Research On The Optimization Of Urban Passenger Transport Structure Under The Background Of "Carbon Peak"

In recent years,with the continuous expansion of the urban scale,more and more residents move to the urban center,and the motor vehicle ownership also shows an increasing trend year by year,which will inevitably make the urban traffic congestion problem increasingly serious,urban traffic carbon emissions are increasing day by day,so the urban passenger traffic structure optimization research,in order to achieve the goal of "carbon peak" as soon as possible.This paper first expounds the relevant concepts of "peaking carbon" in transportation and the calculation methods of carbon emissions,analyzes the structural composition of urban passenger transportation and its optimization methods,and establishes a carbon emission prediction model based on the calculation of carbon emissions of urban passenger transportation.According to the prediction results,it can determine whether the carbon emissions of the city have reached a peak.If the peak of carbon emissions does not occur,the structure optimization is carried out with 2030 as the planning year,and a traffic structure optimization model is constructed with the objective function of the minimum carbon emissions of transportation in the planning year,the lowest generalized travel cost and the maximum total efficiency of passenger transportation.Taking residents’ travel demand,urban road resources,transportation energy consumption,the development scale of various transportation modes,and urban residents’ travel accessibility as constraint conditions,the multi-objective traffic structure optimization model is established,and the priority method and genetic algorithm are respectively used to solve the optimization model by using lingo and matlab software.Finally,taking a city as an example,the "bottom-up" method based on mileage was used to calculate the carbon emissions of passenger transport in the city,and the improved metabolism GM(1,1)model was used to predict the carbon emissions of passenger transport in the city.The results showed that the peak had not been achieved before 2030.Based on the obtained carbon emission data and existing reference data,Taking 2030 as the planning year,a structural optimization model was established to optimize the city,and the results showed that the total carbon emission after optimization was reduced by about 270,000 tons compared with that before optimization.Three emission reduction scenarios were assumed according to the proportion of various passenger transportation modes in the model solution results to implement car driving restriction and adjust the transportation energy structure.The results show that these two measures are of great significance to promote low-carbon emission reduction in cities and accelerate the process of realizing the goal of "carbon peak" in urban transportation.The results show that the improved metabolism GM(1,1)prediction model has high prediction accuracy for urban passenger transport carbon emissions,and the established traffic structure optimization model provides theoretical reference and practical guidance for urban optimization reform to achieve the goal of "carbon peak" in the field of transportation.