In the past ten years, the popularity of car sharing schemes has been growing rapidly. Depending on service policies, a customer might be required to return the vehicle to the same location or a different one. The latter type of service is termed as one-way car sharing since the client is not required to make a return trip to leave the vehicle. It is expected that the car sharing companies will start offering autonomous vehicles in their fleet in the future, in line with the growth of investment in autonomous cars in the automotive industry. Fleet management of autonomous vehicles is, therefore, an area which could be explored to devise and offer solutions to companies regarding autonomous vehicle applications. This paper explores the implementation of an approach with a mixed-integer programming (MIP) algorithm which is inspired by one-way car sharing schemes, to offer assistance on strategic decisions such as fleet size, depot location, and number, as well as depot capacity for shared autonomous vehicle (SAV) systems within cities. The proposed model uses stochastic demand based on expected origin and destination (OD) matrices for a modified version of the Sioux Falls network, incorporates relocations to serve demand and is subject to charging and maintenance constraints. The results show that the proposed model could potentially be used in larger networks, with expected demand of trips to be used as a relocation strategy.