Bus Dynamic Travel Time Prediction: Using a Deep Feature Extraction Framework Based on RNN and DNN

Bus Dynamic Travel Time Prediction: Using a Deep Feature Extraction Framework Based on RNN and DNN

Travel time data is an important factor for evaluating the performance of a public transport system. In terms of time and space within the nature of uncertainty, bus travel time is dynamic and flexible. Since the change of traffic status is periodic, contagious or even sudden, the changing mechanism...

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Bibliographic Details
Main Authors: Yuan Yuan, Chunfu Shao, Zhichao Cao, Zhaocheng He, Changsheng Zhu, Yimin Wang, Vlon Jang
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Electronics
Subjects:
dynamic bus travel time prediction
wide and deep
data fusion
attention
recurrent neural network
deep neural networks
Online Access:https://www.mdpi.com/2079-9292/9/11/1876

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