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Lane-level traffic estimations using microscopic traffic variables

机译:使用微观交通变量估算车道级交通

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This paper proposes a novel inference method to estimate lane-level traffic flow, time occupancy and vehicle inter-arrival time on road segments where local information could not be measured and assessed directly. The main contributions of the proposed method are 1) the ability to perform lane-level estimations of traffic flow, time occupancy and vehicle inter-arrival time and 2) the ability to adapt to different traffic regimes by assessing only microscopic traffic variables. We propose a modified Kriging estimation model which explicitly takes into account both spatial and temporal variability. Performance evaluations are conducted using real-world data under different traffic regimes and it is shown that the proposed method outperforms a Kalman filter-based approach.
机译:本文提出了一种新颖的推理方法来估算道路级交通流量,时间占用和车辆在路段上的到达时间,即无法直接测量和评估本地信息的道路段。所提出的方法的主要贡献是1)能够执行交通流量,时间占用和速度跨时时间和2)通过评估仅进行微观流量变量来适应不同交通方案的能力。我们提出了一种修改的Kriging估计模型,该模型明确地考虑了空间和时间可变性。在不同的交通制度下使用真实世界数据进行性能评估,并表明该方法优于基于卡尔曼滤波器的方法。

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