Research On Road Network Matching Algorithm Based On Hidden Markov Model

In recent years,the development of cities has brought great convenience to people's daily life and travel.At the same time,there have been many problems and huge challenges,such as some of our most common traffic jams,traffic accidents and other traffic problems.In transportation,vehicle positioning equipment is becoming more and more popular,and data research has become a hot topic in the field of connected vehicles today.However,in the process of GPS data collection,due to weather and other external influences,the data we obtain is often deviated from the actual road,not on the road,or even a large deviation from the road.And road network matching can better solve the problem of positioning point deviation,so that the directly observed GPS positioning point data can be accurately mapped to the road network position.The road network matching algorithm can combine the GPS positioning point data received with the urban road network to modify the GPS positioning points so that the GPS positioning points that are not displayed on the road section are accurately displayed in the road network structure after algorithm matching.Hidden Markov Model is a probabilistic model,which has been successfully applied in the field of speech recognition.Later,it has been widely used in pattern recognition,bioinformatics and other fields.The research on applying Hidden Markov Model in transportation is not perfect.We still need to continue to study in depth.Hidden Markov Model is applied in the field of road network matching.Compared with the traditional road network matching algorithm,the matching accuracy is higher,and it also performs well for GPS positioning point data with a relatively large sampling interval.Aiming at the characteristics of low sampling frequency,uneven sampling time and large positioning error of GPS positioning points,this paper proposes an improved road network matching method based on Hidden Markov Model,and finds the corresponding road sequence according to the given original GPS point sequence.Hidden Markov Model is applied to match the original GPS data of low frequency samples on the road network matching,and the test shows that the method has good performance at low frequency GPS points.