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作 者:付晓 金瑜倩 刘志远[1] 吴建军[2] FU Xiao;JIN Yuqian;LIU Zhiyuan;WU Jianjun(School of Transportation,Southeast University,Nanjing 211189,China;State Key Laboratory of Rail Traffic Control and Safety,Beijing Jiaotong University,Beijing 100044,China)
机构地区:[1]东南大学交通学院,南京211189 [2]北京交通大学轨道交通控制与安全国家重点实验室,北京100044
出 处:《系统工程理论与实践》2023年第6期1782-1797,共16页Systems Engineering-Theory & Practice
基 金:国家自然科学基金(42261144745,72288101);教育部人文社会科学研究青年基金(21YJC790030);轨道交通控制与安全国家重点实验室(北京交通大学)开放课题基金(RCS2021K002)。
摘 要:碳排放引发的可持续发展问题引起了全球的广泛重视,在碳中和背景下,城市交通领域的低碳发展势在必行.本文充分考虑了政府的主导性和出行者行为,建立双层规划模型描述交通管理者和出行者之间的领导者-跟随者博弈,采用改进的遗传算法,结合连续平均法和路径交换法求解模型,并对不同策略下的出行者活动行为和出行碳排放进行了比较分析.研究结果表明,考虑碳积分收费方案的协同优化策略相较于仅优化公共交通服务的单一策略,能够显著提高社会效益和减少交通系统的碳排放,提出的模型和算法能够有效地求解考虑多方参与者利益的城市交通系统优化问题,为政府评估各种碳排放相关的城市交通可持续发展政策提供了理论依据和科学框架.The sustainable development issues caused by carbon emissions have received global attention.In the context of carbon neutrality,reducing carbon emission in urban transport system is imperative.In this paper,a bi-level programming model is formulated to describe the leader-follower game between transport authority and travelers fully considering behavior of travelers and the dominant characteristic of government.To compare and analyze the activity behavior of travelers and carbon emission under different strategies,a modified genetic algorithm is used to solve the model by combining method of successive algorithm and path swapping method.The results show that the collaborative optimization strategy with carbon credit charging scheme can significantly improve the social benefits and reduce the carbon emissions in transport system compared to a single strategy that only optimizes public transit services.The proposed model and algorithm can effectively solve the optimization problem of urban transport system considering the interests of multiple participants.This paper provides a theoretical framework for government to evaluate various carbon emission-related policies for sustainable urban transport development.
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