More Efficient Learning in Traffic Grids Viewed as Complex Adaptive Systems Using Agent Based Modeling

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Lane, M. (2017). More Efficient Learning in Traffic Grids Viewed as Complex Adaptive Systems Using Agent Based Modeling. Unc Charlotte Electronic Theses And Dissertations.
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Abstract

Equation based modeling (EBM) is the most common form of scientific modeling. However, the creation of an appropriate EBM for a large system is likely to be complicated and computationally expensive. In contrast, consider the possibilities if even a large system is treated as a complex adaptive system (CAS), applying the basic tenets of a CAS to a model using the concepts of agent based modeling (ABM). ABM requires only the definition of the model environment, the identification of key agents, and a minimum number of key behaviors of those agents. It was a contention of this study that a CAS/ABM model would be easier to design, implement, execute, and extend than an EBM model. It was also a contention that the results would still be predictive and useful. The ABM herein was based on the Uptown Charlotte, North Carolina, traffic grid using traffic volumes based on actual Charlotte traffic counts. It operated with autonomous traffic signals as an adaptive CAS.

Details
Author

Lane, Marion

Title

More Efficient Learning in Traffic Grids Viewed as Complex Adaptive Systems Using Agent Based Modeling

Physical Description

1 online resource (70 pages) : PDF

Date

2017

Degree Granting Institution

University of North Carolina at Charlotte

Abstract

Equation based modeling (EBM) is the most common form of scientific modeling. However, the creation of an appropriate EBM for a large system is likely to be complicated and computationally expensive. In contrast, consider the possibilities if even a large system is treated as a complex adaptive system (CAS), applying the basic tenets of a CAS to a model using the concepts of agent based modeling (ABM). ABM requires only the definition of the model environment, the identification of key agents, and a minimum number of key behaviors of those agents. It was a contention of this study that a CAS/ABM model would be easier to design, implement, execute, and extend than an EBM model. It was also a contention that the results would still be predictive and useful. The ABM herein was based on the Uptown Charlotte, North Carolina, traffic grid using traffic volumes based on actual Charlotte traffic counts. It operated with autonomous traffic signals as an adaptive CAS.

Genre

doctoral dissertations

Subjects--Topics

Information technology

Degree

Ph.D.

Keywords

Agent Based Modeling
Complex Adaptive Systems
Traffic Management

Subject Area

Information Technology

Advisor(s)

Hadzikadic, Mirsad

Committee Members

Ras, Zbigniew
Wang, Weichao
Hauser, Edd

Degree Note

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2017.

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Rights Holder Information

Copyright is held by the author unless otherwise indicated.

Identifier

Lane_uncc_0694D_11465

Permalink

http://hdl.handle.net/20.500.13093/etd:73