Inferring the Purposes of Using Ride-Hailing Services through Data Fusion of Trip Trajectories, Secondary Travel Surveys, and Land-Use Attributes – Sanjana Hossain

Title: Inferring the Purposes of Using Ride-Hailing Services through Data Fusion of Trip Trajectories, Secondary Travel Surveys, and Land-Use Attributes

Abstract: The increasing market penetration of ride-hailing services offered by private transportation companies is making it imperative to understand why the trips are being made. Trip purpose information directly relates to the activities for which ride-hailing is used, thereby providing important context of travel demand generated by the services. This presentation outlines a data fusion methodology for inferring trip purposes from GPS trajectories of ride-hailing services in Toronto. The methodology has a discrete choice model at its core that predicts the most probable purpose distributions using only basic trip-related information such as approximate pick-up and drop-off locations, trip start times, and land use characteristics around the origins and destinations. The inferred purposes reveal important patterns of ride-hailing trips, which in turn will facilitate efficient urban policy planning.

Bio: Sanjana Hossain is a PhD Candidate in transportation engineering at the University of Toronto. She works under the supervision of Prof. Khandker Nurul Habib to develop data fusion methodologies for travel demand analysis. She completed her B.Sc. in Civil Engineering and M.Sc. in Transportation Engineering from Bangladesh University of Engineering and Technology.

Presented by University of Toronto ITE Student Chapter, UT-ITE.