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Schedule-driven intersection control

机译:时间表驱动的路口控制

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Model-based intersection optimization strategies have been widely investigated for distributed traffic signal control in road networks. Due to the form of "black-box" optimization that is typically assumed, a basic challenge faced by these strategies is the combinatorial nature of the problem that must be solved. The underlying state space is exponential in the number of time steps in the look-ahead optimization horizon at a given time resolution. In this paper, we present a schedule-driven intersection control strategy, called SchIC, which addresses this challenge by exploiting the structural information in non-uni-formly distributed traffic flow. Central to our method is an alternative formulation of intersection control optimization as a scheduling problem, which effectively reduces the state space through use of an aggregate representation on traffic flow data in the prediction horizon. A forward recursive algorithm is proposed for solving the scheduling problem, which makes use of a dominance condition to efficiently eliminate most states at early stages. SchIC thus achieves near optimal solutions with a polynomial complexity in the prediction horizon, and is insensitive to the granularity of time resolution that is assumed. The performance of SchIC with respect to both intersection control and implicit coordination between intersections is evaluated empirically on two ideal scenarios and a real-world urban traffic network. Some characteristics and possible real-world extensions of SchIC are also discussed.
机译:对于道路网络中的分布式交通信号控制,已经广泛研究了基于模型的路口优化策略。由于通常采用“黑匣子”优化的形式,这些策略面临的基本挑战是必须解决的问题的组合性质。在给定的时间分辨率下,基础状态空间在前瞻性优化范围内的时间步数是指数级的。在本文中,我们提出了一种称为SchIC的时间表驱动的交叉口控制策略,该策略通过利用非均匀分布的交通流中的结构信息来应对这一挑战。我们方法的核心是将交叉路口控制优化作为调度问题的替代表达,它通过在预测范围内对交通流数据使用聚合表示来有效减少状态空间。提出了一种前向递归算法来解决调度问题,该算法利用优势条件有效地消除了早期的大多数状态。因此,SchIC在预测范围内以多项式复杂度实现了接近最优的解决方案,并且对假设的时间分辨率的粒度不敏感。在两个理想情况和一个现实世界的城市交通网络上,通过经验评估了SchIC在路口控制和路口之间隐式协调方面的性能。还讨论了SchIC的一些特性和可能的​​实际扩展。

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