Sample Expansion Model of Household Travel Survey Using Cellphone Data

Abstract:

In this paper， the causes of errors in household travel surveys were analyzed， the traditional weighted sample expansion model was introduced， and its limitations， especially the lack of unreported trip records were analyzed. Combining the advantages and characteristics of the research method using cellphone data on travel behaviors， a novel model of using cellphone data to expand the sample of household travel surveys and mining unreported trip records was proposed. A sample expansion model was designed including five steps， combining the household travel survey data， traffic operation monitoring data， and cellphone data. Based on the stationary point classification technology， a travel behavior distribution model based on cellphone data was established. The parameters of the model split model were calibrated based on the revealed preference data of household travel surveys. The difference between the results of the survey sample， the traditional weighted sample expansion model， and the proposed model was analyzed from the aspects of travel purpose composition， time of day， and travel distance distribution. The results show that the model proposed reveals the unreported trip record caused by false reports and omissions.