| As the core part of public transportation passengers,the accurate grasp of their activitytrip characteristics is conducive to understanding the relationship between public transportation system and urban activity space,and improving the attractiveness of public transportation and residents’ living quality.Recently,with of the increasingly abundant public transportation smart card data,POI data,activity transaction data,as well as the gradual popularization of machine learning and geographic information technology,the basic conditions have been met to research the rules of activity trip from the perspective of individual coummuters.However,there is still a lack of systematic and in-depth research on how to integrate these multi-source data,extract the activity-trip characteristic indexes of urban public transportation commuters and complete with multi-angle analysis.Taking public transportation commuters as the research object,this paper aims to extract trip information from multi-source data such as public transportation smart card data and activity transaction data,and reveal the activity-trip characteristics of public transportation commuters through commuter identification,activity-trip chain construction and activity-trip characteristic index extraction.On the basis of grasping the characteristics of dynamic and static data of public transportation,this paper makes clear the composition of public transportation trip information,and proposes a multi-source data processing method covering preprocessing,time-space recognition of transfer behavior and operation of trip identification.For the trip records of public transportation,an identification method of public transportation commuters based on spatiotemporal clustering and traditional index screening is proposed.Then,this paper puts forward an activity-trip chain construction method based on trip data and activity transaction data,and from the perspective of daily activities and commuter trip characteristics,builds the public transportation commuter activity-trip characteristic index system.Finally,this paper reveals the activity-trip characteristics of public transportation commuters from the perspectives of characteristic indexes,feature differences under different types of residence and workplace,and the analysis of the correlation with the built environment,so as to put forward optimization suggestions for the infrastructure construction environment and public transportation service.The research results can provide data processing and method basis for the acquisition of spatial-temporal activity-trip characteristics of public transportation commuters,and provide reference and decision support for the optimization of application scenarios associated with characteristics. |
