This research is conducted under supervision of KTH Associate Professor Michele Simoni. This project develops a dynamic crowdshipping simulation framework to evaluate the feasibility and efficiency of a last-mile delivery service leveraging public transit passengers in Stockholm. The framework models a dynamic assignment system, where parcel deliveries are assigned to public transit passengers using a cost minimization optimization process. The study integrates real-world data from Swedish statistical institutions, SL transit records, and a survey conducted by KTH on crowdshipping preferences among public transit users. The dynamic framework is tested under varying condition, including different metro stations, demand profiles and share of available crowdshippers. A sensitivity analysis is conducted to test the proposed assignment strategies under different condtions.