopic based freeway traffic state and spatial-temporal pattern prediction in a connected vehicle environment. Journal of Intelligent Transportation Systems 0:0, pages 1-27.
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Jie Fang & Jing Jin. (2015) Intelligent Algorithms for Reducing Short-Term Traffic State Prediction Error in Active Traffic Management. Journal of Intelligent Transportation Systems 19:3, pages 304-315.
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Jiancheng Long, W.Y. Szeto, Qin Shi, Ziyou Gao & Hai-Jun Huang. (2015) A nonlinear equation system approach to the dynamic stochastic user equilibrium simultaneous route and departure time choice problem. Transportmetrica A: Transport Science 11:5, pages 388-419.
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W. Y. Szeto. (2014) Dynamic Modeling for Intelligent Transportation System Applications. Journal of Intelligent Transportation Systems 18:4, pages 323-326.
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Articles from other publishers (8)

Longjian Wang, Yonggang Wang & Longfei Wang. (2022) STABILITY ANALYSIS FOR URBAN TRAFFIC EVOLUTION PROCESS USING TEMPORAL TRAFFIC STATE PATTERNS. Transport 37:5, pages 310-317.
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Hima Elsa Shaji, Arun K. Tangirala & Lelitha Vanajakshi. (2020) Prediction Of Trends In Bus Travel Time Using Spatial Patterns. Transportation Research Procedia 48, pages 998-1007.
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Diala Jomaa & Siril Yella. (2019) Predicting Automatic Trigger Speed for Vehicle-Activated Signs. Journal of Intelligent Systems 29:1, pages 1079-1091.
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Shaokun Zhang, Zejian Kang, Zhemin Zhang, Congren Lin, Cheng Wang & Jonathan Li. (2019) A Hybrid Model for Forecasting Traffic Flow: Using Layerwise Structure and Markov Transition Matrix. IEEE Access 7, pages 26002-26012.
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Nicholas Polson & Vadim Sokolov. (2018) Bayesian Particle Tracking of Traffic Flows. IEEE Transactions on Intelligent Transportation Systems 19:2, pages 345-356.
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Nicholas G. Polson & Vadim O. Sokolov. (2017) Deep learning for short-term traffic flow prediction. Transportation Research Part C: Emerging Technologies 79, pages 1-17.
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Nicholas Polson & Vadim Sokolov. (2015) Bayesian analysis of traffic flow on interstate I-55: The LWR model. The Annals of Applied Statistics 9:4.
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Jiancheng Long, W.Y. Szeto, Hai-Jun Huang & Ziyou Gao. (2015) An intersection-movement-based stochastic dynamic user optimal route choice model for assessing network performance. Transportation Research Part B: Methodological 74, pages 182-217.
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