A car parking control problem is difficult because of nonholonomic constraints and complicated environmental geometry. We proposed KPP (Korea University Path Planner) in our prior work. KPP is a appropriate scheme for a car-like mobile robot in a parking environment. The purpose of this paper is to investigate the advantages of KPP through both quantitative and qualitative analyses. For comparison, numerical simulations have been carried out by the application of KPP and the conventional RRT (Rapidly Exploring Random Tree) method. The RRT scheme is one of the widely used path planning schemes owing to its superior performance. This paper shows that KPP exhibits outstanding performance from the viewpoints of optimality and computational efficiency.