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

The 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.

Name thesis:degree_name

Master of Science (MSc)

Discipline thesis:degree_discipline

Engineering – Geomatics

Grantor dc:publisher.institution

Schulich School of Engineering

Year dc:date.issued

2020

Author dc:creator

• de Oliveira e Silva, Rodrigo Augusto

Advisor dc:contributor.advisor

• Wang, Xin

Committee members dc:contributor.committeemember

• Stefanakis, Emmanuel
• Liang, Steve H. L.

• GPS trajectories
• Personalized travel route recommendation
• Random walk with restart
• Temporal dependency

Statement dc:rights

• University 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.

Language dc:language.iso

eng

DOI

http://dx.doi.org/10.11575/PRISM/38121

OAI identifier oai:identifier

oai:ucalgary.scholaris.ca:1880/112439