扩展背压交通信号控制算法的吞吐量最优性

Nan Xiao, Emilio Frazzoli, Yiwen Luo, Yitong Li, Yu Wang, Danwei W. Wang
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引用次数: 15

摘要

现有文献中提出的背压/最大压力交通信号控制算法是分布式的,能够最大化网络吞吐量,并且可以在不知道交通到达率的情况下实现。本文提出了一种扩展的背压交通信号控制算法,该算法可以进一步处理队列长度中的有界测量/估计噪声,并结合了转弯比和饱和流量的在线估计。因此,扩展背压算法是实现分布式交通信号控制真正应用的重要一步。我们证明了在一定条件下,扩展背压算法仍然可以获得最大吞吐量,即对于最大可能到达向量集,扩展背压算法下总队列的期望长期平均值是由上有界的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Throughput optimality of extended back-pressure traffic signal control algorithm
The back-pressure/max-pressure traffic signal control algorithm proposed in the existing literature is distributed, maximizes network throughput, and can be implemented without knowing traffic arrival rates. In this paper, we present an extended back-pressure traffic signal control algorithm, which can further handle bounded measurement/estimation noises in queue lengths and incorporate online estimation of turning ratios and saturated flow rates. Therefore, the extended back-pressure algorithm forms an important step towards the real application of distributed traffic signal control. We prove that under certain conditions, the extended back-pressure algorithm still achieves maximum throughput, i.e, the expected long-term average of total queues is bounded from above under the extended back-pressure algorithm for largest possible set of arrival vectors.
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