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

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