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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/15956
Full metadata record
DC FieldValueLanguage
dc.contributor.advisorScott, Darren-
dc.contributor.authorDalumpines, Ron-
dc.date.accessioned2014-09-26T19:23:34Z-
dc.date.available2014-09-26T19:23:34Z-
dc.identifier.urihttp://hdl.handle.net/11375/15956-
dc.description.abstractMost transportation problems arise from individual travel decisions. In response, transportation researchers had been studying individual travel behavior – a growing trend that requires activity data at individual level. Global positioning systems (GPS) and geographical information systems (GIS) have been used to capture and process individual activity data, from determining activity locations to mapping routes to these locations. Potential applications of GPS data seem limitless but our tools and methods to make these data usable lags behind. In response to this need, this dissertation presents a GIS-based toolkit to automatically extract activity episodes from GPS data and derive information related to these episodes from additional data (e.g., road network, land use). The major emphasis of this dissertation is the development of a toolkit for extracting information associated with movements of individuals from GPS data. To be effective, the toolkit has been developed around three design principles: transferability, modularity, and scalability. Two substantive chapters focus on selected components of the toolkit (map-matching, mode detection); another for the entire toolkit. Final substantive chapter demonstrates the toolkit’s potential by comparing route choice models of work and shop trips using inputs generated by the toolkit. There are several tools and methods that capitalize on GPS data, developed within different problem domains. This dissertation contributes to that repository of tools and methods by presenting a suite of tools that can extract all possible information that can be derived from GPS data. Unlike existing tools cited in the transportation literature, the toolkit has been designed to be complete (covers preprocessing up to extracting route attributes), and can work with GPS data alone or in combination with additional data. Moreover, this dissertation contributes to our understanding of route choice decisions for work and shop trips by looking into the combined effects of route attributes and individual characteristics.en_US
dc.language.isoen_USen_US
dc.subjectGPSen_US
dc.subjecttime use diaryen_US
dc.subjectepisode extractionen_US
dc.subjectmultinomial logiten_US
dc.subjecttravel behavioren_US
dc.subjectmode detectionen_US
dc.subjectepisode reconstructionen_US
dc.subjectGISen_US
dc.subjectmap-matchingen_US
dc.subjectroute choiceen_US
dc.subjectpath size logiten_US
dc.subjectpotential path areaen_US
dc.subjectscale estimationen_US
dc.subjectPythonen_US
dc.subjectArcGISen_US
dc.subjectactivity analysisen_US
dc.subjecttrip reconstructionen_US
dc.subjectsmartphoneen_US
dc.subjectglobal positioning systemen_US
dc.subjectgeographic information systemen_US
dc.subjecttoolkiten_US
dc.subjectwork tripen_US
dc.subjectshop tripen_US
dc.subjectpotential activity locationen_US
dc.subjectland useen_US
dc.subjectactivity episodeen_US
dc.subjecttravel episodeen_US
dc.subjectstop episodeen_US
dc.subjecttransferabilityen_US
dc.subjectscalabilityen_US
dc.subjectmodularityen_US
dc.subjectscriptingen_US
dc.subjectbig dataen_US
dc.subjecttravel surveyen_US
dc.subjectrespondent burdenen_US
dc.subjectpreprocessingen_US
dc.subjectmultipath erroren_US
dc.subjecttrackingen_US
dc.subjectpurpose detectionen_US
dc.subjectsegmentationen_US
dc.subjectdata filteren_US
dc.subjectdata smoothingen_US
dc.subjectfuzzy logicen_US
dc.subjectneural networken_US
dc.subjectdecision treeen_US
dc.subjectrule-based algorithmen_US
dc.subjecttrajectoryen_US
dc.subjectpointen_US
dc.subjectroad networken_US
dc.subjectnetwork dataseten_US
dc.subjectgatewayen_US
dc.subjectshortest pathen_US
dc.subjecthorizontal dilution of precisionen_US
dc.subjectHDOPen_US
dc.subjectcommonality factoren_US
dc.subjectmode transfer pointen_US
dc.subjectHalifaxen_US
dc.subjectNova Scotiaen_US
dc.subjectSpace-Time Activity Researchen_US
dc.subjectvariance inflation factoren_US
dc.subjectshapefileen_US
dc.subjectcomma-separated valuesen_US
dc.subjecttraveling salesman problemen_US
dc.subjectdata miningen_US
dc.subjectbranch-and-bound algorithmen_US
dc.subjectpedestrian networken_US
dc.subjectalternative routeen_US
dc.subjectobserved routeen_US
dc.subjectroute efficiencyen_US
dc.subjectroute attributesen_US
dc.subjectdistanceen_US
dc.subjecttimeen_US
dc.subjectheadingen_US
dc.subjectbearingen_US
dc.subjectdurationen_US
dc.subjectaccelerationen_US
dc.subjectlatitudeen_US
dc.subjectlongitudeen_US
dc.subjectcoordinateen_US
dc.subjectoverlay analysisen_US
dc.subjectintersecten_US
dc.subjectshoppingen_US
dc.subjectmoduleen_US
dc.subjectdata loggeren_US
dc.subjectwalken_US
dc.subjectlikelihood ratio testen_US
dc.subjectclassification tableen_US
dc.subjectpath generationen_US
dc.subjectkappa statisticen_US
dc.subjectdegreesen_US
dc.subjectdata collectionen_US
dc.subjecttransportation researchen_US
dc.subjectautomateen_US
dc.subjectframeworken_US
dc.subjectArcToolboxen_US
dc.subjectspatio-temporalen_US
dc.subjectnavigationen_US
dc.subjectpositioningen_US
dc.subjecttrace pathen_US
dc.subjectspatial dataen_US
dc.subjecttopologyen_US
dc.subjecthorizontal accuracyen_US
dc.subjectSPSSen_US
dc.subjectStataen_US
dc.subjectspatial resolutionen_US
dc.subjecttemporal resolutionen_US
dc.subjecthousehold surveyen_US
dc.subjecttrip reportingen_US
dc.subjectproximity analysisen_US
dc.subjectDMTIen_US
dc.subjectDesktop Mapping Technologies Inc.en_US
dc.subjectroad intersectionen_US
dc.subjectroute overlapen_US
dc.subjectleft turnen_US
dc.subjectright turnen_US
dc.subjectlocation analysisen_US
dc.subjecttime geographyen_US
dc.subjectspatial statisticsen_US
dc.subjectbuffer analysisen_US
dc.subjectcyclingen_US
dc.subjectbus transiten_US
dc.subjectpublic transportationen_US
dc.subjectGEOIDEen_US
dc.subjectAGILEen_US
dc.subjectdata needen_US
dc.subjectraw dataen_US
dc.subjecturban canyonen_US
dc.subjectendpointen_US
dc.subjectdata cleaningen_US
dc.subjectelevationen_US
dc.subjectsatelliteen_US
dc.subjectoutliersen_US
dc.subjectautomatic processingen_US
dc.subjectnearest nodeen_US
dc.subjectclassifieren_US
dc.subjectclassification methoden_US
dc.subjectshort tripen_US
dc.subjectmulti-pointen_US
dc.titleGIS-based Episode Reconstruction Using GPS Data for Activity Analysis and Route Choice Modelingen_US
dc.title.alternativeGIS-based Episode Reconstruction Using GPS Dataen_US
dc.typeThesisen_US
dc.contributor.departmentSchool of Geography and Geologyen_US
dc.description.degreetypeDissertationen_US
dc.description.degreeDoctor of Philosophy (PhD)en_US
Appears in Collections:Open Access Dissertations and Theses

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