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

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.

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Identifiers

ORCID for Vahid Yazdanpanah: orcid.org/0000-0002-4468-6193

ORCID for Enrico H. Gerding: orcid.org/0000-0001-7200-552X

ORCID for Sebastian Stein: orcid.org/0000-0003-2858-8857

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