Hierarchical Network Model And Path-Finding Algorithm In Multimodal Route Planning

The continuous development of navigation technology and expansion of city have made crowdsourcing geographic information a significant method of obtaining data.Meanwhile,with the rapid development of smart city and intelligent transportation,the need of route planning using multiple transportation modes is becoming imperious.However,traditional multimodal route planning facing large scale data of real world cannot meet the demand of calculation efficiency.The research on multimodal route planning facing crowdsourcing data is becoming a hot topic in the field of GIS.Aiming at solve the problems above,this article discussed about multimodal route planning facing OSM data.Combining with Contraction Hierarchies,optimize the algorithm.More specifically,this paper contains the following works.Firstly,a multimodal route planning method facing OSM data is proposed.Analyzing data file and data structure of OSM data,creating the multimodal road network combining the concept of switch point,and implementing the search algorithm to acquire the best route.Secondly,putting forward a route planning method based on Contraction Hierarchies.Grading the road network of OSM data based on the idea of hierarchical technique,extracting the main frame of the network,implementing Contraction Hierarchies algorithm on each grade of the network,simplifying the network and merge it together.In the end,implement the search algorithm to acquire the best route.Finally,design a prototype system of multimodal route planning.Supporting five kinds of transportation modes including walking,driving,tram,suburban and underground,the system is able to find the best route between the original point and destiny point.After giving the preferences,the results would be visualized to the users.