Visual Analysis Of Resident Trip Mode Based On Taxi OD Data

With the development of urbanization and the increasing population of the city,despite the great increase in the material and spiritual civilization of the residents,but it also brought a series of sharp social problems:urban traffic congestion intensified,travel time-consuming,travel costs increased.Therefore,the analysis of the behavior of residents in traffic planning and decision-making has an increasingly important role.The traditional residents travel information collected by the completion of artificial,it has brought heavy work,long cycle,high labor costs,high error rate,these problems have not applied to the requirements of contemporary development.With the rapid development and popularization of the mobile intelligent terminal as the carrier,it is possible to collect the trajectory data of the moving object with the sensor having the spatial position recording function.The use of these positioning technology to generate a large number of microblogging sign data,taxi GPS data,bus credit card data and other temporal-spatial data,these temporal-spatial data has beeb focused by the geographical sciences,computer science,anthropology,urban planning and other disciplines.Trajectory data are widely used in the research of urban space,urban residents as the main body of urban mobility,its behavior patterns is of great significance for the research of urban space.Based on the research of the urban residents travel mode,at the city level can reasonable allocate urban traffic resources,effective management of urban traffic order,and reduce the pollution of urban environment;At the residential level,it is possible to optimize personal mobility and save travel costs.The data source used in this paper is the data of GPS mobile trajectory of urban taxi.It contains a lot of travel information of urban residents,and has the characteristics of high precision,continuity and privacy.As the taxi GPS track data with massive,complex structure of the characteristics,if only with the original trajectory data is difficult to have a deep understanding.The method of spatial statistics provides the most direct tool for us to understand the massive temporal-spatial data macroscopically,and the visual analysis technique can show our research results in an efficient and intuitive way.First of all,this article on the taxi GPS track data to clean,filter,remove the original data which due to equipment or environmental factors,filter GPS devices often drift point records;and then,according to vehicle sensors and equipment recorded passenger status,which presented the passenger car's operating activities.Then,the urban space is divided into fine-grained blocks based on the data of the main road network of the city.These blocks will be studied as Spatial subunits are also the smallest units of interaction between study areas.Secondly,the three spatial statistical indexes of BCI,BIDI and BDI are proposed.The spatial distribution of urban residents is analyzed from three dimensions:spatial,time and attribute.And the three indicators are added to the properties of the land.The spatial correlation of the three indexes is carried out by using the spatial correlation analysis of spatial correlation in spatial statistics,and the degree of spatial aggregation is judged according to the confidence level and present urban residents flow hot area.Finally,the method of visualization in data visualization is used to improve the existing classical edge binding algorithm by taking into account the correlation edge selection strategy of spatial similarity factor.This paper analyzes the urban residents'travel structure by visualization of the structure of the urban residents,and obtains the hot spots,travel rules and patterns of urban residents.