In this paper, we present a comparative analysis of five methods for constructing ride-sharing pools of users, focusing on their efficiency in terms of execution time, the percentage of user requests fulfilled, the distance of the detour made by the driver and the waiting time of the passenger. Furthermore, we introduce a model able to simulate user demand, based on car usage data across different time intervals in Belgium. Then, we use the proposed model as a basis for evaluating the performance of the five methods and their variants: OD Similarity, OD Clustering, OD Time Alignment, Trip Similarity, and Trip Buffering.