Predicting traffic flow based on average speed of neighbouring road using multiple regression

Bagus Priambodo, Azlina Ahmad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationAdvances in Visual Informatics - 5th International Visual Informatics Conference, IVIC 2017, Proceedings
PublisherSpringer Verlag
Pages309-318
Number of pages10
Volume10645 LNCS
ISBN (Print)9783319700090
DOIs
Publication statusPublished - 1 Jan 2017
Event5th International Visual Informatics Conference, IVIC 2017 - Bangi, Malaysia
Duration: 28 Nov 201730 Nov 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10645 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Visual Informatics Conference, IVIC 2017
CountryMalaysia
CityBangi
Period28/11/1730/11/17

Fingerprint

Multiple Regression
Traffic Flow
Cascading Failure
Predict
Traffic Jam
Accidents
Path
Prediction
Ripple
Traffic
Calculate
Demonstrate
Relationships

Keywords

  • Multiple regressions
  • Traffic flow prediction
  • Traffic flow propagation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Priambodo, B., & Ahmad, A. (2017). Predicting traffic flow based on average speed of neighbouring road using multiple regression. In Advances in Visual Informatics - 5th International Visual Informatics Conference, IVIC 2017, Proceedings (Vol. 10645 LNCS, pp. 309-318). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10645 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-70010-6_29

Predicting traffic flow based on average speed of neighbouring road using multiple regression. / Priambodo, Bagus; Ahmad, Azlina.

Advances in Visual Informatics - 5th International Visual Informatics Conference, IVIC 2017, Proceedings. Vol. 10645 LNCS Springer Verlag, 2017. p. 309-318 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10645 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Priambodo, B & Ahmad, A 2017, Predicting traffic flow based on average speed of neighbouring road using multiple regression. in Advances in Visual Informatics - 5th International Visual Informatics Conference, IVIC 2017, Proceedings. vol. 10645 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10645 LNCS, Springer Verlag, pp. 309-318, 5th International Visual Informatics Conference, IVIC 2017, Bangi, Malaysia, 28/11/17. https://doi.org/10.1007/978-3-319-70010-6_29
Priambodo B, Ahmad A. Predicting traffic flow based on average speed of neighbouring road using multiple regression. In Advances in Visual Informatics - 5th International Visual Informatics Conference, IVIC 2017, Proceedings. Vol. 10645 LNCS. Springer Verlag. 2017. p. 309-318. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-70010-6_29
Priambodo, Bagus ; Ahmad, Azlina. / Predicting traffic flow based on average speed of neighbouring road using multiple regression. Advances in Visual Informatics - 5th International Visual Informatics Conference, IVIC 2017, Proceedings. Vol. 10645 LNCS Springer Verlag, 2017. pp. 309-318 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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