Backpressure (BP) control was originally used for packet routing in communications networks. Since its first application to network traffic control, it has undergone different modifications to tailor it to traffic problems with promising results. Most of these BP variants are based on an assumption of perfect knowledge of traffic conditions throughout the network at all times, specifically the queue lengths (more accurately, the traffic volumes). However, it has been well established that accurate queue length information at signalized intersections is never available except in fully connected environments. Although connected vehicle technologies are developing quickly, we are still far from a fully connected environment in the real world. This paper test the effectiveness of BP control when incomplete or imperfect knowledge about traffic conditions is available. We combine BP control with a speed/density field estimation module suitable for a partially connected environment. We refer to the proposed system as a BP with estimated queue lengths (BP-EQ). We test the robustness of BP-EQ to varying levels of connected vehicle penetration, and we compared BP-EQ with the original BP (i.e., assuming accurate knowledge of traffic conditions), a real-world adaptive signal controller, and optimized fixed timing control using microscopic traffic simulation with field calibrated data. Our results show that with a connected vehicle penetration rate as little as 10%, BP-EQ can outperform the adaptive controller and the fixed timing controller in terms of average delay, throughput, and maximum stopped queue lengths under high demand scenarios.

中文翻译：

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城市网络流量估计队列长度的背压控制

背压 (BP) 控制最初用于通信网络中的数据包路由。自从它第一次应用于网络流量控制以来，它经历了不同的修改，以适应流量问题，并取得了有希望的结果。这些 BP 变体中的大多数都基于一个假设，即始终对整个网络的交通状况，特别是队列长度（更准确地说，是交通量）了如指掌。然而，众所周知，除非在完全连接的环境中，否则永远无法获得信号交叉口的准确队列长度信息。尽管车联网技术发展迅速，但在现实世界中，我们离完全互联的环境还很远。本文测试了当有关交通状况的知识不完整或不完善时，BP 控制的有效性。我们将 BP 控制与适用于部分连接环境的速度/密度场估计模块相结合。我们将所提出的系统称为具有估计队列长度的 BP（BP-EQ）。我们测试了 BP-EQ 对不同级别的联网车辆渗透率的稳健性，并将 BP-EQ 与原始 BP（即假设准确了解交通状况）、真实世界的自适应信号控制器和优化的固定时序控制进行了比较使用带有现场校准数据的微观交通模拟。我们的结果表明，在联网车辆渗透率低至 10% 的情况下，BP-EQ 在平均延迟、吞吐量、