The application of ground mobile robots in complex outdoor environments, particularly in rugged terrains, has been widely investigated to improve the capability. The terrain features significant variations in elevation, with dramatic surface undulations and diverse slope changes. In such terrain, path planning for mobile robots must balance both the distance of the path and safety considerations, and there are many safety issues that still need to be addressed. In unstructured environments, the determination of terrain traversability is crucial for generating global paths. This paper proposes a terrain traversability analysis based on Plane Fitting Rapidly-Exploring Random Trees* (PF-RRT*) to enhance the safety of ground mobile robots in outdoor terrains. The traversability metrics include sparsity and flatness of the planes containing the points along the PF-RRT* path, as well as the predicted pitch and roll angles of the mobile robot at those points. These metrics are incorporated into a cost function to assess the traversability of points along the path. The simulation results demonstrate that the proposed method could obtain safer paths with smoother velocities and has better performance compared with traditional strategies.