Lonardi Alessandro, De Bacco Caterina
Max Planck Institute for Intelligent Systems, Cyber Valley, Tübingen 72076, Germany.
Phys Rev Lett. 2023 Dec 29;131(26):267401. doi: 10.1103/PhysRevLett.131.267401.
Global infrastructure robustness and local transport efficiency are critical requirements for transportation networks. However, since passengers often travel greedily to maximize their own benefit and trigger traffic jams, overall transportation performance can be heavily disrupted. We develop adaptation rules that leverage optimal transport theory to effectively route passengers along their shortest paths while also strategically tuning edge weights to optimize traffic. As a result, we enforce both global and local optimality of transport. We prove the efficacy of our approach on synthetic networks and on real data. Our findings on the international European highways suggest that thoughtfully devised routing schemes might help to lower car-produced carbon emissions.
全球基础设施的稳健性和本地运输效率是交通网络的关键要求。然而，由于乘客往往贪婪地出行以最大化自身利益并引发交通拥堵，整体运输性能可能会受到严重干扰。我们开发了适应规则，利用最优运输理论有效地将乘客沿着最短路径引导，同时还策略性地调整边权重以优化交通。结果，我们实现了运输的全局和局部最优。我们在合成网络和真实数据上证明了我们方法的有效性。我们在欧洲国际高速公路上的研究结果表明，精心设计的路由方案可能有助于降低汽车产生的碳排放。
