Prediction system for decision-making to improve the road environment

Yu Mi Song; Sung Ah Kim

doi:10.1007/978-3-319-46771-9_40

Prediction system for decision-making to improve the road environment

Yu Mi Song
, Sung Ah Kim

Department of Architecture

Sungkyunkwan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The aim of this research was to find the relations among traffic volume, travel speed, and road connectivity in order to predict the traffic congestion. The result showed that when a road has higher connectivity, the travel speed goes lower. Therefore, it was assumed that the congestion on the target area should be affected by high connectivity. The visualization of this prediction would significantly affect the urban planning that is related with the stakeholders of different kind.

Original language	English
Title of host publication	Cooperative Design, Visualization, and Engineering - 13th International Conference, CDVE 2016, Proceedings
Editors	Yuhua Luo
Publisher	Springer Verlag
Pages	309-312
Number of pages	4
ISBN (Print)	9783319467702
DOIs	https://doi.org/10.1007/978-3-319-46771-9_40
State	Published - 2016
Event	13th International Conference on Cooperative Design, Visualization, and Engineering, CDVE 2016 - Sydney, Australia Duration: 24 Oct 2016 → 27 Oct 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9929 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	13th International Conference on Cooperative Design, Visualization, and Engineering, CDVE 2016
Country/Territory	Australia
City	Sydney
Period	24/10/16 → 27/10/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

Space syntax
Traffic congestion
Urban data
Urban information visualization

Access to Document

10.1007/978-3-319-46771-9_40

Cite this

Song, Y. M., & Kim, S. A. (2016). Prediction system for decision-making to improve the road environment. In Y. Luo (Ed.), Cooperative Design, Visualization, and Engineering - 13th International Conference, CDVE 2016, Proceedings (pp. 309-312). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9929 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46771-9_40

Song, Yu Mi ; Kim, Sung Ah. / Prediction system for decision-making to improve the road environment. Cooperative Design, Visualization, and Engineering - 13th International Conference, CDVE 2016, Proceedings. editor / Yuhua Luo. Springer Verlag, 2016. pp. 309-312 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Prediction system for decision-making to improve the road environment",

abstract = "The aim of this research was to find the relations among traffic volume, travel speed, and road connectivity in order to predict the traffic congestion. The result showed that when a road has higher connectivity, the travel speed goes lower. Therefore, it was assumed that the congestion on the target area should be affected by high connectivity. The visualization of this prediction would significantly affect the urban planning that is related with the stakeholders of different kind.",

keywords = "Space syntax, Traffic congestion, Urban data, Urban information visualization",

author = "Song, \{Yu Mi\} and Kim, \{Sung Ah\}",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 13th International Conference on Cooperative Design, Visualization, and Engineering, CDVE 2016 ; Conference date: 24-10-2016 Through 27-10-2016",

year = "2016",

doi = "10.1007/978-3-319-46771-9\_40",

language = "English",

isbn = "9783319467702",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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editor = "Yuhua Luo",

booktitle = "Cooperative Design, Visualization, and Engineering - 13th International Conference, CDVE 2016, Proceedings",

}

Song, YM & Kim, SA 2016, Prediction system for decision-making to improve the road environment. in Y Luo (ed.), Cooperative Design, Visualization, and Engineering - 13th International Conference, CDVE 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9929 LNCS, Springer Verlag, pp. 309-312, 13th International Conference on Cooperative Design, Visualization, and Engineering, CDVE 2016, Sydney, Australia, 24/10/16. https://doi.org/10.1007/978-3-319-46771-9_40

Prediction system for decision-making to improve the road environment. / Song, Yu Mi; Kim, Sung Ah.
Cooperative Design, Visualization, and Engineering - 13th International Conference, CDVE 2016, Proceedings. ed. / Yuhua Luo. Springer Verlag, 2016. p. 309-312 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9929 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Prediction system for decision-making to improve the road environment

AU - Song, Yu Mi

AU - Kim, Sung Ah

N1 - Publisher Copyright: © Springer International Publishing AG 2016.

PY - 2016

Y1 - 2016

N2 - The aim of this research was to find the relations among traffic volume, travel speed, and road connectivity in order to predict the traffic congestion. The result showed that when a road has higher connectivity, the travel speed goes lower. Therefore, it was assumed that the congestion on the target area should be affected by high connectivity. The visualization of this prediction would significantly affect the urban planning that is related with the stakeholders of different kind.

AB - The aim of this research was to find the relations among traffic volume, travel speed, and road connectivity in order to predict the traffic congestion. The result showed that when a road has higher connectivity, the travel speed goes lower. Therefore, it was assumed that the congestion on the target area should be affected by high connectivity. The visualization of this prediction would significantly affect the urban planning that is related with the stakeholders of different kind.

KW - Space syntax

KW - Traffic congestion

KW - Urban data

KW - Urban information visualization

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U2 - 10.1007/978-3-319-46771-9_40

DO - 10.1007/978-3-319-46771-9_40

M3 - Conference contribution

AN - SCOPUS:84994130005

SN - 9783319467702

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 309

EP - 312

BT - Cooperative Design, Visualization, and Engineering - 13th International Conference, CDVE 2016, Proceedings

A2 - Luo, Yuhua

PB - Springer Verlag

T2 - 13th International Conference on Cooperative Design, Visualization, and Engineering, CDVE 2016

Y2 - 24 October 2016 through 27 October 2016

ER -

Song YM, Kim SA. Prediction system for decision-making to improve the road environment. In Luo Y, editor, Cooperative Design, Visualization, and Engineering - 13th International Conference, CDVE 2016, Proceedings. Springer Verlag. 2016. p. 309-312. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-46771-9_40

Prediction system for decision-making to improve the road environment

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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