According to driving scenarios, intelligent vehicle is mainly applied on urban driving, highway driving and close zone driving, etc. As one of the most valuable developments, automated highway driving has great progress. This paper focuses on automated highway driving decision, and considering decision efficiency and feasibility, a hierarchical motion planning algorithm based on dynamic programming was proposed, and simultaneously, road coordinate transformation methods were developed to deal with complex road conditions. At first, all transportation user states are transformed into straight road coordinate to simplify modeling and planning, then a set of candidate paths with Bezier form was developed and with the help of obstacles motion prediction, the feasible target paths with collision-free were remains, and via comparing vehicle performance for feasible path, the optimal driving trajectory was generated. At last, the optimal control model was applied to obtain the motion parameters, which were regarded as the control target for lower level controller. A three-lane highway simulations was designed, and the results demonstrated that the proposed algorithm was valid to avoid obstacles with given speed, and by split planning and optimization, the computation cost could be easily configured by sampling nodes. This paper gives a synthetic automated highway driving decision system design and reveals a practical engineering application for intelligent vehicle.