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In this paper, we introduce a practical two-layer planning framework for autonomous vehicles operating in unknown off-road environment. The first layer refers to a global path planning layer, searching a shortest global path from road network according to given task points. We build up road network through pre-processing on Google earth and refactoring network in terms of vehicle real historical trajectory on real-time. The second layer refers to a local planning layer, solving a real-time planning problem to generate a collision-free and kinematic-feasible local path by a hybrid trajectory planning method. Our method has been verified in real off-road environment. Experimental results show that the proposed planning method performs well in off-road environment.