{"id":{"repo_id":"texas","oai_identifier":"oai:repositories.lib.utexas.edu:2152/68738"},"canonical_url":"https://search.dev.ndltd.org/etd/texas/oai:repositories.lib.utexas.edu:2152/68738","repository":{"repo_id":"texas","name":"University of Texas","base_url":"https://repositories.lib.utexas.edu/server/oai/request"},"display":{"title":"Transit signal priority strategies : impacts and effects of various factors","abstract":"A Transit Signal Priority (TSP) system’s fundamental job is to give priority to transit vehicles enabling faster passage through signalized intersections. Through a system that responds to transit vehicles approaching an intersection, green phase extension or red truncation is granted to minimize transit travel time. With emerging technologies TSP has the potential of doing so without disturbing general traffic flows. In this dissertation, an evaluation of the overall state of practice for TSP is conducted to upgrade the quality of TSP. Certain parameters were found to be significant in TSP performance, like: transit occupancies, transit arrival times, traffic volume, network capacity, system quality and green time. These multiple parameters affecting TSP performance from various studies are gathered and tested in three different cases: 1) Isolated intersection, 2) Main corridor with cross-streets and 3) Case study: Austin downtown network. This study focused on developing different TSP response scenarios to test what is the best way to handle bus requests. These scenarios represent the three TSP system types: passive, active and adaptive. By creating multiple scenarios, the goal is to develop technology that will minimize bus delays while also minimizing effects on general traffic delays.","abstract_html":"A Transit Signal Priority (TSP) system’s fundamental job is to give priority to transit vehicles enabling faster passage through signalized intersections. Through a system that responds to transit vehicles approaching an intersection, green phase extension or red truncation is granted to minimize transit travel time. With emerging technologies TSP has the potential of doing so without disturbing general traffic flows. In this dissertation, an evaluation of the overall state of practice for TSP is conducted to upgrade the quality of TSP. Certain parameters were found to be significant in TSP performance, like: transit occupancies, transit arrival times, traffic volume, network capacity, system quality and green time. These multiple parameters affecting TSP performance from various studies are gathered and tested in three different cases: 1) Isolated intersection, 2) Main corridor with cross-streets and 3) Case study: Austin downtown network. This study focused on developing different TSP response scenarios to test what is the best way to handle bus requests. These scenarios represent the three TSP system types: passive, active and adaptive. By creating multiple scenarios, the goal is to develop technology that will minimize bus delays while also minimizing effects on general traffic delays.","abstract_has_math":false,"creators":["Alrashidan, Ahmad"],"institution":"The University of Texas at Austin","degree_name":"Doctor of Philosophy","degree_level":"Doctoral","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Machemehl, Randy B."],"committee_chairs":[],"committee_members":["Claudel, Christian","Harvey, Kristin","Hersh, Matthew","Leite, Fernanda","Zhang, Zhanmin"],"year":2018,"date_issued":"2018-05","date_published":"2018-05","updated_at":"2026-07-24T05:01:06Z","subjects":["TSP","Transit signal priority systems","Bus reliability"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["doi:10.15781/T2416TJ3G"],"render_values":[{"text":"doi:10.15781/T2416TJ3G","href":"https://doi.org/10.15781/T2416TJ3G","code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2152/68738","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Machemehl, Randy B."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Claudel, Christian","Harvey, Kristin","Hersh, Matthew","Leite, Fernanda","Zhang, Zhanmin"]},{"key":"dc:creator","label":"Author","values":["Alrashidan, Ahmad"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2018-10-09T15:27:46Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2018-10-09T15:27:46Z"]},{"key":"dc:date.issued","label":"Date","values":["2018-05"]},{"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":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The University of Texas at Austin"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["TSP","Transit signal priority systems","Bus reliability"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["doi:10.15781/T2416TJ3G"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/2152/68738"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["A Transit Signal Priority (TSP) system’s fundamental job is to give priority to transit vehicles enabling faster passage through signalized intersections. 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