Study On The Forecasting Method Of Passenger Flow Walking To And From The Public Transport Station

Walking is the main way of connecting public transportation from and to the station,accounting for more than 70%.Relevant studies have shown that improving the convenience of walking away from the station is conducive to the development of public transportation.The flow from the station provides basic data for estimating the walking flow of the route,which is an important prerequisite for judging whether the walking route is optimized and evaluating the optimization effect.From the three aspects of walking distance to station distance distribution,passenger flow forecasting methods at bus stops,and passenger flow influencing factors,the existing research has limitations.At present,there is a lack of simple and effective methods for predicting passenger flow from walking distance to public transportation stations.It is necessary to qualitatively and quantitatively analyze the influencing factors of the passenger flow from the station on the basis of the status investigation and data collection,and construct a public transportation passenger flow forecast model with the gravity model as the main body.Taking the 39 public transportation stations in the Dalian Xueyuan Plaza-Digital Plaza area as the research object,through field investigation and establishing a buffer model,basic data such as the outgoing flow rate,bus stations,bus lines,and land area are obtained.Based on this,qualitative analysis and quantitative research are combined to determine the main influencing factors of the pedestrian flow from the station,and regression analysis of the correlation between each influencing factor and the passenger flow from the station.In order to obtain the distribution law of walking distance to the station,the distribution texture is analyzed through theoretical derivation,and it is proposed that under the comprehensive influence of the distance scale utility and the distance attenuation utility,the walking distance to the station distance distribution presents a "low high and low" distribution state.Using the open platform of Gaode Maps,we obtained 29920 walking distance data from the Dalian University of Technology area to the Xi’an Road area.Through data processing and regression analysis,the distribution law of walking distance to the station distance was verified and the distance distribution function and distance attenuation function were obtained.On the basis of considering the distance attenuation,through the integration of influence factors and data conversion,the calculation formulas of passenger flow generation P and passenger flow attraction A are respectively obtained.Then regression analysis of the correlation between the PA product of each station and the outbound flow rate,the functional relationship is obtained.This formula is used to predict the outbound flow of 6 bus stations in different regions and different types in Dalian.The comparative analysis of the predicted value and the survey value shows that the obtained outbound passenger flow prediction method and prediction function are reasonable and accurate.In view of the changes in the entrances and exits of residential quarters and the newly constructed residential quarters in the process of urban development,this prediction method is applied to predict the changes in the traffic from the station to the station,and from the three aspects of detailed planning control,station reconstruction and walkto-station path optimization Propose reform measures.Compared with the traditional forecasting method of constructing traffic districts,the forecasting method obtained in this paper simplifies the difficulty of basic data investigation,and can predict the outbound traffic of a single station in a city and a station in a new urban area,which is more applicable.In the detailed urban planning and public transportation special planning,this method can be used to estimate the flow from the station to the station,and provide a basis for the setting of the entrance and exit of the residential area and the layout of the bus station.It provides a data basis for the optimization of the walk-away-to-stop path,the transformation of bus stops,and the dispatch of bus operations in the process of urban development.