{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/44304"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/44304","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Link State Relationships under Incident Conditions: Using a CTM-based Dynamic Traffic Assignment Model","abstract":"Urban transportation networks are vulnerable to various incidents. In order to combat the negative effects due to incident-related congestion, various mitigation strategies have been proposed and implemented. The effectiveness of these congestion mitigation strategies for incident conditions largely depends on the accuracy of information regarding network conditions. Therefore, an efficient and accurate procedure to determine the link states, reflected by flows and density over time, is essential to incident management. This thesis presents a user equilibrium Dynamic Traffic Assignment (DTA) model that incorporates the Cell Transmission Model (CTM) to evaluate the temporal variation of flow and density over links, which reflect the link states of a transportation network. Encapsulation of the CTM equips the model with the capability of accepting inputs of incidents like duration and capacity reduction. Moreover, the proposed model is capable of handling multiple origin-destination (OD) pairs. By using this model, the temporal variation of flows over links can be readily evaluated. The visualized prediction of link density variations is used to investigate the link state relationships. By isolating the effects of an incident, the parallel routes of a specific OD pair display the relationship of substituting for each other, which is consistent with the general expectation regarding such parallel routes. A closer examination of the density variations confirms the existence of a substitution relationship between the unshared links of the two parallel routes. This information regarding link state relationship can be used as general guidance for incident management purposes.","abstract_html":"Urban transportation networks are vulnerable to various incidents. In order to combat the negative effects due to incident-related congestion, various mitigation strategies have been proposed and implemented. The effectiveness of these congestion mitigation strategies for incident conditions largely depends on the accuracy of information regarding network conditions. Therefore, an efficient and accurate procedure to determine the link states, reflected by flows and density over time, is essential to incident management. This thesis presents a user equilibrium Dynamic Traffic Assignment (DTA) model that incorporates the Cell Transmission Model (CTM) to evaluate the temporal variation of flow and density over links, which reflect the link states of a transportation network. Encapsulation of the CTM equips the model with the capability of accepting inputs of incidents like duration and capacity reduction. Moreover, the proposed model is capable of handling multiple origin-destination (OD) pairs. By using this model, the temporal variation of flows over links can be readily evaluated. The visualized prediction of link density variations is used to investigate the link state relationships. By isolating the effects of an incident, the parallel routes of a specific OD pair display the relationship of substituting for each other, which is consistent with the general expectation regarding such parallel routes. A closer examination of the density variations confirms the existence of a substitution relationship between the unshared links of the two parallel routes. This information regarding link state relationship can be used as general guidance for incident management purposes.","abstract_has_math":false,"creators":["Yin, Weihao"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Civil Engineering","degree_department":"Civil Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Murray-Tuite, Pamela Marie"],"committee_members":["Hancock, Kathleen L.","Triantis, Konstantinos P."],"year":2010,"date_issued":"2010-08-11","date_published":"2010-08-11","updated_at":"2026-07-22T22:20:37Z","subjects":["Transportation Engineering","Link State relationship","Dynamic Traffic Assignment","Cell Transmission Model"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-08182010-174509"],"render_values":[{"text":"etd-08182010-174509","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/44304","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Murray-Tuite, Pamela Marie"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Hancock, Kathleen L.","Triantis, Konstantinos P."]},{"key":"dc:contributor.department","label":"Department","values":["Civil Engineering"]},{"key":"dc:creator","label":"Author","values":["Yin, Weihao"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T21:43:05Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T21:43:05Z","2010-08-30"]},{"key":"dc:date.issued","label":"Date","values":["2010-08-11"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Transportation Engineering","Link State relationship","Dynamic Traffic Assignment","Cell Transmission Model"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-08182010-174509"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/44304"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Urban transportation networks are vulnerable to various incidents. In order to combat the negative effects due to incident-related congestion, various mitigation strategies have been proposed and implemented. The effectiveness of these congestion mitigation strategies for incident conditions largely depends on the accuracy of information regarding network conditions. Therefore, an efficient and accurate procedure to determine the link states, reflected by flows and density over time, is essential to incident management. This thesis presents a user equilibrium Dynamic Traffic Assignment (DTA) model that incorporates the Cell Transmission Model (CTM) to evaluate the temporal variation of flow and density over links, which reflect the link states of a transportation network. Encapsulation of the CTM equips the model with the capability of accepting inputs of incidents like duration and capacity reduction. Moreover, the proposed model is capable of handling multiple origin-destination (OD) pairs. By using this model, the temporal variation of flows over links can be readily evaluated. The visualized prediction of link density variations is used to investigate the link state relationships. By isolating the effects of an incident, the parallel routes of a specific OD pair display the relationship of substituting for each other, which is consistent with the general expectation regarding such parallel routes. A closer examination of the density variations confirms the existence of a substitution relationship between the unshared links of the two parallel routes. This information regarding link state relationship can be used as general guidance for incident management purposes."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:title","label":"Title","values":["Link State Relationships under Incident Conditions: Using a CTM-based Dynamic Traffic Assignment Model"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Murray-Tuite, Pamela Marie"],"dc:contributor.committeemember":["Hancock, Kathleen L.","Triantis, Konstantinos P."],"dc:contributor.department":["Civil Engineering"],"dc:creator":["Yin, Weihao"],"dc:date.accessioned":["2014-03-14T21:43:05Z"],"dc:date.available":["2014-03-14T21:43:05Z","2010-08-30"],"dc:date.issued":["2010-08-11"],"dc:description.abstract":["Urban transportation networks are vulnerable to various incidents. In order to combat the negative effects due to incident-related congestion, various mitigation strategies have been proposed and implemented. The effectiveness of these congestion mitigation strategies for incident conditions largely depends on the accuracy of information regarding network conditions. Therefore, an efficient and accurate procedure to determine the link states, reflected by flows and density over time, is essential to incident management. This thesis presents a user equilibrium Dynamic Traffic Assignment (DTA) model that incorporates the Cell Transmission Model (CTM) to evaluate the temporal variation of flow and density over links, which reflect the link states of a transportation network. Encapsulation of the CTM equips the model with the capability of accepting inputs of incidents like duration and capacity reduction. Moreover, the proposed model is capable of handling multiple origin-destination (OD) pairs. By using this model, the temporal variation of flows over links can be readily evaluated. The visualized prediction of link density variations is used to investigate the link state relationships. By isolating the effects of an incident, the parallel routes of a specific OD pair display the relationship of substituting for each other, which is consistent with the general expectation regarding such parallel routes. A closer examination of the density variations confirms the existence of a substitution relationship between the unshared links of the two parallel routes. 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