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首页> 外文期刊>Intelligent Transportation Systems, IEEE Transactions on >Moment Analysis of Highway-Traffic Clearance Distribution
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Moment Analysis of Highway-Traffic Clearance Distribution

机译:公路通行间隙分布的矩分析

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摘要

To help with the planning of intervehicular communication networks, an accurate understanding of traffic behavior and traffic phase transition is required. We calculate intervehicle spacings from empirical data collected in a multilane highway in California, USA. We calculate the correlation coefficients for spacings between vehicles in individual lanes to show that the flows are independent. We determine the first four moments for individual lanes at regular time intervals, namely, the mean, variance, skewness, and kurtosis. We follow the evolution of these moments as the traffic condition changes from the low-density free flow to high-density congestion. We find that the higher moments of intervehicle spacings have a well-defined dependence on the mean value. The variance of the spacing distribution monotonously increases with the mean vehicle spacing. In contrast, our analysis suggests that the skewness and kurtosis provide one of the most sensitive probes toward the search for the critical points. We find two significant results. First, the kurtosis calculated in different time intervals for different lanes smoothly varies with the skewness. They share the same behavior with the skewness and kurtosis calculated for probability density functions that depend on a single parameter. Second, the skewness and kurtosis as functions of the mean intervehicle spacing show sharp peaks at critical densities expected for transitions between different traffic phases. The data show a considerable scatter near the peak positions, which suggests that the critical behavior may depend on other parameters in addition to the traffic density.
机译:为了帮助进行车辆间通信网络的规划,需要对交通行为和交通相位过渡有准确的了解。我们根据在美国加利福尼亚州的多车道高速公路中收集的经验数据计算车辆间距。我们计算各个车道上车辆间距的相关系数,以表明流量是独立的。我们以规则的时间间隔确定各个车道的前四个时刻,即均值,方差,偏度和峰度。当交通状况从低密度自由流动变为高密度拥堵时,我们会跟踪这些时刻的演变。我们发现,行距的较高矩对平均值具有明确的依赖性。间距分布的方差随平均车辆间距单调增加。相反,我们的分析表明,偏度和峰度为寻找临界点提供了最灵敏的探针之一。我们发现两个重要结果。首先,在不同时间间隔内针对不同车道计算出的峰度随偏斜度平滑变化。它们与为依赖于单个参数的概率密度函数计算的偏度和峰度具有相同的行为。第二,偏斜度和峰度是平均行车间距的函数,在不同交通阶段之间的过渡所预期的临界密度处会出现尖峰。数据显示在峰值位置附近有相当大的分散,这表明临界行为可能还取决于流量密度以外的其他参数。

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