Abstract: Existing algorithms for hot route detection are difficult to solve the complex coupled problem of hot routes, or they need the support of road network topologies. In order to overcome these disadvantages, we present a hot route detection algorithm based on grid clustering. In this algorithm the trajectory is converted to grid sequence, and the density reachability of the neighbor grids is determined based on their common traffic, and then the grids are abstracted to a graph model. So the grid clustering algorithm, GridGrowth, can be presented based on the graph theory, i.e. the hot route detection algorithm. Experimental results show that the proposed algorithm can effectively detect the hot routes and can accurately solve the complex coupled problem of the hot routes.

Key words: computer application, coupled problem, trajectory mining, hot routes, grid clustering