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Incorporating multiple congestion levels into spatiotemporal analysis for the impact of a traffic incident

机译：将多种拥塞水平纳入时尚分析，以对交通事故的影响

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摘要

Traffic incidents occurring on the road interrupt the smooth mobility of traffic flow and lead to traffic congestion. Although there has been a proliferation of studies that attempt to estimate the spatiotemporal impact of a traffic incident, most, if not all, of them focus exclusively on the differentiation of bi-level traffic status. In this research, we propose to incorporate multiple congestion levels in the spatiotemporal analysis for the impact of a traffic incident, which is new to the literature. The input to our model includes the historical speed on a given road and the occurrence time and location of the incident. The model then outputs the spatiotemporal impact region with multiple congestion levels. We first use a discriminant indicator to initially indicate the traffic status according to the travelling speed of probe vehicles. We then develop an integer programming model with a set of novel constraints to estimate the spatiotemporal region impacted by the incident. Unlike existing studies that only distinguish between uncongested and congested status, our model allows us to determine the impact region with diverse congestion levels. We validate our model using both simulation and real data. Results demonstrate that our approach can not only ensure the consistency of the propagation of shockwaves even when multiple congestion levels are incorporated, but also produce more accurate estimation of the delay caused by the incident when compared to the current state-of-the-art approach.
机译：在道路上发生的交通事故中断交通流量的平稳流动性并导致交通拥堵。虽然有促进了研究的研究，但试图估计交通事件的时空影响，最重要的是，如果不是全部，他们都会专注于双层交通状况的分化。在这项研究中，我们建议在空间分析中纳入多种充血水平，以对交通事故的影响，这对文献来说是新的。我们模型的输入包括给定道路上的历史速度和事件的发生时间和位置。然后，该模型输出具有多种拥塞水平的时空撞击区域。我们首先使用判别指示器根据探针车辆的行驶速度最初地指示交通状态。然后，我们开发一个整数编程模型，具有一组新颖的约束来估计由事件影响的时空区域。与现有的研究不同，这些研究只区分了不受欢迎和拥挤状态，我们的模型允许我们确定具有多种拥塞水平的冲击区域。我们使用模拟和实际数据验证我们的模型。结果表明，即使在掺入多种拥塞水平时，我们的方法也不仅可以确保冲击波的传播的一致性，而且还产生更准确地估计与当前最先进的方法相比引起的事件引起的延迟。

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