In this paper, we focus on multilevel parking facilities and propose a navigation system that minimizes the time required for cars to find vacant parking spaces. Parking zones at large parking facilities provide drivers conditions to drivers due to differences in distances from the entrance of the parking facility or to the entrances of the shopping areas. This leads to many cars concentrating at some parking zones while other zones are not occupied. It is not easy for car drivers entering a large parking facility to know which parking zones are vacant. It is fairly common that parking facilities have indicators that show occupancy information to the drivers. However, since these indicators deliver the same information to all drivers, this method tends to make a new congested zone by sending many drivers to that zone. In this paper, we propose a system that provides each driver with a recommended route in the parking facility that minimizes the expected parking time. Our method estimates the occupancy of each zone from the information sensed by the cars that implement the proposed method. This information is collected to a server installed in the facility, and then the server disseminates the processed information to the cars. The cars then calculates the recommended route from this information. We conducted a simulation-based evaluation of the proposed method using a realistic model simulating a real parking facility in Nara. As a result, we confirmed that the proposed method reduced parking waiting time by 20%-70% even with low penetration ratio.