In this paper, we study the task of aggregating user-generated trajectories in a differentially private manner. We present a new algorithm for this problem and demonstrate its effectiveness and practicality through detailed experiments on real-world data. We also show that under simple and natural assumptions, our algorithm has provable utility guarantees.