Truck queuing at marine terminal gates has long been recognized as a source of emissions problem due to the large number of trucks idling. For this reason, there is a great deal of interest among the different stakeholders to lessen the severity of this problem. In order to assist these stakeholders address the congestion problem, baseline data and predictive models are needed. With the advancement of computer technology, more and more marine terminals in the United States now offer live views of their gates via webcams as a means of managing demand for the terminals. These webcams could be used to gather much needed truck queuing information and additional truck related data. This thesis focuses on developing methodologies to utilize webcam data to predict truck queuing time.
","abstract_html":"<p>Truck queuing at marine terminal gates has long been recognized as a source of emissions problem due to the large number of trucks idling. For this reason, there is a great deal of interest among the different stakeholders to lessen the severity of this problem. In order to assist these stakeholders address the congestion problem, baseline data and predictive models are needed. With the advancement of computer technology, more and more marine terminals in the United States now offer live views of their gates via webcams as a means of managing demand for the terminals. These webcams could be used to gather much needed truck queuing information and additional truck related data. This thesis focuses on developing methodologies to utilize webcam data to predict truck queuing time.</p>","abstract_has_math":false,"creators":["Pham, Quyen Thi"],"institution":null,"degree_name":"M.S.","degree_level":"Campus Access Thesis","degree_discipline":"Civil and Environmental Engineering","degree_department":null,"school":null,"contributors":["Nathan Huynh"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-01-01T08:00:00Z","date_published":"2011-01-01T08:00:00Z","updated_at":"2026-07-24T04:37:56Z","subjects":["Civil and Environmental Engineering","Engineering","Gatecam","Prediction","Regression","Terminal port","Truck queuing","Waiting time"],"languages":[],"rights":["© 2011, Quyen Thi Pham"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarcommons.sc.edu/etd/645","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Nathan Huynh"]},{"key":"dc:creator","label":"Author","values":["Pham, Quyen Thi"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil and Environmental Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Campus Access Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Civil and Environmental Engineering","Engineering","Gatecam","Prediction","Regression","Terminal port","Truck queuing","Waiting time"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["© 2011, Quyen Thi Pham"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarcommons.sc.edu/etd/645"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Truck queuing at marine terminal gates has long been recognized as a source of emissions problem due to the large number of trucks idling. For this reason, there is a great deal of interest among the different stakeholders to lessen the severity of this problem. In order to assist these stakeholders address the congestion problem, baseline data and predictive models are needed. With the advancement of computer technology, more and more marine terminals in the United States now offer live views of their gates via webcams as a means of managing demand for the terminals. These webcams could be used to gather much needed truck queuing information and additional truck related data. This thesis focuses on developing methodologies to utilize webcam data to predict truck queuing time.
"]},{"key":"dc:title","label":"Title","values":["Truck Queuing At Seaports Using Terminal Webcam"]}]}],"canonical_facts":{"dc:contributor":["Nathan Huynh"],"dc:creator":["Pham, Quyen Thi"],"dc:description.abstract":["Truck queuing at marine terminal gates has long been recognized as a source of emissions problem due to the large number of trucks idling. For this reason, there is a great deal of interest among the different stakeholders to lessen the severity of this problem. In order to assist these stakeholders address the congestion problem, baseline data and predictive models are needed. With the advancement of computer technology, more and more marine terminals in the United States now offer live views of their gates via webcams as a means of managing demand for the terminals. These webcams could be used to gather much needed truck queuing information and additional truck related data. This thesis focuses on developing methodologies to utilize webcam data to predict truck queuing time.
"],"dc:identifier":["https://scholarcommons.sc.edu/etd/645"],"dc:rights":["© 2011, Quyen Thi Pham"],"dc:subject":["Civil and Environmental Engineering","Engineering","Gatecam","Prediction","Regression","Terminal port","Truck queuing","Waiting time"],"dc:title":["Truck Queuing At Seaports Using Terminal Webcam"],"thesis:degree_discipline":["Civil and Environmental Engineering"],"thesis:degree_level":["Campus Access Thesis"],"thesis:degree_name":["M.S."]},"updated_at":"2026-07-24T04:37:56Z"}