Continuum modeling of the deceleration transient state in stochastic traffic flow

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

Grantor dc:publisher

University of Tennessee at Chattanooga

Author dc:creator

• Cemerlic, Alma

Contributors dc:contributor

• McDonald, Henry
• Pankajakshan, Ramesh; Swafford, Timothy; Dumas, Joe
• College of Engineering and Computer Science

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

Licence

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

Language dc:language

English, eng

Repository record dc:identifier

https://scholar.utc.edu/theses/432

OAI identifier oai:identifier

oai:scholar.utc.edu:theses-1571