Abstract: : To better describe the effect of the traveler and parking space owner' strategies on the matching results of shared parking spaces, this paper develops an evolutionary game model with traveler and parking space owner involved and further analyzes the evolutionary stable state. The effects of different benefits, costs, and strategies on shared parking are illustrated by simulation analysis. The results show that both the traveler and the parking space owner can evolve to a stable equilibrium state through continuous learning, but the rate of evolution and the volatility of evolution are restricted by the benefits of both parties. The analysis also shows that a high initial ratio is needed to evolve to an ideal state. Both travelers and parking space owners can be encouraged to use shared parking by increasing revenue and reducing costs. At the same time, when the initial proportion is high, the proportion of income distribution also has great impact on the evolution process. It is found that the government incentive policy promotes the development of shared parking when the sharing platform provides reasonable revenue and expenditure.

Key words: urban traffic, shared parking, evolutionary game, replicator dynamics, evolutionary stability analysis

摘要： 为研究在政府鼓励措施下出行者和车位拥有者参与共享停车时的策略对共享停车匹配结果的影响，建立出行者和车位拥有者演化博弈模型并进行演化稳定状态分析，结合仿真说明不同收益和成本及策略选择对共享停车的影响。研究结果表明：在政府鼓励措施下双方演化博弈中出行者和车位拥有者均能通过不断学习最终演化至稳定均衡状态，但演化速率和演化波动性受双方收益制约；通过分析发现，想要演化至(使用，共享)状态则需要较高初始比例，可以通过提高收益和减少成本等措施诱导出行者和车位拥有者使用共享停车，同时在初始比例较高时收益分配比例对演化过程也有较大影响。研究发现，当共享平台给出合理收益和支出费用时，政府鼓励 政策对共享停车发展起促进作用。

关键词: 城市交通, 共享停车, 演化博弈, 复制者动态, 演化稳定性