Research On Framework Of Resident Trip Survey Checking System Based On Multi-Source Big Data

With the background of Reform and Opening Up continued,the large and medium sized cities across the country are at a high speed of development to the planning and construction of urban transportation infrastructure.Meanwhile,with the rise of emerging traffic tools such as Urban Rail Transit,Car-hailing Service and Bicycle-Sharing,the travel behavior of urban residents increasingly diversified.Under this trend,We need accurate,efficient and comprehensive urban comprehensive traffic survey data basis and theoretical support for theplanning and construction of city road network,urban rail transit and other traffic systems.Traditional urban residents travel survey,during survey design,implementation phases,data quality and various aspects seems difficult to achieve the comprehensive and perfection.The rise of urban traffic big data technology brings new ideas and reliable data source,make it possible for the parameter of the traffic which can not be accurately measured in the past.Firstly,this paper studied the data structure of traffic data,and take actions such as data cleaning,data integration and data format transform for the problem of unknown data definition,data redundancy and information incomplete and other defects.Put forward method for obtaining the trip survey statistical parameters based on traffic big data.On this basis,the research of traditional research methods,including traffic district division,the sampling rate determination and expansion methods.After the analysis of multi-stage error resource,and put forward new ideas in the framework of resident trip survey checking system.Through the research of this paper,use the current traffic big data technology to improved the framework of resident trip survey checking system efficiently,which is significant to the development of the urban transportation infrastructure planning and construction...