Transportation Network Companies (TNC), like Uber, Lyft, and VIA, started their activities a decade ago with a far-reaching hope that Mobility-On-Demand (MOD) transportation services would decelerate or even stop the ever-growing congestion. However, it didn't happen; the negative incentives, like congestion charges and higher parking prices, seem to be the only policy tools for influencing congestion and associated negative externalities like pollution and noise. The question is whether we can establish socially acceptable congestion charges and parking prices that will effectively reduce the arrivals and traffic in highly congested areas and become the background for the future MOD arrangement? We employ the MATSim agent-based simulation model (Horni et al., 2016) of multi-modal traffic in Jerusalem Metropolitan Area (JMA) to address this problem. We investigate whether the combination of congestion and parking prices can force drivers to use Public Transport (PT), thus reducing arrivals with the private cars into the center of the city. The model study demonstrates that a reasonable charge of 7–12€ for entering the city center could decrease arrivals by 25%. From the transport policy point of view, the effects of congestion charges and parking prices are different – the increase in the congestion charges decreases arrivals. In contrast, the increase in parking prices decreases the dwell time. We discuss the policy consequences of employing each of the two mechanisms.