关键词: 城市交通, 碳税, 票价优化, 粒子群算法, 定制公交, 结构方程, 弹性客流需求

Abstract:

To study the influence of carbon tax on the relation between residents' commuting travel choices and social welfare in the process of optimizing customized bus fares for commuter corridors, a two-tier planning model that considers the flexible passenger flow demand and overall social welfare of corridors is established. The upper layer of the model decides the departure location and customized bus fare, and the lower layer is the flexible demand passenger flow allocation model, considering both customized bus and private carbon the commuter corridor. From the perspective of residents' travel satisfaction, the relationship between random passenger flow demand and ticket price was analyzed in the context of carbon tax. According to different passenger departure points, the passenger flow demand is refined as the input of the passenger flow allocation model of the lower elastic demand. Considering the relationship among the passenger flow demand, road congestion, passenger satisfaction, and social welfare, the welfare of corridor passenger transportation system is set as the optimization goal of the upper model. The measurement statistical analysis and particle swarm algorithm are used to solve the two-layer programming model. The calculation results show that the optimized social welfare is considerably improved, the road traffic conditions are significantly improved, and the progressive carbon tax shows positive effect on increasing the sharing rate of customized buses. Under the carbon tax setting, the optimized customized bus fares and departure locations can serve social welfare and reduce the operating costs of urban passenger transportation systems.

Key words: urban transportation, carbon tax, rare optimization, particle swarm algorithm, customized buses, structural equations, elastic passenger flow demand