A vehicle sharing system (VSS) offers users to rent vehicles for a short period of time. The price of the trip is generally determined according to trip duration and length. These systems are becoming increasingly popular, primarily due to their financial and environmental advantages. However, VSSs face many operational challenges, including inventory management of vehicles and parking spots, vehicle load balancing and redistribution, pricing strategies, and demand forecasting. If these challenges are not addressed properly, the VSS risks experiencing a significant loss of customers and revenue. One of the challenges faced in such systems is the imbalance of the vehicles throughout the city. This problem is solved by forecasting the demand and rebalancing the vehicles to meet user demand. However, since it is exhausting to collect the data to develop a demand model, this project will make use of the Multi-Agent Transport Simulation Toolkit (MATSim) to build this environment. First, the student is going to review the literature related to VSSs and get familiar with MATSim software. The student is expected to develop an environment in MATSim for a VSS where the census data is used and the VSS is the only transport mode in the city other than walking. Then, she will create different scenarios in order to test the effects of different characteristics of the city/region. She will then identify the cases in which the rebalancing operations are needed. In other words, different strategies (static, reactive, and proactive) for rebalancing operations will be tested for each scenario and the results will be used to drive to conclusions which explain the relation between the city structure, demand structure and the different strategies of rebalancing operations.