Committee Chair

McDonald, Henry

Committee Member

Pankajakshan, Ramesh; Swafford, Timothy; Dumas, Joe

Department

Dept. of Computational Engineering

College

College of Engineering and Computer Science

Publisher

University of Tennessee at Chattanooga

Place of Publication

Chattanooga (Tenn.)

Abstract

Due to individual driver behavior, a traffic system is subject to many stochastic factors. Deterministic partial differential equations and their extensions, traditionally used in traffic flow modeling, may not be sufficient in applications such as real-time estimation and prediction of traffic flow conditions. In previous studies, the issue of physical relevance has received little attention in efforts to introduce a stochastic component into deterministic equilibrium-based traffic models. In this work, the stochastic component is derived directly from realistic driver behavior implemented as a fully discrete fine-grained agent-based model and combined into the deterministic Aw-Rascle system of equations via ensemble averaging. The same approach can be applied to any second-order traffic model of a similar form. Solutions for the stopping and deceleration cases are obtained using the second-order Lax-Wendroff scheme and compared to the results obtained from the agent-based simulation. iv

Degree

Ph. D.; A dissertation submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Doctor of Philosophy.

Date

8-2015

Subject

Driver assistance systems; Traffic flow -- Mathematical models; Stochastic processes

Keyword

Aw-Rascle traffic model; Agent-based traffic model; Ensemble average; Stochastic traffic model

Document Type

Doctoral dissertations

DCMI Type

Text

Extent

xii, 126 leaves

Language

English

Rights

https://rightsstatements.org/page/InC/1.0/?language=en

License

http://creativecommons.org/licenses/by-sa/3.0/

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