Taxi Big Data Analysis And Application For Urban Traffic Planning

In recent years,the number of motor vehicles in China has continued to grow.The resulting shortage of road resources and traffic congestion has become increasingly prominent,seriously affecting and restricting the sustainable,rapid,and healthy development of the urban economy and society.Moreover,due to various factors such as technology,space,environment,and economy,it is impossible to fundamentally solve the current traffic problem by adopting a method of expanding the scale of the road network.Therefore,exploring and seeking new methods and strategies to maximize the use of resources in urban roads has become an urgent need and an inevitable trend for the development of urban transportation at this stage.The rise of big data technology has provided new solutions for urban traffic problems.In view of this,this article takes taxi big data as the object,through analyzing the traffic flow status and driver historical experience information contained in it,proposes a path planning algorithm based on hotspot road map.Based on this,an application system using Hadoop as a data processing platform is designed to achieve the optimal path query function for a given start point and end point.Specifically,the research content of this article includes:(1)Hadoop-based system overall framework design.Based on the three-tier architecture of the Internet of Things,the Hadoop platform is added as a "data processing layer" to form a four-tier architecture consisting of a perception layer,a network layer,a data processing layer,and an application layer from the bottom up.Among them,the Hadoop platform completes the storage and analysis of big data,and finally provides the analysis results to the application layer and presents them in the form of Web pages.(2)Taxi big data preprocessing and analysis.The Xi'an taxi GPS data was cleaned,and the interference data was removed.The map matching work was further combined with Xi'an road network data.On this basis,the frequency of visits and average speeds of different sections in different time periods are calculated,and the section with higher access frequency is selected as the hot section,and the map of urban hot spots is constructed based on the calculation results of the average speed.(3)Design and application of optimal path planning algorithm.Based on the map of hotspot road segment,A* algorithm was selected to improve,and the travel index,time index,and hotspot index were added as evaluation indicators for route selection.Compared with the traditional shortest path algorithm,the experimental results show that the algorithm is effective under different traffic conditions.Further apply the planning results to the query system to provide the user with an optimal route query function.