Multiobjective routing in sustainable mobility-on-demand

Abstract

It is estimated that smart on-demand mobility services can significantly reduce emissions caused by urban transportation, especially when combined with the use of low emission vehicles and ridesharing. While current research on sustainable routing typically focuses on economic sustainability (as cost minimisation), this paper also considers the other pillars of sustainability, i.e., the environmental and social aspects of what we call sustainable and equitable Mobility-On-Demand (MOD). To that end, we apply multiobjective genetic algorithms and generate routing options that balance all three pillars of sustainability. We envisage that a diverse set of routing solutions allows participation of end-users in determining an equitable route (e.g., through voting processes) and strongly supports widespread adoption of sustainable MOD and ridesharing services. This work follows principles of human-centred intelligent systems and provides a foundation for building participatory, dynamic, and explainable MOD systems.

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Identifiers

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

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

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

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