Urban low carbon transportation travel mode selection method based on Bayesian DSGE model

Due to the problems of low emission reduction contribution rate, large carbon emissions and low accuracy of selection results after applying the traditional low-carbon transportation travel mode selection method, an urban low-carbon transportation travel mode selection method based on Bayesian DSGE model is proposed. Firstly, the index system of low-carbon transportation travel mode selection is constructed, and the weight of principal component index is calculated. Secondly, the DSGE model is used to establish the optimal behavior equation of actors, and the urban low-carbon transportation travel mode selection model is constructed. Finally, combined with Bayesian method, the model parameters are estimated to obtain the optimal solution of the model, that is, the optimal low-carbon travel mode. The simulation results show that the contribution rate of emission reduction is high, the carbon emission is less, and the selection results of travel mode are consistent with the expert results.