Modelling Long Haul Truck Route Choice in Ontario

dc.contributor.advisorGingerich, Kevin
dc.contributor.authorAli, Syed Ubaid Ullah
dc.date.accessioned2020-11-13T13:58:19Z
dc.date.available2020-11-13T13:58:19Z
dc.date.copyright2020-09
dc.date.issued2020-11-13
dc.date.updated2020-11-13T13:58:19Z
dc.degree.disciplineCivil Engineering
dc.degree.levelMaster's
dc.degree.nameMASc - Master of Applied Science
dc.description.abstractA route choice model is developed in this thesis to explain and predict long-haul truck vehicle movements in Ontario. An algorithm is devised to process approximately 58,000 observed trips from GPS data in ArcGIS to establish variable choice sets based on an optimal commonality factor that measures route overlap. Novel implications of the commonality factor add to the existing literature. Route characteristics are next used to estimate a C-logit model. Results indicate that truck drivers are more likely to select routes exhibiting lower minimum travel times, more freeway and Highway 401 usage, more diesel stations, and fewer intersections. The travel time is the most dominant variable based on measurements of elasticity. Two scenarios are tested using the final model to determine routing changes due to increased travel time on Highway 401 and other freeways. Further detailed scenarios can be used to predict long-haul trucking patterns for future transportation planning purposes.
dc.identifier.urihttp://hdl.handle.net/10315/37970
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectCivil engineering
dc.subject.keywordsRoute choice
dc.subject.keywordsLong-haul truck trips
dc.subject.keywordsLogit model
dc.subject.keywordsCommonality factor
dc.subject.keywordsChoice Set Generation
dc.subject.keywordsGPS data
dc.subject.keywordsTruck Route Choice
dc.subject.keywordsRoute Choice models
dc.titleModelling Long Haul Truck Route Choice in Ontario
dc.typeElectronic Thesis or Dissertation

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