Fair and efficient ride-scheduling: a preference-driven approach

Yi Cheng Ong, Nicos Protopapas, Vahid Yazdanpanah, Enrico H. Gerding and Sebastian Stein

Journal of Simulation, 2024, vol. 18, issue 6, 940-956

Abstract: Smart mobility and, in particular, automated ridesharing platforms promise efficient, safe, and sustainable modes of transportation in urban settings. To make such platforms acceptable to the end-users, it is key to capture their preferences not in a static manner (by determining a fixed route and schedule for the vehicle) but in a dynamic manner by giving the riders the chance to get involved in the routing process of an upcoming journey. To that end, this work provides a toolbox of multiagent methods that enable different forms of active preference-awareness in ridesharing services. We capture riders’ preferences (as end-users of a ridesharing service), preserve their privacy by avoiding expecting them to share preferences with other riders, and show the efficacy of the presented ridesharing algorithms using agent-based simulation and illustrating their utilitarian and fairness properties.

Date: 2024
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DOI: 10.1080/17477778.2024.2334826

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