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A Comparative Assessment of Stochastic Capacity Estimation Methods

机译:随机容量估计方法的比较评估

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The stochastic nature of highway capacity has gained increasing attention in recent times. For the empirical estimation of capacity distribution functions based on measured traffic data, two methodologies have received considerable application: The direct estimation of breakdown probabilities for groups of traffic volumes on the one hand and the estimation of capacity distribution functions based on statistical models for censored data on the other hand. The objective of the paper is to compare these methods in terms of estimation accuracy, applicability, and consistency of the results. The theoretical differences of both methods as well as the consequences for application are discussed and analyzed based on empirical traffic data as well as data from macroscopic simulation. The analysis yields that the capacity estimation based on models for censored data performs better than the direct breakdown probability estimation technique, particularly concerning the consistency of the estimated capacity distribution functions.
机译:近年来,高速公路通行能力的随机性越来越受到关注。对于基于实测交通数据的容量分布函数的经验估计,两种方法已得到了广泛应用:一方面直接估计一组交通量的故障概率,另一种方法是基于受审查数据的统计模型来估计容量分布函数。另一方面。本文的目的是在估计准确性,适用性和结果一致性方面比较这些方法。基于经验交通数据以及宏观模拟数据,讨论和分析了这两种方法的理论差异以及应用的后果。分析得出,基于审查数据模型的容量估计比直接分解概率估计技术要好,特别是在估计容量分布函数的一致性方面。

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