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QUANTIFYING CROSS-WEAVE IMPACT ON CAPACITY REDUCTION FOR FREEWAY FACILITIES WITH MANAGED LANES

机译:量化交叉网对带管理车道的高速公路设施的减容影响

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With the increasing concerns towards environmental impacts and sustainability of roadwaycapacity expansion, transportation agencies are seeking alternative solutions for congestionmitigation. Managed Lanes (MLs) promote person throughput on freeways and managecongestion through improving efficiency. The ML concept therefore has been gaining popularityin the past decades. However, the lack of guidance on performance evaluation of ML facilityposes real challenges for agencies wanting to design and implement the strategy in an effectivemanner. Many MLs are designed to be left-lane concurrent, where vehicles entering the freewayfrom General Purpose (GP) lanes on-ramps, need to cross weave over multiple GP lanes toaccess the ML. These weaving vehicles will have a negative impact on the operatingperformance of the parallel GP lanes. This paper investigates this cross-weaving effect as afunction of different roadway geometric configurations as well as traffic conditions. Amicroscopic simulation model is built and calibrated on the basis of video data collected alongIH 635 in Dallas, Texas. Multiple scenarios are tested to explore the effect of number of GPlanes, cross-weave demand, and cross-weaving length. A set of Capacity Adjustment Factors(CAF) are determined to account for this effect as a function of the above parameters. This studydiscovers that the capacity reducing effect is higher with a reduction in cross weaving length, anincrease in number of GP lanes, or a rise in cross-weave demand volumes. The results arevaluable in evaluating the operational performance of freeway segments in the presence ofconcurrent GP and ML in a Highway Capacity Manual context.
机译:随着人们越来越关注环境影响和道路的可持续性 运力扩大,运输机构正在寻求替代方案来解决拥堵问题 减轻。托管车道(MLs)可以提高高速公路上的人员吞吐量并进行管理 通过提高效率来解决拥堵问题。因此,机器学习的概念已逐渐普及 在过去的几十年中。但是,缺乏关于机器学习设施绩效评估的指导 对于希望有效设计和实施策略的代理商提出了真正的挑战 方式。许多ML设计为左车道并发,车辆进入高速公路 从斜坡上的通用(GP)车道,需要交叉编织到多个GP车道, 访问ML。这些织造车辆将对运营产生负面影响 并行GP通道的性能。本文将这种交叉编织的影响作为 不同道路几何形状以及交通状况的功能。一种 基于收集的视频数据,建立并校准微观仿真模型 德克萨斯州达拉斯市的IH 635。测试了多种方案以探索GP数量的影响 车道,交叉编织需求和交叉编织长度。一组容量调整因素 确定CAF(CAF)作为上述参数的函数来解决此问题。这项研究 发现随着交叉编织长度的减少,容量降低效果更高, GP车道数量的增加,或交叉编织需求量的增加。结果是 在评估高速公路段存在的情况下的运营绩效方面具有重要价值 在“公路通行能力手册”中同时进行GP和ML。

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