Visual Analysis Of Relationship Between Traffic Flow Pattern And Air Quality Based On Trend Detection Algorithm

With the rapid development of China's economy and the continuous improvement of economic level,the size of the domestic motor vehicle market is becoming larger and larger,and many families have private cars to meet the needs of convenient travel.At the same time,a large number of motor vehicle emissions will affect the quality of air,aggravating the damage to our living environment,but also seriously affect people's health.Therefore,the analysis of vehicle flow is also an important aspect of air quality analysis.At present,the relevant research on motor vehicle analysis mainly focuses on the analysis of the driving condition of vehicles on a certain road section or the movement change of a specific trajectory.Analysis of air quality includes correlation analysis of meteorological elements and air quality,dynamic evolution of urban agglomeration in space and time based on air quality data,and visual analysis of haze distribution.In this paper,the grid data of traffic flow in Beijing is used to analyze the traffic flow in a certain region,and the correlation between traffic flow and air pollutants is analyzed by combining the air quality data of Beijing.This paper designs and implements a new interactive visual analysis system for the relationship between spatial and temporal patterns of vehicle flow and air quality.Through the visual analysis of Beijing traffic flow grid data and air quality site data,it explores the spatial and temporal cycle patterns of people using taxis and the cycle rules of air quality.Then the similarity and trend change of traffic flow and air pollutants are studied.Finally,the effectiveness of the experiment is proved by case analysis.The main research contents of this paper include: First,cluster air pollutant data and traffic flow data,analyze the cycle rule.Different from the traditional similarity judgment method,this paper compared the clustering similarity of the results after clustering to judge the similarity between traffic flow and pollutants.Second,the trend detection algorithm is proposed to analyze the change of traffic flow and air quality with time.Third,design the interactive visual analysis system of the relationship between the spatial and temporal patterns of traffic flow and air quality,and effectively analyze the experimental data.