EC-RIDER: Explainable AI Methods for Human-Centric Ridesharing

The EC-RIDER project will study and create novel, advanced and explainable AI methods for problems in the realm of shared urban mobility and validate them on selected ridesharing scenarios. While working towards these objectives, EC-RIDER will address four research challenges: (1) Understand and model human motivation and behavior in ridesharing applications while maintaining user privacy. (2) Develop and evaluate novel business and operations models, pricing and incentive schemes, in order to achieve a satisfactory degree of social welfare. (3) Develop and evaluate innovative algorithmic AI methods to find human-centered, socially sustainable, fair and efficient traffic assignments. (4) Develop and evaluate new methodologies for explaining decisions of these AI algorithms to human users, aiming to increase user satisfaction.