  Autonomous mobility on demand services have the potential to disrupt the
future mobility system landscape. Ridepooling services in particular can
decrease land consumption and increase transportation efficiency by increasing
the average vehicle occupancy. Nevertheless, because ridepooling services
require a sufficient user base for pooling to take effect, their performance
can suffer if multiple operators offer such a service and must split the
demand. This study presents a simulation framework for evaluating the impact of
competition and cooperation among multiple ridepooling providers. Two different
kinds of interaction via a broker platform are compared with the base cases of
a single monopolistic operator and two independent operators with divided
demand. In the first, the broker presents trip offers from all operators to
customers (similar to a mobility-as-a-service platform), who can then freely
choose an operator. In the second, a regulated broker platform can manipulate
operator offers with the goal of shifting the customer-operator assignment from
a user equilibrium towards a system optimum. To model adoptions of the service
design depending on the different interaction scenario, a game setting is
introduced. Within alternating turns between operators, operators can adapt
parameters of their service (fleet size and objective function) to maximize
profit. Results for a case study based on Manhattan taxi data, show that
operators generate the highest profit in the broker setting while operating the
largest fleet. Additionally, pooling efficiency can nearly be maintained
compared to a single operator. With the resulting increased service rate, the
regulated competition benefits not only operators (profit) and cities
(increased pooling efficiency), but also customers. Contrarily, when users can
decide freely, the lowest pooling efficiency and operator profit is observed.
