Pankajakshan, Ramesh; Swafford, Timothy; Dumas, Joe
College of Engineering and Computer Science
University of Tennessee at Chattanooga
Place of Publication
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
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.
Driver assistance systems; Traffic flow -- Mathematical models; Stochastic processes
xii, 126 leaves
Cemerlic, Alma, "Continuum modeling of the deceleration transient state in stochastic traffic flow" (2015). Masters Theses and Doctoral Dissertations.