  Cities worldwide struggle with overloaded transportation systems and their
externalities. The emerging autonomous transportation technology has the
potential to alleviate these issues, but the decisions of profit-maximizing
operators running large autonomous fleets could negatively impact other
stakeholders and the transportation system. An analysis of these tradeoffs
requires modeling the modes of transportation in a unified framework. In this
paper, we propose such a framework, which allows us to study the interplay
among mobility service providers (MSPs), public transport authorities, and
customers. Our framework combines a graph-theoretic network model for the
transportation system with a game-theoretic market model in which MSPs are
profit maximizers while customers select individually-optimal transportation
options. We apply our framework to data for the city of Berlin and present
sensitivity analyses to study parameters that MSPs or municipalities can
strategically influence. We show that autonomous ride-hailing systems may
cannibalize a public transportation system, serving between 7% and 80% of all
customers, depending on market conditions and policy restrictions.
