Abstract

This study develops a feedback perimeter control strategy to maximize the throughput of an incident-affected network. The proposed perimeter control strategy is innovative in two aspects. First, the control variables, i.e., the inflow rates to the controlled subnetwork within the incident-affected network, are adjusted based on the online estimation of maximum network throughput that is updated dynamically using real-time traffic data and road vulnerability. The incident-dependent network throughput provides the perimeter control a more legitimate control target. Second, the proposed perimeter control strategy applies the proportional-integral-derivative controller, which enhances control stability given the dynamically-updated control target. The results of simulation experiments demonstrate that the proposed strategy can enhance the average speed and reduce the total delay of the incident-affected traffic.

摘要

本研究开发了一种反馈边界控制策略，以最大限度地提高受事件影响的网络的吞吐量。提议的周界控制策略在两个方面具有创新性。首先，控制变量，即受事故影响网络内受控子网的流入速率，根据最大网络吞吐量的在线估计进行调整，该估计使用实时交通数据和道路脆弱性动态更新。事件相关的网络吞吐量为周边控制提供了一个更合法的控制目标。其次，所提出的周界控制策略应用了比例-积分-微分控制器，在动态更新控制目标的情况下提高了控制稳定性。