found within a walkable distance [4]. In these districts, most of the trips would be one-person, short distance,
and low speed, reducing car dependency and favoring walking and sustainable micro-mobility systems [4–6].
In this scenario, micro-mobility systems could be a solution for these short-distance trips and provide the
first- and last-mile connection to mass transit. Furthermore, micro-mobility solutions could also be used for
package or food delivery when not in use by riders [6].
With this image of a future city in mind, the MIT Media Lab City Science research group has developed
several mobility solutions over the last decades. These solutions include vehicles such as the CityCar
lightweight electric folding automobile, or the PEV, an autonomous three-wheeler designed for shared use
[7, 8]. One of the most recent projects is the MIT Autonomous Bicycle Project: a novel system that
aims to bring autonomy into bicycle-sharing systems (BSS) [9]. Autonomous driving capabilities would
transform BSS into an on-demand mobility system, radically increasing the convenience of bike-share [9].
In an autonomous BSS, a user would be able to request a trip through a mobile app, and an autonomous
bicycle would drive to the user’s location. Then, the user would ride the autonomous bicycle just like a
regular bicycle. Upon arrival to the destination, the bicycle would drive autonomously to pick up another
user, to a charging station, or towards wherever the demand is predicted to occur.
We envision this bike to be part of the ecosystem of shared and autonomous micro-mobility in future
walkable cities, as well as a new approach to current bicycle-sharing systems. Governments all over the
world have been promoting public BSS, intending to improve mobility and public health and introduce
a sustainable mode of transportation [10]. Especially in the last 15 years, BSS have quickly proliferated,
increasing from 17 station-based systems worldwide in 2005 to over 2000 in 2019 [9].
However, current BSS still face several challenges, among which it is worth highlighting the rebalancing
problem caused by uneven travel patterns and the oversupply of bicycles that often happens in dockless
systems [11–15]. Autonomous bicycles could be the solution to these challenges: For the system operators,
it would solve the rebalancing problem and make the sharing system more efficient, with higher vehicle
utilization rates and smaller fleet sizes. Moreover, having bicycles with autonomous driving capabilities
would bring the convenience of mobility-on-demand into the current BSS, improving user experience. This
article aims to describe and quantify to which extent an autonomous system would outperform the current
BSS.
Most of the previous research around the performance of shared autonomous vehicles has been focused
on cars or taxis. Narayanan et al. [16] provide an overview of the relevant studies in the field of shared
autonomous vehicle (SAV) services published from 1950 to 2019. This overview covers the most relevant
work done in terms of simulations SAV [17–25] and provides a comparison of the main results. While this
overview explicitly warns that bike-sharing and scooter-sharing systems are not considered in the study,
there are several similarities between simulations of other shared autonomous vehicles, such as cars, taxis,
or buses, and shared autonomous bikes. Therefore, we recommend visiting the overview mentioned above
for further details. With regards to simulations related to autonomous micro-mobility, Grignard et al.
[26] proposed a generic simulation framework that allows for modeling different future mobility modes and
understanding their impact on traffic and congestion. Recently, Kondor et al. [27] presented a simulation
study of the impact of a fleet of autonomous scooters.
Due to the uniqueness and radical novelty of introducing autonomous driving technology into BSS
and the inherent complexity of these systems, there is the need to quantify the potential impact that
autonomy might have on the fleet performance and user experience. Consequently, this paper presents an
ad-hoc simulator that provides an in-depth understanding of the fleet behavior of an autonomous BSS, how
different parameters affect the performance, and a quantification of the extent to which it outperforms the
current BSS. These simulations were conducted considering the most realistic possible scenarios, including
a rebalancing system based on demand prediction.
The remainder of the paper is organized as follows. Section 2 describes some central aspects for the
mobility modes of future walkable cities. Section 3 analyzes how autonomous bicycles can pose a new
and more efficient approach to BSS. Then, Section 4 describes the architecture of the proposed agent-based,
discrete event simulation framework along with its main features. The three BSS under study are also defined
and formalized in this section. Section 6 gathers the results of the simulation for the autonomous system and
current station-based and dockless systems, comparing their performance under different scenarios. This
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