Research on Double-Weighted Graph Model and Optimal Path Planning for Intelligent Tourism Navigation Considering Entrances and Exits

TLDR: A Double-Weighted Graph Model considering multiple entrances and exits for tourist scenic area, and the weights of both vertexes and edges of the proposed model can be selected and weighted dynamically, and an optimal path planning algorithm based on Dijkstra algorithm and Prim algorithm is proposed.

Abstract: When visiting multiple tourist scenic spots, a recommended travel line is usually the most effective route designed for tourists according to the actual road situations. In the field of intelligent tourism navigation, a traditional recommended travel line is mainly generated by path planning algorithm automatically, considering thescenic spots' positions and road networks based on graph model. Normally, the traditional algorithms firstly map scenic spots(which belong to certain scenic area) into points of interests(POIs),and map the road network that links these POIs into a line collection, then build the corresponding graph model. But when a scenic spot has a limited area and involves multiple entrances or exits(for example buildings with multiple indoor space), the traditional described mechanism for single point coordinates is difficult to reflect these structural features. In reality, scenic area path planning is widely applied in the field of mobile tourism guide recently, especially for pedestrians. There exist significant differences between theoretical optimal paths and actual optimal paths, sincetouristsare inclined to have more choices. In order to solve this problem, this paper analyzed various influences on the process of path planning, caused by scenic spots' own structural features(such as the size, shape and entrance),and focused on the influences of multiple entrances or exits located within the scenic area. Then,we proposed a Double-Weighted Graph Model considering multiple entrances and exits for tourist scenic area, and the weights of both vertexes and edges of the proposed model can be selected and weighted dynamically. Next, we discussed the building method for the model, and proposed an optimal path planning algorithm based on Dijkstra algorithm and Prim algorithm. Experimental results show that the optimal planned travel line derived from this proposed model and algorithms is considerably reasonable, and the travelling order and travelling distance can be further optimized.