双模式下考虑碳税的定制公交站点位置与票价优化研究

Optimization study on customized bus stop location and fare considering carbon tax

为研究碳税设定下通勤廊道定制公交票价优化过程中居民通勤出行选择与社会福利之间的影响关系,建立了兼顾弹性客流需求和廊道整体社会福利的双层规划模型。模型上层决策为发车位置和定制公交票价,下层为弹性需求客流分配模型,考虑通勤廊道上的定制公交和私家车两种交通方式。从居民出行满意度的角度,对比考虑碳税的环境下,分析客流需求与票价之间的关系;根据乘客出发点的不同将客流需求分层,作为下层弹性需求客流分配模型的输入;考虑客流需求、道路拥堵状况、乘客满意度与社会福利间的关系,设置廊道客运交通系统福利为上层模型优化目标;采用测量分析系统与粒子群算法求解双层规划模型。实例计算结果表明,优化后的社会福利得到较大提升,同时道路通行状况得到明显改善,累进碳税对于提升定制公交分担率的效果较好。由此可见,在碳税设定下,优化后的定制公交票价和发车位置能更好地提高社会福利,降低城市客运交通系统运行成本。

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.