一种包含交通灯的城市交通网络Payne-Whitham模型及其在交通优化中的应用
A Payne-Whitham model of urban traffic networks in the presence of traffic lights and its application to traffic optimisation
AI总结：
本文提出了一种扩展的Payne-Whitham模型，用于模拟包含交通灯的城市交通网络，并展示了该模型在交通信号优化中的应用。
摘要：
城市道路运输是影响生活质量与经济活动的重要挑战。解决这些挑战需要多学科方法和可持续的城市规划策略以减轻城市交通的负面影响。本文介绍了一种流行的宏观交通模拟模型Payne-Whitham模型的扩展版本。我们研究了该模型最初设计用于模拟高速公路直线路段交通，如何适应更现实的条件，包括任意道路网络图和多个带有交通信号灯的交叉口。此外，我们展示了该扩展模型在优化交通信号设置的实验中的实际应用。出于计算原因，这些实验采用了替代模型来近似我们的扩展Payne-Whitham模型，随后我们利用微分进化优化算法，从而确定了提高汽车平均速度并减少总排队长度的交通信号设置，从而促进更顺畅的交通流。
英文摘要：
Urban road transport is a major civilisational and economic challenge, affecting the quality of life and economic activity. Addressing these challenges requires a multidisciplinary approach and sustainable urban planning strategies to mitigate the negative effects of traffic in cities. In this paper, we introduce an extension of one of the most popular macroscopic traffic simulation models, the Payne-Whitham model. We investigate how this model, originally designed to model highway traffic on straight road segments, can be adapted to more realistic conditions with arbitrary road network graphs and multiple intersections with traffic signals. Furthermore, we showcase the practical application of this extension in experiments aimed at optimising traffic signal settings. For computational reasons, these experiments involve the adoption of surrogate models for approximating our extended Payne-Whitham model, and subsequently, we utilise the Differential Evolution optimization algorithm, resulting in the identification of traffic signal settings that enhance the average speed of cars and decrease the total length of queues, thereby facilitating smoother traffic flow.
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