In this paper, we study how to alleviate highway traffic congestion by encouraging plug-in hybrid and electric vehicles to stop at a charging station around peak congestion times. Specifically, we design a pricing policy to make the charging price dynamic and dependent on the traffic congestion, predicted via the cell transmission model, and the availability of charging spots. Furthermore, we develop a novel framework to model how this policy affects the drivers' decisions by formulating a mixed-integer potential game. Technically, we introduce the concept of "road-to-station" (r2s) and "station-to-road" (s2r) flows, and show that the selfish actions of the drivers converge to charging schedules that are individually optimal in the sense of Nash. In the second part of this work, submitted as a separate paper (Part II: Case Study), we validate the proposed strategy on a simulated highway stretch between The Hague and Rotterdam, in The Netherlands.

中文翻译：

---

通过智能电动交通进行公路交通控制-第一部分：理论

在本文中，我们研究了如何通过鼓励插电式混合动力和电动汽车在交通拥堵高峰时段停在充电站来缓解高速公路交通拥堵。具体来说，我们设计了一种定价策略，以使充电价格动态变化，并取决于通过小区传输模型预测的交通拥堵情况和充电地点的可用性。此外，我们开发了一个新颖的框架，通过制定混合整数潜在博弈模型来模拟该政策如何影响驾驶员的决策。从技术上讲，我们介绍了“公路到车站”（r2s）和“车站到公路”（s2r）流量的概念，并显示了驾驶员的自私行为会收敛到从某种意义上说是最佳的充电时间表纳什 在这项工作的第二部分，作为单独的论文提交（第二部分：