论文标题
考虑到转弯比的不确定性的强大交通控制模型
A Robust Traffic Control Model Considering Uncertainties in Turning Ratios
论文作者
论文摘要
模型参数不确定性对交通流控制问题的影响最近引起了研究的关注。尽管过去已经研究了基本图相关参数的不确定性，但很少有文章集中在网络参数不确定性上，包括转弯比不确定性。为了填补这一空白，本文提出了一个可靠的控制模型，以使用分配强大的机会约束来处理转弯比的不确定性。该模型允许在网络参数的所有可能分布下计算最大化某些目标的最佳控制动作。然后，我们将此强大的控制框架应用于高速公路网络和城市网络，并评估不确定性对最佳控制输入的影响，对测试网络。案例研究表明，与非运动控制相比，提出的强大模型可以减少不确定性带来的拥塞并改善整体吞吐量。
The effects of model parameter uncertainty on traffic flow control problems have recently drawn research attention. While the uncertainty in fundamental diagram related parameters has been investigated in the past, few articles have focused on network parameters uncertainty, including turning ratio uncertainty. To fill this gap, this article proposes a robust control model to deal with the uncertainties in the turning ratio by using distributionally robust chance constraints. The model allows one to compute the optimal control action that maximizes some objective, under all possible distributions of network parameters. We then apply this robust control framework to both a freeway network and an urban network, and evaluate the impact of uncertainty on optimal control inputs, over the test networks. The case studies show that compared to non-robust control, the proposed robust model can reduce congestion brought by the uncertainties and improve the overall throughput.
