Road surface friction prediction using long short-term memory neural network based on historical data-Reference-Cited by-同舟云学术

Road surface friction prediction using long short-term memory neural network based on historical data

Published:2020-07-08 Issue:1 Volume:26 Page:34-45
ISSN:1547-2450
Container-title:Journal of Intelligent Transportation Systems
language:en
Short-container-title:Journal of Intelligent Transportation Systems

Author:

Pu Ziyuan¹^ORCID,Liu Chenglong²^ORCID,Shi Xianming³^ORCID,Cui Zhiyong¹,Wang Yinhai¹

Affiliation:

1. Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, USA

2. Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai, China

3. Department of Civil and Environmental Engineering, Washington State University, Pullman, Washington, USA

Funder

Exploring Weather-related Connected Vehicle Applications for Improved Winter Travel in Pacific Northwest

CSET

1905

Publisher

Informa UK Limited

Subject

Applied Mathematics,Computer Science Applications,Aerospace Engineering,Automotive Engineering,Information Systems,Software,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15472450.2020.1780922

Reference54 articles.

1. A two-stage-training support vector machine approach to predicting unintentional vehicle lane departure

2. Learning long-term dependencies with gradient descent is difficult

3. Studying the effect of weather conditions on daily crash counts using a discrete time-series model

4. Long short-term memory model for traffic congestion prediction with online open data

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