蔡鉴明

高级实验师 硕士生导师

所在单位:交通运输工程学院

学历:研究生(博士)毕业

性别:男

联系方式:jmcai@csu.edu.cn

学位:博士学位

在职信息:在职

毕业院校:中南大学

   
当前位置: 中文主页 >> 论文成果

System Dynamics Modeling for a Public–Private Partnership Program to Promote Bicycle–Metro Integration Based on Evolutionary Game

发布时间:2021-05-29

点击次数:

DOI码:10.1177/03611981211012425

所属单位:中南大学交通运输工程学院

发表刊物:Transportation Research Record

摘要:A marriage between dockless bike-sharing systems and rail transit presents new opportunities for sustainable transportation in Chinese cities. However, how to promote the bicycle–metro integration mode remains largely unstudied. This paper designs a public–private partnership program to promote bicycle–metro integration. We consider the cooperation between bike-sharing companies and rail transit companies to improve both services and attract long-distance travelers to choose the bicycle–metro integration mode, with government subsidies. To analyze the proportion of each population participating in this public–private partnership program, we establish an evolutionary game model considering bike-sharing companies, rail transit companies, and long-distance travelers, and obtain eight scenarios of equilibriums and corresponding stable conditions. To prove the evolutionary game analysis, we construct a system dynamics simulation model and confirm that the public–private partnership project can be achieved in reality. We discuss key parameters that affect the final stable state through sensitivity analysis. The results demonstrate that by reasonably adjusting the values of parameters, each equilibrium can be changed into an optimal evolutionary stable strategy. This study can provide useful policy implications and operational recommendations for government agencies, bike-sharing companies, and transit authorities to promote bicycle–metro integration.

第一作者:Jianming Cai

论文类型:期刊论文

通讯作者:Yue Liang

学科门类:工学

一级学科:交通运输工程

文献类型:J

卷号:2675

期号:10

页面范围:689–710

是否译文:

发表时间:2021-05-29

收录刊物:SCI

发布期刊链接:https://journals.sagepub.com/eprint/Y9TRJBEZWVRAMGUWJDUE/full

下一条: Collaborative Optimization of Storage Location Assignment and Path Planning in Robotic Mobile Fulfillment Systems