用交通均衡模型优化充电桩布局，缓解城市拥堵
Congestion Reduction in EV Charger Placement Using Traffic Equilibrium Models
- 基于拥堵博弈和排队模拟的双模型指导充电桩选址
- 在真实路网中实现接近最优的拥堵缓解效果
- 排队模型更贴近实际，适合交通规划者参考
电动汽车普及若不考虑充电设施对交通的影响，可能加剧拥堵。本文研究如何通过两种均衡模型——基于拥堵博弈和基于原子排队模拟——来战略性部署充电桩以降低拥堵。将两种模型整合进可扩展的贪心选址算法中。实验表明，该算法在真实路网中能取得最优或近似最优的拥堵缓解效果，尽管全局最优性无法保证（反例已验证）。此外，排队模型比拥堵博弈模型更贴近现实，并提出统一方法：从排队仿真中校准拥堵延迟，并在链路空间求解均衡。
原文摘要 · Abstract (English)
Growing EV adoption can worsen traffic conditions if chargers are sited without regard to their impact on congestion. We study how to strategically place EV chargers to reduce congestion using two equilibrium models: one based on congestion games and one based on an atomic queueing simulation. We apply both models within a scalable greedy station-placement algorithm. Experiments show that this greedy scheme yields optimal or near-optimal congestion outcomes in realistic networks, even though global optimality is not guaranteed as we show with a counterexample. We also show that the queueing-based approach yields more realistic results than the congestion-game model, and we present a unified methodology that calibrates congestion delays from queue simulation and solves equilibrium in link-space.
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