The recent build-up network of Automatic Identification System (AIS) equipped on vessels provides a rich source of vessel movement information. AIS is originally designed for automatically exchanging navigation information, such as their unique identification, position, course, and speed, with nearby vessels and terrestrial receivers to affect collision avoidance and safety control. The collected sequences of AIS logs can be considered as maritime trajectory data, i.e., the sequences of location points with timestamps. This vast amount of AIS trajectory data can be collected and employed to achieve an awareness of maritime traffic knowledge. This paper is devoted to discovery of maritime traffic route from trajectory data generated by AIS networks. However, AIS trajectory data discovery is a challenging task because of the trajectory data is available with uncertainty. Furthermore, unlike the vehicles' movements are constrained by road networks, there is no such a sea route for vessels to follow in marine areas. To overcome the challenges, we propose a framework of Maritime Traffic Route Discovery (abbreviated as MTRD) to generate pattern-aware routes to achieve an effective understanding of maritime traffic awareness. The proposed framework is evaluated on real AIS data and the experimental results shows that the proposed MTRD is able to extract the marine traffic route effectively and provides a cornerstone of maritime traffic knowledge for traffic management, anomaly detection, and conflict analysis in the future.