  Rethinking cities is now more imperative than ever, as society faces global
challenges such as population growth and climate change. The design of cities
can not be abstracted from the design of its mobility system, and, therefore,
efficient solutions must be found to transport people and goods throughout the
city in an ecological way. An autonomous bicycle-sharing system would combine
the most relevant benefits of vehicle sharing, electrification, autonomy, and
micro-mobility, increasing the efficiency and convenience of bicycle-sharing
systems and incentivizing more people to bike and enjoy their cities in an
environmentally friendly way. Due to the uniqueness and radical novelty of
introducing autonomous driving technology into bicycle-sharing systems and the
inherent complexity of these systems, there is a need to quantify the potential
impact of autonomy on fleet performance and user experience. This paper
presents an ad-hoc agent-based simulator that provides an in-depth
understanding of the fleet behavior of autonomous bicycle-sharing systems in
realistic scenarios, including a rebalancing system based on demand prediction.
In addition, this work describes the impact of different parameters on system
efficiency and service quality and quantifies the extent to which an autonomous
system would outperform current bicycle-sharing schemes. The obtained results
show that with a fleet size three and a half times smaller than a station-based
system and eight times smaller than a dockless system, an autonomous system can
provide overall improved performance and user experience even with no
rebalancing. These findings indicate that the remarkable efficiency of an
autonomous bicycle-sharing system could compensate for the additional cost of
autonomous bicycles.
