| The imbalance between the supply and demand of urban road resources and the growth of private cars has led to increasingly severe urban traffic congestion,resulting in a large amount of noise and exhaust pollution.In order to improve the implementation effect of traffic demand management,it is first necessary to study an effective travel demand prediction model.Different modes of urban transportation system need to be efficiently connected and coherent in order to enhance the overall competitiveness and efficiency of the transportation system.As a connection place between different modes of transportation,the supply level of pedestrian environment affects the choice of residents’ travel mode to a certain extent.Therefore,in order to improve the accuracy of prediction of urban residents’ travel characteristics and travel mode choices,it is necessary to consider the influence of walking environment,and the prediction results of the model can help relevant departments formulate policies and measures to optimize the structure of transportation demand.Based on the subjectobject observation of pedestrian environment,this paper explores the influence mechanism of pedestrian environment on travel behavior,and establishes a mixed selection model of urban transportation mode considering pedestrian environment,the main contents are as follows:1 、 Sort out and analyze relevant basic theories.This thesis elaborates the modeling foundations of social ecology theory,Maslow’s hierarchy of needs,planned behavior theory,value-belief-norm theory,stochastic utility theory,and structural equation model.Firstly,the influence mechanism of pedestrian environment on travel mode selection behavior and the decision-making process of travel mode selection were analyzed,and secondly,the personal social attributes,travel characteristics,psychology and walking environment factors affecting travel mode selection behavior were analyzed.2、Model the impact of the pedestrian environment on travel intent.Firstly,based on TPB and VBN theory,the equation model of travel intention structure is constructed,and nine latent variables including walking environment are selected according to the existing research,the relationship between the latent variables is hypothetical zed,and the measurement method of the latent variables is elaborated.The influence model of pedestrian environment on travel intention was constructed,and the AMOS software was used to evaluate the model through test indicators,and the latent variable factors that had an important impact on residents’ travel mode choice were analyzed,which laid the foundation for the construction of a hybrid travel mode selection model later.3、Build a hybrid choice model of travel modes that considers the pedestrian environment.Based on the stochastic utility theory,according to the analysis structure of the travel intention model and the existing research,three types of characteristic variables are selected to construct a mixed choice model of travel mode considering the environmental impact of walking.According to the model,the utility function of each mode of transportation is determined,and the model parameters are calibrated,solved,tested and analyzed by Stata software.4、Empirical analysis.Through offline and online questionnaires,the research data of travelers in the central urban area of Chongqing were collected,and the model was solved on the basis of the data.The results show that there are direct and indirect effects of pedestrian environment on public transport,light rail,car and walking travel intention,and the indirect effects of bus and walking have two paths: walking environment-behavioral attitude-travel intention,walking environment-subjective normtravel intention;There is only one indirect impact path of pedestrian environment on light rail and cars: pedestrian environment-behavioral attitude-travel intention;The influence of pedestrian environment on each travel intention was walking(0.665),bus(0.663),light rail(0.384)and car(0.304)in descending order.The goodness ratio of SEM-MNL model after considering the latent variables was improved from 0.2752 to0.4544,which was significantly better than that of the MNL model without latent variables,and the calibrated parameters showed that the latent variables of the pedestrian environment had a significant positive impact on the selection probability of bus,light rail and pedestrian travel,indicating that it was feasible to improve the selection probability of transit,light rail and walking travel by improving the pedestrian environment.Taking the car as the reference item,from the perspective of odds ratio,the pedestrian environment had the greatest influence on the selection probability of walking travel(10.751),followed by bus(8.373)and light rail(5.652).Based on the above research,based on the calibration results of model parameters,strategic suggestions are proposed for different modes of transportation. |
PDF Full Text Request