More Efficient Learning in Traffic Grids Viewed as Complex Adaptive Systems Using Agent Based Modeling
1 online resource (70 pages) : PDF
University of North Carolina at Charlotte
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.
AGENT BASED MODELINGCOMPLEX ADAPTIVE SYSTEMSTRAFFIC MANAGEMENT
Ras, ZbigniewWang, WeichaoHauser, Edd
Thesis (Ph.D.)--University of North Carolina at Charlotte, 2017.
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