**6. Conclusions**

This paper presents a direction-aware continuous moving *K*-nearest-neighbor query algorithm in road networks. In this algorithm, we adopt an efficient direction determination method that is based on road network expansion to quickly judge whether moving objects are moving towards the query point. This method can filter out moving objects that are far away from the query point and reduce the number of candidate objects for continuous *K*-nearest-neighbor query, thereby improving algorithm efficiency. In this paper, we define the road network distance of a moving object from the query object as a function of time, so we can determines when candidate objects replace the objects in the result set. The algorithm guarantees the consistency of the query results within each sub-interval; hence, it does not make continuous query requests on continuous *K*-nearest neighbor queries, avoids repeated queries and reduces computational costs.

This paper initially solves the problem of direction-aware continuous moving *K*-nearest neighbor query in road networks. However, there are still some limitations in our method. On the one hand, due to the simulated moving objects information, the more moving objects there are, the more points will move outside the edge, and the information of each moving point that arrives at the specified node will be recorded in memory, which may lead to memory overflow of computers and cause substantial difficulties in the process of comparative tests. On the other hand, when the moving object reaches a road network node, an adjacent edge of the node is randomly selected as its next traveling edge; the moving object will travel along the selected edge. This randomness does not match the reality. In future research, we will study the processing of the node and the variable motion speed of moving objects to be more realistic.

**Author Contributions:** Conceptualization, T.D., Y.S. and L.Y.; Methodology, Y.S. and L.Y.; Original draft preparation, Y.Y. and Y.S.; Paper writing Y.S. and L.Y.; Data quality check, Y.S. and L.Y.; Data validation, L.Z.; Paper revision, T.D. and L.Y.; Writing-revision &editing, Y.S. and L.Y.; Project Administration, T.D.

**Funding:** This research was supported by the following foundations: National Natural Science Foundation of China (No.61672464, No.61572437).

**Conflicts of Interest:** The authors declare no conflict of interest.
