Required traffic micro-simulation runs for reliable multivariate performance estimates

Long Truong, Majid Sarvi, Graham Currie, Tim Garoni

Research output: Contribution to journalArticleResearchpeer-review

16 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)296 - 314
Number of pages19
JournalJournal of Advanced Transportation
Volume50
Issue number3
DOIs
Publication statusPublished - 2016

Keywords

  • Traffic micro-simulation
  • Simulation
  • Run
  • Replication

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