  We consider ride-sharing networks served byhuman-driven vehicles and
autonomous vehicles. First, wepropose a novel model for ride-sharing in this
mixed autonomysetting for a multi-location network in which the platformsets
prices for riders, compensation for drivers, and operatesautonomous vehicles
for a fixed price. Then we study thepossible benefits, in the form of increased
profits, to the ride-sharing platform that are possible by introducing
autonomousvehicles. We first establish a nonconvex optimization
problemcharacterizing the optimal profits for a network operatingat a
steady-state equilibrium and then propose a convexproblem with the same optimal
profits that allows for efficientcomputation. Next, we study the relative mix
of autonomous andhuman-driven vehicles that results at equilibrium for
variouscosts of operation for autonomous vehicles. In particular, weshow that
there is a regime for which the platform will chooseto mix autonomous and
human-driven vehicles in order tooptimize profits. Our results provide insights
into how suchride-sharing platforms might choose to integrate
autonomousvehicles into their fleet.
