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Lane Group-Based Traffic Model for Assessing On-Ramp Traffic Impact

机译:基于LANE组的流量模型,用于评估斜坡交通影响

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摘要

On-ramp merging areas are congestion-prone segments of freeways. Depending on the aggressiveness of the driving population and the congestion level, the speed variance among travel lanes due to lane changes and ramp-merging flows may be so significant as to affect the optimal settings of deployed traffic control systems, such as metering rates or advisory speed limits. Extending from METANET, this study presents a lane group-based (LGB) traffic model to reflect the temporal and spatial distributions of traffic conditions among lane groups. The proposed model would allow traffic engineers to reliably assess the impacts of lane-changing activities in both upstream and downstream segments of an on-ramp area and better design their coordinated control strategies. To assess the effectiveness of the proposed model, this study has compared its performance with METANET under various traffic scenarios. The comparison results show that the proposed model can yield up to 26.9% improvement on the accuracy of predicting the temporal and spatial evolution of a freeway's speed at the interchange area where freeway segments often experience extensive lane-changing activities due to on-ramp merging flows.
机译:匝道融合区域是高速公路拥堵易患段。根据驾驶人口的侵略性和拥塞水平,由于车道变化和斜坡合并流量的行程车道之间的速度方差可能非常重要,以影响部署的流量控制系统的最佳设置,例如计量率或咨询速度限制。本研究从Metanet延伸,介绍了基于车道组(LGB)业务模型,以反映车道组之间的交通状况的时间和空间分布。拟议的模型将允许交通工程师可靠地评估车道改变活动在斜坡面积上游和下游部分中的影响,并更好地设计其协调的控制策略。为了评估所提出的模型的有效性,本研究将其在各种交通方案下与Metanet进行了比较。比较结果表明,拟议的模型可以提高高达26.9%的提高,提高高速公路速度在高速公路段的速度速度的时间和空间演进的准确性,在坡道段常常由于匝道合并流动而经历了广泛的车道变化活动。

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