Study On The Combined Multi-Mode Split And Trip Assignment Model

Traditional four-stage method divides traffic requirement forecasting into four stages. At present each model that every stage developed, generally include variables of the level of service, especially in the stages of model split and traffic assignment. Because going on stage by stage, variables are inconsistent in different stages. Some scholars have studied the combined model to solve this problem, but these studies dealt with two traffic modes (generally abut modes of subway and car). There are many traffic modes in our country, especially urban traffic system, such as subway, regular public transit, taxi, car, bicycle and so on. Therefore, study on multi-mode combined model is necessary.This paper takes the multi-mode combined model as the core, and the other contents process around this core. This article studies the model split firstly, then takes Beijing as the example, establishes the RP data models, the SP data model and the fusion data model, and it carries on the analysis of model sensitivity. The results indicate: because of the attributes correlation and the limitation of attribute levels, the RP data model the parameter of expense estimated value mark and actually not symbol; The SP data model precision is high, but some t Test values of the parameters are not very remarkable; The t Test values of the parameters in fusion data model parameter are remarkable, the model elasticity is small, the sensitivity is deactivated.Based on the former studies of the network balance, this paper proposes the concept of the multi-mode network balance: many traffic modes run on a traffic network under the designated OD matrix, travelers are unable to obtain smaller generalized cost by changing traffic modes or trip routes, this state reaches the multi-mode network balance. Then this paper formulates a classification method of traffic modes, which accords to relation that different traffic modes affect mutually while moving. Based on that classification of various traffic modes, this test proposes a combined modal split and trip distribution model of multinomial modes. And the corresponding identification and algorithm are provided. In the algorithm, this paper proposes using...