Parking difficulty in urban cities, especially in commercial areas, has attracted wide attention. With the help of remote parking of automated vehicles (AVs), people do not waste time cruising for parking, and the utilization of distant parking facilities becomes possible. This study presents a bi- level model to determine the optimal planning of parking facilities under coexistence of AVs and human-driving vehicles (HVs), where the locations and capacities of parking lots is obtained in upper and lower-level models to determine the traffic assignments. Simulated annealing (SA) is adopted in upper level for large-scale problems. Numerical experiments are conducted under different penetration rates of AVs and construction budgets. It is indicated that the total commuting costs can be reduced by 37% without increasing construction cost when there are 50% AVs. Meanwhile, the increase in total commuting costs caused by inadequate budgets can be well controlled by use of AVs.