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A Complex Network Method for Traffic...

ProQuest Information and Learning Co.

A Complex Network Method for Traffic Modeling and Control.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	A Complex Network Method for Traffic Modeling and Control./
Author:	Yeung, Fiona Chehong.
Description:	1 online resource (45 pages)
Notes:	Source: Masters Abstracts International, Volume: 57-02.
Contained By:	Masters Abstracts International57-02(E).
Subject:	Statistics. -
Online resource:	click for full text (PQDT)
ISBN:	9780355460933

A Complex Network Method for Traffic Modeling and Control.
Yeung, Fiona Chehong.

A Complex Network Method for Traffic Modeling and Control. - 1 online resource (45 pages)

Source: Masters Abstracts International, Volume: 57-02.

Thesis (M.S.)--University of California, Los Angeles, 2017.

Includes bibliographical references

Transportation systems are the economic foundation of any regional development. Our reliance on transportation to move goods and resources and to ensure access to labor to increase productivity, all have tremendous impact on revenue generation and growth. Traffic congestion is an inevitable byproduct of economic growth; the costs of traffic is not just time wasted, but also include the financial loss and environmental impacts of fuel being wasted. As an effort to understand congestion formation, this project investigates modeling traffic as a network and uses a percolation model to identify a normal traffic pattern as exhibited by the inhabitants of the region. Using real street maps from the OpenStreetMap project, morning, noon, and evening rush-hour traffic zones in Westwood Village were created to simulate the travel behavior of the inhabitants. The street bottlenecks identified for a 24-hr period were then compared to those formed from a uniform traffic flow. The results from this study may provide the foundation for a reasonable starting configuration for a self-organizing traffic light network that can dynamically adapt to unexpected demand in real-time.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355460933Subjects--Topical Terms:

556824
Statistics.
Index Terms--Genre/Form:

554714
Electronic books.

A Complex Network Method for Traffic Modeling and Control.
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020 $a 9780355460933
035 $a (MiAaPQ)AAI10600274
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035 $a AAI10600274
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100 1 $a Yeung, Fiona Chehong. $3 1195503
245 1 2 $a A Complex Network Method for Traffic Modeling and Control.
264 0 $c 2017
300 $a 1 online resource (45 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 57-02.
500 $a Adviser: Mark Handcock.
502 $a Thesis (M.S.)--University of California, Los Angeles, 2017.
504 $a Includes bibliographical references
520 $a Transportation systems are the economic foundation of any regional development. Our reliance on transportation to move goods and resources and to ensure access to labor to increase productivity, all have tremendous impact on revenue generation and growth. Traffic congestion is an inevitable byproduct of economic growth; the costs of traffic is not just time wasted, but also include the financial loss and environmental impacts of fuel being wasted. As an effort to understand congestion formation, this project investigates modeling traffic as a network and uses a percolation model to identify a normal traffic pattern as exhibited by the inhabitants of the region. Using real street maps from the OpenStreetMap project, morning, noon, and evening rush-hour traffic zones in Westwood Village were created to simulate the travel behavior of the inhabitants. The street bottlenecks identified for a 24-hr period were then compared to those formed from a uniform traffic flow. The results from this study may provide the foundation for a reasonable starting configuration for a self-organizing traffic light network that can dynamically adapt to unexpected demand in real-time.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Statistics. $3 556824
655 7 $a Electronic books. $2 local $3 554714
690 $a 0463
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of California, Los Angeles. $b Statistics. $3 1186550
773 0 $t Masters Abstracts International $g 57-02(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10600274 $z click for full text (PQDT)

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