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2017 | OriginalPaper | Buchkapitel

Predicting Traffic Flow Based on Average Speed of Neighbouring Road Using Multiple Regression

verfasst von : Bagus Priambodo, Azlina Ahmad

Erschienen in: Advances in Visual Informatics

Verlag: Springer International Publishing

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Abstract

The prediction of traffic flow is a challenge. There are many factors that can affect traffic flow. One of the factors is an inter path relationship between neighbouring roads. For example, an individual incidents (such as accidents) may cause ripple effects (a cascading failure) which then spreads and creates a sustained traffic jam the neighbouring area. To know the relationship between road segments we propose multiple regression method to predict the traffic based on the nearby surrounding roads. The prediction factor is chosen from a high-relation road with the path to be searched. To know the relationship between roads we calculate their correlation among neighbouring roads. The results are then displayed on the map for further observation. From this study, we demonstrate that multiple regression method can be used to predict impact of speed of vehicles on neighbouring roads on traffic flows.

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Titel: Predicting Traffic Flow Based on Average Speed of Neighbouring Road Using Multiple Regression
verfasst von: Bagus Priambodo
Azlina Ahmad
Verlag: Springer International Publishing
Buch: Advances in Visual Informatics
Print ISBN: 978-3-319-70009-0

Electronic ISBN: 978-3-319-70010-6

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-70010-6_29

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