Award Date

8-1-2016

Degree Type

Thesis

Degree Name

Master of Science in Electrical Engineering (MSEE)

Department

Electrical and Computer Engineering

First Committee Member

Pushkin Kachroo

Second Committee Member

Yingtao Jiang

Third Committee Member

Ke-Xun Sun

Fourth Committee Member

Amei Amei

Number of Pages

76

Abstract

This thesis presents a novel methodology to divide a traffic region into subregions such that in each subregion a Macroscopic Fundamental Diagram (MFD) can be used to determine the state of that subregion. The region division is based on the theory of complex networks. We exploit the inherent network characteristics through PageRank centrality algorithm to identify the most significant nodes in the traffic network. We use these significant nodes as the seeds for a Voronoi diagram based partitioning mechanism of the network. A network wide hierarchical control framework is then presented which controls these sub regions individually and the network as a whole. At the subregion level a feedback controller is designed based on MFD concept. At the network level we develop a dynamic toll pricing algorithm to control the inflows into the network. This dynamic toll pricing is coupled with the subregion controller and thus forming a network wide hierarchical control. We use optimal control theory to design the dynamic toll pricing. A cost function is designed and then Hamilton-Jacobi-Bellman equation is used to derive an optimal control law that uses real-time information. The objective of the dynamic toll algorithm is to strike a balance between the toll price and optimal traffic conditions in each of the subregions. A case study is performed for the Manhattan area in New York city and results are provided through simulations.

Keywords

Complex Networks; Hamilton-Jacobi-Bellman equation; Macroscopic Fundamental Diagram; Optimal Control for Congestion Pricing; PageRank Centrality algorithm; Voronoi Diagram

Disciplines

Electrical and Computer Engineering

Language

English


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