Hierarchical route planning based on taxi GPS-trajectories

The popular methods of route planning, the planar and hierarchical algorithms, are mainly based on the Dijkstra´s algorithm. The shortest path in machine computation is always different from the optimal one in a human cognition because travel experience information of human is neglected. In this paper, hierarchical travel experience information of road network is given by statistical analysis on a large amount of taxi GPS trajectories. According to taxi trajectories, the roads can be divided into frequent roads, secondary frequent roads and seldom roads. These trajectories can well reflect a hierarchical cognition of road network because considering taxi driver´s cognition of the road network. With the hierarchical model of road network, the corresponding hierarchical route planning can be performed based on the experienced driver´s cognition. The experiments show that the route results according to the experiential information approach to optimal results more than that according to static information of road network.