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QUANTIFYING NON-RECURRING CONGESTION IMPACT ON SECONDARY INCIDENTS USING PROBE VEHICLE DATA

机译:使用探测车数据量化对次要事故的非递归堵塞影响

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As a significant cost and externality to economic efficiency, congestion is partly caused by traffic incidents. For more systematic, planned and coordinated incident management, quantifying a primary incident's impact on secondary incidents is crucial and challenging. Many thresholds have been suggested in defining the secondary incidents, but there is no universal acceptance of a definition and corresponding set of measurement parameters. Static threshold methods cannot consider the actual representation of prevailing traffic conditions when the incidents took place. On the other hand, dynamic methods have disadvantages because necessary traffic detector data may not be available, and replication of the incidents using a simulation package can be time consuming. The novelty of this study rests in the attempt of a probe vehicle technique for capturing the dynamics of traffic evolution during the primary-crash incidents. Compared to the previous thresholds which have many errors, proposed speed contour map from Traffic Message Channel codes provides accurate feasible area for identification of secondary incidents.
机译:由于交通成本高昂和经济效率的外部性,交通拥堵在一定程度上引起了交通拥堵。对于更系统,计划和协调的事件管理,量化主要事件对次要事件的影响至关重要且具有挑战性。在定义次要事件时已经提出了许多阈值,但是并没有普遍接受定义和相应的测量参数集。发生事件时,静态阈值方法无法考虑实际交通状况的实际表示。另一方面,动态方法具有缺点,因为可能无法获得必要的流量检测器数据,并且使用模拟包复制事件可能很耗时。这项研究的新颖性在于尝试探测车辆技术来捕获主要碰撞事件期间交通演变的动态。与先前存在很多错误的阈值相比,交通消息通道代码提出的速度等高线图为识别二次事件提供了准确的可行区域。

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