{"id":{"repo_id":"utc","oai_identifier":"oai:scholar.utc.edu:theses-1571"},"canonical_url":"https://search.dev.ndltd.org/etd/utc/oai:scholar.utc.edu:theses-1571","repository":{"repo_id":"utc","name":"University of Tennessee - Chattanooga","base_url":"https://scholar.utc.edu/do/oai/"},"display":{"title":"Continuum modeling of the deceleration transient state in stochastic traffic flow","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","abstract_html":"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","abstract_has_math":false,"creators":["Cemerlic, Alma"],"institution":"University of Tennessee at Chattanooga","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["McDonald, Henry","Pankajakshan, Ramesh; Swafford, Timothy; Dumas, Joe","College of Engineering and Computer Science"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T05:46:28Z","subjects":["Driver assistance systems","Traffic flow -- Mathematical models","Stochastic processes"],"languages":["English","eng"],"rights":[],"rights_urls":["https://rightsstatements.org/page/InC/1.0/?language=en"],"identifier_entries":[]},"links":{"outbound_url":"https://scholar.utc.edu/theses/432","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["McDonald, Henry","Pankajakshan, Ramesh; Swafford, Timothy; Dumas, Joe","College of Engineering and Computer Science"]},{"key":"dc:creator","label":"Author","values":["Cemerlic, Alma"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-08-01T07:00:00Z"]},{"key":"dc:publisher","label":"Institution","values":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"]},{"key":"dc:relation","label":"Dc Relation","values":["Masters Theses and Doctoral Dissertations"]},{"key":"dc:type","label":"Dc Type","values":["Doctoral dissertations","Text"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Driver assistance systems","Traffic flow -- Mathematical models","Stochastic processes"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["https://rightsstatements.org/page/InC/1.0/?language=en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholar.utc.edu/theses/432"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Dept. of Computational Engineering","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."]},{"key":"dc:description.abstract","label":"Abstract","values":["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"]},{"key":"dc:title","label":"Title","values":["Continuum modeling of the deceleration transient state in stochastic traffic flow"]}]}],"canonical_facts":{"dc:contributor":["McDonald, Henry","Pankajakshan, Ramesh; Swafford, Timothy; Dumas, Joe","College of Engineering and Computer Science"],"dc:creator":["Cemerlic, Alma"],"dc:date":["2015-08-01T07:00:00Z"],"dc:description":["Dept. of Computational Engineering","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."],"dc:description.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"],"dc:identifier":["https://scholar.utc.edu/theses/432"],"dc:language":["English","eng"],"dc:publisher":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"],"dc:relation":["Masters Theses and Doctoral Dissertations"],"dc:rights":["https://rightsstatements.org/page/InC/1.0/?language=en"],"dc:subject":["Driver assistance systems","Traffic flow -- Mathematical models","Stochastic processes"],"dc:title":["Continuum modeling of the deceleration transient state in stochastic traffic flow"],"dc:type":["Doctoral dissertations","Text"]},"updated_at":"2026-07-24T05:46:28Z"}