Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction

Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction

This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dim...

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Bibliographic Details
Main Authors: Xiaolei Ma, Zhuang Dai, Zhengbing He, Jihui Ma, Yong Wang, Yunpeng Wang
Format: Article
Language:English
Published: MDPI AG 2017-04-01
Series:Sensors
Subjects:
transportation network
traffic speed prediction
spatiotemporal feature
deep learning
convolutional neural network
Online Access:http://www.mdpi.com/1424-8220/17/4/818

Internet

http://www.mdpi.com/1424-8220/17/4/818

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