Analysis Method of Travel Mode Choice of Urban Residents Based on Spatial-temporal Heterogeneity

Abstract

Green travel, low-carbon travel, harmonious and livable have become the main objectives of urban development. Public transport-oriented urban development mode can effectively alleviate traffic congestion, reduce energy consumption, reduce environmental pollution. Considering the influence of spatial-temporal heterogeneity on the choice of urban residents' travel modes, a cross-classification selection model is constructed based on hierarchical modeling theory to capture the spatial-temporal heterogeneity quantitatively. Bayesian estimation method is selected to estimate the model parameters, and then the influencing factors of urban residents' travel mode choice behavior are revealed. Combining with typical cases, this paper compares and analyzes the differences between the results of the model analysis under the two scenarios of neglecting spatial-temporal heterogeneity and considering spatial-temporal heterogeneity, so as to provide a scientific basis for public transport-oriented urban planning.