The Transfer Volume Forecasting On Integrated Passenger Transportation Hub

Integrated Passenger Transportation Hub assembles a variety of ways, is an importantnode for realizing transport integration, and is the bridge of achieving convergence wellfrom point to plane by the various modes. With the rapid development of urban economy,trips of residents has constantly increased, which brings certain negative effects to the hub,such as operational efficiency low, transfer inconvenience, passengers crowded and otherissues. While predicting the transfer volume within the hub scientifically is the basiccondition to solve these problems, and is the foundation for the layout of hub internalfacilities and the operations scheduler of various ways, based on this, rationally adjust tothe scheduling of a variety of ways, In order to improve the coordination between the hubinternal ways, to improve the efficiency of passenger evacuation, to reduce the duration ofstay of visitors within the hub, and to reduce the cost of passenger travel, at the same timepromote the hub operation efficient highly, to achieve seamless transfer.Based on the study status of domestic and foreign, explore the various functions of thehub from the passenger transfer environment In this paper, at the same time positioninganalysis of the hub with the method of combining macro and micro, combining global andlocal, to determine the transfer convergence function in the inner city traffic and externaltraffic which Is the focus of this study. Analysis the transfer types and transfer modeswithin the hub on this basis. In addition, prediction of the transfer volume should be withina reasonable range, From the objective and subjective angle analysis the transfer influencesphere of hub, from the environmental of the hub objectively, The transfer affect scope islimited by the constituent elements of the transfer system, and the boundary conditions ofthe hub; subjectively departure from the passenger’s point of view，it is necessary toanalysis the generated and attracted area of passengers in the hub to research transferaffected areas, that is "reasonable zone". In the next section starting from the passengerindividual, analyze the decision-making mechanism of transfer behavior to the passengerswithin the hub. First analyze the arrival temporal characteristics and departure timecharacteristics of the various modes and the passengers at the hub. Followed studying thetransfer behavior of the passengers from a new perspective of the theory of plannedbehavior, and analyze systematically from the macro, meso and microscopic levels. Withfactor analysis to research transfer influencing factors and solving factor score. Combinedwith the logistic method to determine the mechanism of action of various factors on thedifferent ways, and determine influence degree of various factors on the different ways.Establish transfer sharing rate and transfer volume forecasting models, first of all determinethe transfer amount forecast ideas, explore the transfer prediction methods of different hub,analysis the difference of the prediction methods of completion before and after the completion for hub, Analyze and compare the existing models of transfer amountprediction, apply the multinomial Logit model of disaggregate method to establish thetransfer volume prediction model, establish the two cross transfer probability model of thedifferent ways within hub, and make the passengers disaggregation, predict the amount ofthe transfer between the different ways within the hub.Finally, to analyze the Liaoyang City Integrated Passengers Transportation Hub as aexample. In the first place introduce the basic situation of the hub, and make a location tothe transfer modes of the hub. Based on this, select the characteristic variables inaccordance with the decision-making mechanism of transfer behavior. Establishing theshare rate model of two cross transfer between the different ways, make the parametercalibration with SPSS software，forecast the ride-sharing rate between the dominant modesand auxiliary modes of the different times. Predict the transfer volume for different timesbetween the dominant modes and auxiliary modes, according to passenger volume of thedominant ways in the hub.