The Research Of Passenger Flow Influence Factors Analysis And Macro Forecast Model Of BRT

With the rapid development of China's economy, the sharp increase in carownership, and a serious shortage of road capacity, and brought such as trafficcongestion, environmental pollution, traffic accidents and a series of trafficproblems. To develop public transport, private car travel diversion is an inevitabledevelopment trend of urban transport systems. Rail transit construction generallyhuge investment, long construction period, in a short time is difficult to work.Therefore, rapid transit system has been widespread concern, bus rapid transit (BRT)as an improved capacity utilization of buses and modern intelligent transportationtechnology, running on a dedicated bus lane, both characteristics similar to railtransport operation, but also have the flexibility of ordinary buses, an economy'sconvenient, safe, comfortable, punctual public transport operator service. In order todetermine the scientific and rational planning of BRT systems or building programs,rapid transit traffic forecast is very important. Only according to reliable rapidtransit traffic forecast data to make accurate judgments and decisions on importantissues BRT planning or construction stage, to address key issues such as the size ofthe construction project, operational economic evaluation, risk assessment and otherfactors.Rapid transit traffic to analyze the factors which affect the specific articlefrom the five aspects of12technical factors influencing factors, social factors,economic factors, policy factors, and factors such as starting travelers, drawn byLogistic regression model the impact of rapid transit passenger the key factor.In this paper, five technical factors, social factors, economic factors, policyfactors and traveler factors, analyzes the influencing factors of rapid transit trafficthrough the construction of the structural model to explain, analyze hierarchicalrelationships drawn between the various factors, and thus science quick guide morepeople choose bus travel, reduce urban traffic congestion; chapter describes therapid transit traffic prediction method, and then propose a two-stage rapid transittraffic forecasting model.Firstly, according to the actual situation partial least squares regression methodto predict traffic. According rapid transit passenger factors identified, in line withmacro-control, the principle is simple and easy to operate, to the gray hair has beenthe key factors influencing the rapid transit passenger, and then build a macro usingregression analysis to predict the total traffic BRT model by model parametercalibration and validation model, and so on urban rapid transit traffic can have amacro grasp.In determining the total passenger bus rapid transit on the basis by considering the nature of urban land use, land-use intensity, land use characteristics to attractpassenger layout generated macro-forecasting model based on land-use passengerbus rapid transit lines. After attracting different characteristic function of land tobuild on land to attract different coefficients determined to build a passenger linemacro forecast models.Harbin urban rapid transit planning for the case, the first rapid transit passengerflow forecasting total demand, reuse model passenger bus rapid transit line macroforecasts.