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A Study for Self-adapting Urban Traffic Control

机译:自适应城市交通控制研究

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Nowadays, managing traffic in cities is a complex problem involving considerable physical and economical resources. However, traffic can be simulated by multi-agent systems (MAS), since cars and traffic lights can be modeled as agents that interact to obtain an overall goal: to reduce the average waiting times for the traffic users. In this paper, we present a self-organizing solution to efficiently manage urban traffic. We compare our proposal with other classical and alternative self-organizing approaches, observing that ours provides better results. Then, we present the main contributions of the paper that analyze the effects of different traffic conditions over our cheap and easy-to-implement method for self-organizing urban traffic management. We consider several scenarios where we explore the effects of dynamic traffic density, a reduction in the percentage of sensors needed to support the traffic management system, and the possibility of using communication among cross-points.
机译:如今,管理城市交通是一个复杂的问题,涉及大量的物力和经济资源。但是,可以通过多智能体系统(MAS)来模拟交通,因为可以将汽车和交通信号灯建模为交互以实现总体目标的智能体:减少交通用户的平均等待时间。在本文中,我们提出了一种自组织解决方案来有效地管理城市交通。我们将我们的建议与其他经典的和替代性的自组织方法进行了比较,发现我们的方法提供了更好的结果。然后,我们提出了本文的主要贡献,分析了不同交通状况对我们便宜且易于实现的自组织城市交通管理方法的影响。我们考虑了几种场景,其中探讨了动态流量密度的影响,减少了支持流量管理系统所需的传感器的百分比以及在交叉点之间使用通信的可能性。

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