Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Identifying Critical Fleet Sizes Using a Novel Agent-Based Modelling
  Framework for Autonomous Ride-Sourcing   Ride-sourcing platforms enable an on-demand shared transport service by
solving decision problems often related to customer matching, pricing and
vehicle routing. These problems have been frequently represented using
aggregated mathematical models and solved via algorithmic approaches designed
by researchers. The increasing complexity of ride-sourcing environments
compromises the accuracy of aggregated methods. It, therefore, signals the need
for alternative practices such as agent-based models which capture the level of
complex dynamics in ride-sourcing systems. The use of these agent-based models
to simulate ride-sourcing fleets has been a focal point of many studies;
however, this occurred in the absence of a prescribed approach on how to build
the models to mimic fleet operations realistically. To bridge this research
gap, we provide a framework for building bespoke agent-based models for
ride-sourcing fleets, derived from the fundamentals of agent-based modelling
theory. We also introduce a model building sequence of the different modules
necessary to structure a simulator based on our framework. To showcase the
strength of our framework, we use it to tackle the highly non-linear problem of
minimum fleet size estimation for autonomous ride-sourcing fleets. We do so by
investigating the relationship of system parameters based on queuing theory
principles and by deriving and validating a novel model for pickup wait times.
By modelling the ride-sourcing fleet function in the urban areas of Manhattan,
San Francisco, Paris and Barcelona, we find that ride-sourcing fleets operate
queues with zero assignment times above the critical fleet size. We also show
that pickup wait times have a pivotal role in the estimation of the minimum
fleet size in ride-sourcing operations, with agent-based modelling to be a more
reliable route for their identification given the system parameters.

9
The categories of this paper are: nlin
16
The categories of this paper are: stat
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph
21
The categories of this paper are: adap-org
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
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The categories of this paper are: hep-th
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The categories of this paper are: cmp-lg
3
The categories of this paper are: physics
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The categories of this paper are: gr-qc
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The categories of this paper are: q-fin
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The categories of this paper are: q-bio
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The categories of this paper are: nucl-ex