In recent years, end-to-end autonomous driving frameworks have been shown to not only enhance perception performance but also improve planning capabilities. However, most previous end-to-end autonomous driving frameworks have focused primarily on enhancing environmental perception while neglecting the learning of autonomous vehicle driving intent, which refers to the vehicle's intended direction of travel. In planning, the autonomous vehicle's direction is clear and well-defined, yet this crucial aspect has often been overlooked. This paper introduces NTT (Navigation to Target for Trajectory planning), a method within an end-to-end framework for autonomous driving. NTT generates the planned trajectory in two steps. First, it generates the future target point for the autonomous vehicle on the basis of the navigation path. Then, it produces the complete planned trajectory on the basis of this target point. On the one hand, generating the target point for the autonomous vehicle from the navigation path enables the vehicle to learn a clear driving intent. On the other hand, generating the trajectory on the basis of the target point allows for a flexible planned trajectory that can adapt to complex environmental changes, thereby enhancing the safety of the planning process. Our method achieved excellent planning performance on the widely used nuScenes dataset and its effectiveness was validated through ablation experiments.