Research On Road Network Incremental Updating Algorithm Based On Road Network Meshes

With the rapid development of urbanization,urban road network updates significantly.Traditional means for obtaining updated road network based on surveying and mapping not only require long time but are also not cost-effective.However,the methods for building the latest road network have been greatly advanced as positioning techniques in mobile devices are gradually being implemented in road network research and applications.Therefore,updating road networks with the vehicle GPS trajectories using various extracting algorithms has become an important research topic.This paper presented a new method of road network change detection and updating based on road network meshes.Firstly,topology analysis of the road network generated a set of minimum closed polygons(namely,road network meshes,RNM)which divided the whole study area into a set of RNMs enclosing all the trajectory points(TPs).Then,for each RNM and all TPs located within the RNM,dual spatial buffering analysis(DSBA)and a Hidden Markov model(HMM)were combined to extract the TPs that were not likely matched to existing road network,also termed as mismatched points(MPs).The dual buffering analysis labeled those TPs located close enough to RNM(within a buffered distance y)as non-MPs and TPs located far enough to RNM(a buffered distance r)as MPs.Those TPs that not processed by DSBA were classified by HMM into non-MPs and MPs.The MPs,indicating the vertices for newly developed roads were used to produce an MP density map from which all skeleton lines(SLs)were extracted.All the SLs were connected and used to update old road network.We concluded that the combination of DSBA and HMM to obtain mismatched trajectories could greatly reduce the time of finding the mismatched trajectory points.Using RNM as a control unit to compute the mismatched trajectory was effective in producing coherent and accurate road network dataset.Finally,the method was validated by the Portuguese Porto taxi trajectory data,and the experimental results indicated that the proposed method was a promising tool for updating road network at large scale.