Real-time Analysis Of Road Network Traffic Operation Based On Spark

With the continuous increase of the number of motor vehicles in our country,the contradiction between the demand for transportation and the supply of road resources is growing,resulting in frequent traffic congestion.Studying and analyzing the traffic status and trends of traffic in the road network can provide the reference for the traffic management department’s plan formulation and traveler route planning,and help alleviate traffic congestion.This paper conducts research based on the regional road network.In order to improve the efficiency of massive traffic data mining,a method of real-time analysis and research of traffic states is proposed to realize the prediction and evaluation of road traffic conditions.This paper uses Spark technology to build a traffic big data platform and uses distributed cluster processing to solve the traditional single-machine processing capacity and limited storage problems.According to the basic data and traffic flow data on the road,the flow,average travel time,average travel speed,and average delay time are extracted and used to determine the traffic status of the road by using a distributed clustering algorithm;By studying the spatial structure of road network,a spatial proximity matrix is constructed,and combined the time characteristics of traffic flow,the spatiotemporal correlation analysis method is used to extract the spatiotemporal factors that affect the traffic status of each road section,and this is used as the input of the neural network to realize the prediction of road traffic status.Misjudgment occurs due to the different judgment results of the road network traffic status by different indicators.This paper studies and analyzes the road network traffic status indicators such as the proportion of severe congested mileage,average travel time ratio and average delay time ratio.Method to evaluate the traffic operation status of the road network.Finally,a traffic status analysis system is built on the basis of the traffic big data platform,and the road network data is managed using information methods,and the research and analysis results can be graphically based on different needs.In the form of images and electronic maps,the visual display of traffic status is realized.Based on the regional road network data in California’s PeMS system,this paper analyzes the road network traffic flow in the traffic big data platform.The research results can effectively analyze the traffic status of each road section in the road network,the traffic flow trend in the future,and the overall traffic status of the road network can provide reference opinions for the daily travel routes of travelers,and can also provide powerful data support for the overall planning of the regional road network in the future.