In recent years, ridesharing has become one of the most efficient and cost-effective transportation solutions allowing multiple passengers to share a single vehicle. However, effective scheduling remains a major challenge that must be addressed to improve user adoption. This paper tackles the problem through twofold objectives by providing frequent riders with reliable, pre-arranged routes and by enabling the dynamic addition of new riders to active shared trips. To achieve this, we propose an algorithm named aVC, which clusters riders into ridesharing groups based on the similarity of their frequent travel routes. This approach removes the need for users to repeatedly search for rides or endure long waiting times, as trip details and driver assignments are communicated in advance. Furthermore, when a regular ridesharing trip beings and there are vacant seats, drivers can accept real-time requests from new riders without disrupting the planned itinerary. To efficiently handle such dynamic insertion, a method biSearchIns is designed to rapidly process shared trip queries. The proposed methods are evaluated against existing approaches using simulated datasets. Experimental results demonstrate that the proposed approach outperforms current situations in computational efficiency. The number of riders served, and the overall reduction in vehicle usage.