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Required traffic micro-simulation runs for reliable multivariate performance estimates

机译:进行必要的流量微仿真,以进行可靠的多元性能估算

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摘要

Previous methods to calculate the minimum number of traffic micro-simulation runs do not consider multiple measures of performance simultaneously at an overall confidence level, which can lead to unreliable simulation outputs. This paper describes new methodologies for calculating the minimum number of traffic micro-simulation runs for multivariate estimates at an overall confidence level. Simultaneous confidence intervals obtained from multiple comparisons in statistical theory such as the Bonferroni inequality and simultaneous confidence interval method are used to estimate multiple measures of performance with allowable errors at an overall confidence level. Measures of performance can be means and standard deviations. Results of numerical analysis based on an example corridor suggest that the proposed methods provide improved means of assessing statistical accuracy of multiple measures of performance. Results also indicate that the minimum number of runs is influenced by not only the sample size issue but also the complexity of the traffic system. Copyright (c) 2015 John Wiley & Sons, Ltd.
机译:先前用于计算流量微仿真运行的最小数量的方法没有在总体置信度上同时考虑多种性能指标,这可能导致仿真输出不可靠。本文介绍了一种用于在总体置信度水平上为多变量估计计算最小流量模拟运行次数的新方法。从统计理论中的多次比较(例如Bonferroni不等式和同时置信区间方法)获得的同时置信区间用于估计总体置信水平下允许误差的性能的多种度量。绩效的衡量标准可以是均值和标准差。基于示例走廊的数值分析结果表明,所提出的方法提供了改进的方法来评估多种绩效衡量指标的统计准确性。结果还表明,最少运行次数不仅受到样本量问题的影响,还受到交通系统复杂性的影响。版权所有(c)2015 John Wiley&Sons,Ltd.

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