Applying Machine Learning and Statistical Approaches for Travel Time Estimation in Partial Network Coverage

Applying Machine Learning and Statistical Approaches for Travel Time Estimation in Partial Network Coverage

The objective of this study is to estimate the real time travel times on urban networks that are partially covered by moving sensors. The study proposes two machine learning approaches; the random forest (RF) model and the multi-layer feed forward neural network (MFFN) to estimate travel times on ur...

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Bibliographic Details
Main Authors: Fahad Alrukaibi, Rushdi Alsaleh, Tarek Sayed
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Sustainability
Subjects:
machine learning
random forest
neural network
ITS
travel time estimation
Online Access:https://www.mdpi.com/2071-1050/11/14/3822

Internet

https://www.mdpi.com/2071-1050/11/14/3822

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