Congestion pricing and License Plate Rationing (LPR) are classical transportation policies targeting travel demand. Travelers are constrained to reduce their cars' usage to improve traffic conditions or decrease exhaust gases emissions. They have already been proven effective in the field but have also received some criticism for being unfair or badly perceived by users. On the other side, Tradable Credit and Permit Schemes (TCS/TPS) have been investigated in the literature for more than a decade but have never been implemented in practice. In this paper, we present a large-scale dynamic simulation study, corresponding to the morning peak hour for the Lyon city (France) to benchmark pricing, LPR, TCS, and TPS in terms of modal shift from personal cars to Public Transportation (PT), over a horizon of several days and with different charging schemes. Congestion dynamic in the transportation system is reproduced using a trip-based Macroscopic Fundamental Diagram (MFD) framework.We compute the modal assignment at equilibrium by iteratively solving a Quadratic Problem (QP). The initial formulation, presented in previous work for a single day and a uniform TCS, is extended to account for different days, validity cycles, charging schemes, and TPS. The benchmarking shows that the TCS outperforms LPR in terms of both social cost and carbon emissions. Making credit valid over multiple days reduces the price variability while keeping the same system performances and gain distributions.