Exploring Personalized Route Recommendation Based on Travel Behaviors of Historical GPS Trajectories

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dc.contributor.advisorWang, Xin
dc.contributor.authorde Oliveira e Silva, Rodrigo Augusto
dc.contributor.committeememberStefanakis, Emmanuel
dc.contributor.committeememberLiang, Steve H. L.
dc.date.accessioned2020-08-27T21:10:30Z
dc.date.available2020-08-27T21:10:30Z
dc.date.issued2020-08-25
dc.description.abstractThe most popular navigation applications and services optimize routes based on either distance or time, disregarding drivers’ preferences when suggesting routes. Various unknown circumstances may affect users’ travel behaviors between two locations on the road network, hence it is complicated to provide satisfactory personalized route recommendations. In this thesis, it is believed that users’ travel behaviors are implicitly reflected and can be learned from their historical Global Positioning System (GPS) trajectories. The Behavior-based Route Recommendation (BR²) method is proposed to compute personalized routes based exclusively on users’ travel preferences. The concepts of appearance and transition behaviors are defined to describe users’ travel behaviors. The behaviors are extracted from users’ past travels and the missing behaviors, of locations not yet visited, are estimated with the Optimized Random Walk with Restart technique. Furthermore, the temporal dependency of travel behaviors is considered by constructing a time difference interval histogram. A behavior graph is generated to allow the maximum probability route computation with the shortest path algorithm, resulting in the most likely route to be taken by a user. Experiments conducted on two real GPS trajectory data sets demonstrate the efficiency and effectiveness of the proposed method. In addition, a web-based geographic information system (GIS) application is designed and implemented to demonstrate differences in route recommendation when time, distance, or users’ preferences are considered, besides providing insight about users' movement through data visualization of their spatial and temporal coverage.en_US
dc.identifier.citationde Oliveira e Silva, R. A. (2020). Exploring Personalized Route Recommendation Based on Travel Behaviors of Historical GPS Trajectories (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/38121
dc.identifier.urihttp://hdl.handle.net/1880/112439
dc.language.isoengen_US
dc.publisher.facultySchulich School of Engineeringen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectGPS trajectoriesen_US
dc.subjectPersonalized travel route recommendationen_US
dc.subjectRandom walk with restarten_US
dc.subjectTemporal dependencyen_US
dc.subject.classificationSociology--Transportationen_US
dc.subject.classificationComputer Scienceen_US
dc.titleExploring Personalized Route Recommendation Based on Travel Behaviors of Historical GPS Trajectoriesen_US
dc.typemaster thesisen_US
thesis.degree.disciplineEngineering – Geomaticsen_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameMaster of Science (MSc)en_US
ucalgary.item.requestcopytrueen_US
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