Koopman算子在信号控制交通系统中的应用
Koopman Operator Applications in Signalized Traffic Systems
摘要：
本文提出了Koopman算子理论和相应的动态模式分解（DMD）算法，用于信号控制交通流网络的分析和控制。DMD提供了一个无模型的方法来表示复杂的振荡动力学从测量数据，我们研究了它的应用在信号交通中的几个问题。我们首先研究了一个单信号交叉口，我们提出应用这种方法来推断交通信号控制参数，如相位定时直接从交通流数据。接下来，我们建议使用振荡模式的Koopman运营商，近似DMD，早期识别不稳定的队列增长，有可能导致级联拥塞。然后，我们演示了如何DMD可以加上知识的交通信号控制状态，以确定交通信号控制参数，能够减少队列长度。最后，我们证明，DMD允许确定的结构和强度的相互作用，在网络的信号交叉口。所有的例子都证明了使用一个案例研究网络仪表与高分辨率的交通流量传感器。
英文摘要：
This paper proposes Koopman operator theory and the related algorithm dynamical mode decomposition (DMD) for analysis and control of signalized traffic flow networks. DMD provides a model-free approach for representing complex oscillatory dynamics from measured data, and we study its application to several problems in signalized traffic. We first study a single signalized intersection, and we propose applying this method to infer traffic signal control parameters such as phase timing directly from traffic flow data. Next, we propose using the oscillatory modes of the Koopman operator, approximated with DMD, for early identification of unstable queue growth that has the potential to cause cascading congestion. Then we demonstrate how DMD can be coupled with knowledge of the traffic signal control status to determine traffic signal control parameters that are able to reduce queue lengths. Lastly, we demonstrate that DMD allows for determining the structure and the strength of interactions in a network of signalized intersections. All examples are demonstrated using a case study network instrumented with high resolution traffic flow sensors.
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