Research On Dynamic Path Optimization Problem Based On Improved Map Matching Algorithm And Dijkstra Algorithm

In recent years,with the rapid development of social economy and transportation technology,urban logistics distribution have been flourishing.It is increasingly necessary to optimize distribution models and improve the efficiency logistics distribution.On the other hand,the problem of urban traffic has become increasingly serious,and the Intelligent Transportation System(ITS)has emerged.Intelligent Transportation System is a general term for traffic systems that use traffic information systems,positioning systems,and intelligent analysis.It can provide real-time and effective information for vehicles,realize route planning,reduce vehicle driving time,ease road congestion,reduce pollution,and save energy.As an important part of the intelligent traffic system,dynamic path optimization plays an increasingly important role in solving traffic congestion and vehicle driving problems.It is an important issue in the logistics industry today how to properly arrange the travel route of a logistics delivery vehicle and to complete the distribution task with the least travel time within the stipulated time and overcome difficulties such as traffic jams.Applying efficient and practical dynamic path optimization techniques to current logistics distribution can shorten distribution time,reduce distribution costs,and improve logistics service levels.In this paper,the research of dynamic path optimization based on improved Map matching algorithm and Dijkstra algorithm is studied.The related research contents are as follows:Firstly,the background and significances of researching the dynamic path optimization are expounded in detail.The domestic and foreign research status and related theories of Map matching and path optimization are introduced.The necessity of studying dynamic path optimization is emphasized.Secondly,based on the detailed introduction of Map matching related knowledge,a Map matching method for logistics vehicle navigation using Frechet distance was improved.The new algorithm was modified in three aspects of adjustability,real-time,and integrity,which improved the the accuracy of the match.In order to test the performance of the Map matching algorithm,the paper used the collected GPS data of the vehicle to perform corresponding practical tests on related software.The research results show that the new Map matching algorithm has feasibility and operability in vehicle navigation.It corrects the deviation of GPS positioning information and has higher matching accuracy,which reflects the advantages of the new algorithm.Therefore,Map matching algorithm not only has theoretical significance,but also has practical application value.In this way,the accurate and real-time dynamic traffic information obtained provides basic conditions for the routing of logistics vehicles.Thirdly,the related concepts of graphs in graph theory are studied.Based on this,the classic Dijkstra algorithm is studied and analyzed.Aiming at the defects of the classical Dijkstra algorithm,an optimization scheme was proposed.Improvements were made in the three aspects of storage structure,search method,and data queue.By comparing the results of the Dijkstra algorithm before and after the improvement,the advantages of the improved algorithm in terms of running time and search efficiency are verified.Finally,the road network of the city is abstracted into a virtual road network.Based on the virtual road network,a dynamic road network model is constructed with the travel time of the road section as the weight and the least travel time as the objective function.Through simulation experiments,we can see that the optimal logistics distribution path planned by the dynamic path optimization algorithm in this paper is more in line with the actual situation and has a high practical value.