Research On Trip Mode Choice Based Fuzzy Reasoning Model

Urban trip mode structure is an important indicator, which measure a citytraffic is reasonable allocation of resources, it is also an important basis fordeveloping traffic management policies and making transportation facilitiesdecision-making. Traditional trip mode choice model use linear relationship toexpress the relationship between factors which effecting the travelers’ choice withgeneralized cost of various modes of transportation, it is too simple, and there aresome limitations in reflecting the characteristics of trip mode.This paper studied the advantages and disadvantages of aggregate model anddisaggregate mode, summed up the development law of the traffic demandstructural model, analyzed the selection process for urban residents to trip, pointedout that the selection process for travelers to trip should be a qualitativedecision-making process, factors for an individual traveler is fuzzy, there is noinevitable relationship between the influencing factors and the decision, so it is notappropriate to do research on the selection process for travelers to trip useddeterministic mathematics. Paper used fuzzy mathematics to do research, whichcan more rational reflect travelers’ selection process, conform travelers’ regular.This paper do a study on model structure, the generalized cost function`s form,parameter calibration and testing. Based on the depth analysis of citizen’ tripcharacteristics, in order to reflect fuzzy concept about factors, handed the factorsfuzzy, in order to reflect citizen’ trip mode choice decision-making process, withanalyzing the key influencing factors, developed fuzzy rules, and then constructedgeneralized cost function, substituted logit model finally, fuzzy reasoning basedtrip mode choice model which include unknown parameters is constructed.Considering that established model belongs to the large-scale characteristics ofnonlinear equations, this paper find the optimal solution of unknown parametersusing genetic algorithms (selection, crossover and mutation) instead of thetraditional method of maximum likelihood estimation, that is programmed withMATLAB; parameters which is calibrated are tested with hit rate method. Testingresults is fed back to model construction and parameter calibration section, whichis used to refine the model and parameters; applied fuzzy reasoning based tripmode choice model used rail and private car trip sample data of Dalian Jinzhou,and make a sensitivity analysis on the influencing factors, further validate theapplicability of the mode.