GPS-based citywide traffic congestion forecasting using CNN-RNN and C3D hybrid model-Reference-Cited by-同舟云学术

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GPS-based citywide traffic congestion forecasting using CNN-RNN and C3D hybrid model

Published:2020-04-08 Issue:2 Volume:17 Page:190-211
ISSN:2324-9935
Container-title:Transportmetrica A: Transport Science
language:en
Short-container-title:Transportmetrica A: Transport Science

Author:

Guo Jingqiu¹,Liu Yangzexi¹,Yang Qingyan (Ken)²,Wang Yibing³,Fang Shouen¹

Affiliation:

1. Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai, People’s Republic of China

2. AECOM, Southfield, MI, USA

3. College of Civil Engineering & Architecture, Zhejiang University, Hangzhou, People’s Republic of China

Publisher

Informa UK Limited

Subject

General Engineering,Transportation

Link

https://www.tandfonline.com/doi/pdf/10.1080/23249935.2020.1745927

Reference45 articles.

1. Spatiotemporal Patterns in Large-Scale Traffic Speed Prediction

2. A unified architecture for natural language processing

3. A statistical method for estimating predictable differences between daily traffic flow profiles

4. Detection of traffic congestion and incidents from GPS trace analysis

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