Zhu, L.; Zhou, R.; Li, X.; Zhang, L. An Evolutionary Game Analysis of Shared Private Charging Pile Behavior in Low-Carbon Urban Traffic. Sustainability2023, 15, 10149.
Zhu, L.; Zhou, R.; Li, X.; Zhang, L. An Evolutionary Game Analysis of Shared Private Charging Pile Behavior in Low-Carbon Urban Traffic. Sustainability 2023, 15, 10149.
Zhu, L.; Zhou, R.; Li, X.; Zhang, L. An Evolutionary Game Analysis of Shared Private Charging Pile Behavior in Low-Carbon Urban Traffic. Sustainability2023, 15, 10149.
Zhu, L.; Zhou, R.; Li, X.; Zhang, L. An Evolutionary Game Analysis of Shared Private Charging Pile Behavior in Low-Carbon Urban Traffic. Sustainability 2023, 15, 10149.
Abstract
Choosing new energy vehicles for travel, especially electric vehicles, is an important component of building a low-carbon urban transportation system. However, the charging need of electric vehicle users is still constrained by the unreasonable layout and insufficient supply of public charging piles in the city. Private charging pile sharing as an alternative policy tool can play a very good role in solving this problem. But it needs decision-makers in urban transportation to take corresponding measures to promote. This paper constructs an evolutionary game model to study the decision behavior of participants in private piles sharing platform. Through numerical simulation analysis, it is found that under most parameter conditions, the government tends to establish a shared charging pile platform based on public interests. Private charging pile owners are influenced by the relationship between the cost of supply modification and revenue, and they tend to join the shared platform when they expect to recover the modification cost. The research conclusions of this paper will provide support for exploring how participants make decisions to maximize overall benefits in the development of low-carbon urban transportation.
Engineering, Transportation Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
