Thesis Title
Fairness for Rideshare Systems

Research Description
Rideshare systems are widespread mobility applications where the central issue is to assign different vehicles to different passengers with various objectives. Potential fairness issues in existing rideshare systems include unfair earning among drivers, unfair waiting time among riders, and bias in predicting the number of rideshare requests that will be raised in different areas. Yufan’s research focuses on discovering various fairness issues in existing rideshare systems and propose methods to fix them. To tackle those issues, she will exploit different optimisation and prediction techniques and demonstrate proof of concept on publicly available rideshare datasets. Our target is to propose a novel model that is able to mitigate fairness issues in the rideshare system.

Supervisors
Prof Flora Salim, RMIT University
Assoc Prof Jeff Chan, University of Melbourne