低碳排放约束下城市多方式交通网络道路收费研究  

Study on Road Pricing for Urban Multi-modal Transport Network with Low Carbon Emission Constraints

作　　者：张鑫 李佳杰[2] 俞灏[3] 刘攀[3] ZHANG Xin;LI Jia-jie;YU Hao;LIU Pan(Government Service Center of Beijing Municipal Transport Commission(Beijing Boats Inspection Center),Beijing 100161,China;School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,China;School of Transportation,Southeast University,Nanjing Jiangsu 210096,China)

机构地区：[1]北京市交通委员会政务服务中心(北京市船舶检验所),北京100161 [2]北京交通大学交通运输学院,北京100044 [3]东南大学交通学院,江苏南京210096

出　　处：《公路交通科技》2022年第5期131-139,共9页Journal of Highway and Transportation Research and Development

基　　金：国家自然科学基金项目(51561135003)。

摘　　要：为控制和降低城市交通碳排放,研究了低碳排放约束下的城市多方式交通网络道路收费问题。以私家车、常规公交和地铁组成的多方式交通网络为研究对象,以CO_(2)预期减排量和CO环境容量为约束,建立了最小化CO_(2)排放总量和用户出行总时间的双目标道路收费模型。模型采用基于博弈论的双层优化方法刻画决策者和出行者间的领导-跟随关系,上层为决策者在低碳排放约束下制定道路收费方案以权衡双目标,下层为出行者根据收费措施做出交通方式及路径选择。运用变分不等式描述了交通方式间的不对称影响及出行者的出行行为。针对所构建的非线性双目标道路收费模型,设计了改进型非支配排序遗传算法进行求解。算例结果表明:道路收费措施可有效地调节各种交通方式的出行比例,使得私家车出行者转移至公共交通(常规公交和地铁),从而缓解路网拥堵且达到低碳减排的目标;相比于道路收费前的初始状态,收费措施可至少提升43%的公共交通出行量,且使CO_(2)减排量达到32%以上;Pareto前沿验证了2个目标之间的负相关关系,若不增加初始状态的出行总时间,路网能够达到的最大减排比例为32%~59%;若欲达到高于60%的CO_(2)预期减排目标,需提高公共交通的供给水平,减少由私家车转移至公共交通的时间损失,提高系统的运输效率。In order to control and reduce the carbon emission of urban transport,the road tolls for urban multi-modal transport network under the constraint of low carbon emission is studied.Taking the multi-modal transport network composed of private cars,conventional buses and subways as the research object,and with the expected CO_(2) emission reduction and CO environmental capacity as constraints,a bi-objective road pricing model that minimizes the total CO_(2) emissions and the total travel time of users is established.The model uses a 2-layer optimization method based on game theory to describe the leader-follower relationship between decision makers and travelers.The upper layer is the decision makers to formulate road pricing scheme under the constraints of low carbon emissions to balance the dual goals,and the lower layer is the travelers to make traffic mode and route choices according to the pricing measures.The asymmetric influence of transport modes and travel behaviors are analyzed by variational inequality.The NSGA-Ⅱis designed to solve the proposed nonlinear bi-objective road pricing model.The result of the numerical examples shows that(1)road pricing measures can effectively adjust the travel proportion of various transport modes,so that private car travelers will transfer to public transport(regular buses and subways),thereby alleviating road network congestion and reducing low carbon emission;(2)compared with the initial state before road pricing,the volume of public transport is increased by 43%at least,and carbon emissions is decreased more than 32%;(3)the result of Pareto front demonstrated the negative correlation of the 2 objectives,so that the maximum ratio of emission reduction is 32%-59%without increasing the total travel time;(4)to achieve the expected CO_(2) emission reduction by more than 60%,it is necessary to increase the supply level of public transport,reduce the time loss of transferring from private cars to public transport,and improve the transport efficiency of the system.

关 键 词：城市交通 道路收费 双目标优化 多方式交通网络 碳减排 改进型非支配排序遗传算法 

分 类 号：U491.2[交通运输工程—交通运输规划与管理]