Research On The Methods Of Analysing Transit Trip Chain Multisource Data Based On APTs

Advanced Public Transportation Systems integrate advanced technology of modern communication, information, computer, electronic control, etc. Its charge, scheduling, monitoring system has accumulated massive data. How to excavate the massive APTS data to analyse the hidden and potential operation rules in public transportation has important significance for improving the city public transportation system planning and management level. Application of APTS data to relace the traditional travel survey data need to establish and analyse the transit trip chain model. The complete bus passengers' travel information is needed to analyse bus passengers' travel behavior at the micro level and analyse the public transit demand at the macro level.However, parts of bus passengers' alighting stop cannot be estimated become the key factor of application of APTS data.This paper combines the “commuting model” and “travel model” to estimate bus passengers' alighting stop who brush only once one day through the analysis of bus passenger travel rules. The paper proposes “commute model” to estimate the commuters' alighting stop who brush only once one day based on the existing research which can estimate the residence location and work location. The paper matches bus passengers' different trips when using “travel model” to estimate the alighting stop. The proposed two methods are programmed with real data and the accuracy of the methods are estimated by using Visual Basic.The paper puts forward the concept of transit trip chain from the angle of trip chain and then adopt the comprehensive integrated judgment method of estimating the alighting stop to solve the restricting factors of establishing the transit trip chain. The paper utlizes the data and the existing research to identify a city's bus passengers' boarding stops, transfer stops. The paper adopt the snowflake model design based on transit trip chain's multisource data based on APTS to establish a data warehouse. Then the paper gets bus passengers' complete transit trip information and utilize the expression method of spatial-temporal path to establish the transit trip chain model. The paper analyses the transit trip chain data from different granularity and dimensions at the micro level and at the macro level.The paper analyses the transit trip chain and compare different transit trip chains at the micro level. Finally the paper analyses the public transportation's characteristics index from the overall characteristics, tempal characteristics, spatial characteristics at the macro level.