Accuracy of critical gap estimates

Abstract

The critical gap is an important parameter in capacity models of unsignalized intersections. Although there are many methods for critical gap estimation, there is currently no approach or method available to determine how precise a calculated estimate is, i.e. how close it is to the true mean critical gap. As a result, traffic engineers and researchers risk unknowingly working with imprecise estimates, which can lead to inaccurate or unreliable capacity analyses of unsignalized intersections. The purpose of this paper is to address this problem by providing new methods for measuring the accuracy of critical gap estimates. We focus on estimates obtained by the maximum likelihood method (using the so-called Fisher information), but a method for measuring the accuracy of arbitrary estimation methods (the Bootstrap method) is also provided. The paper shows how the proposed methods help to assess the quality of critical gap estimates, detect imprecise estimates, and provide guidance on how many observations should be made for the calculated values to be sufficiently precise. Specifically, we recommend that at least 100 observations should be made to generally obtain reliable estimates. For ease of use, an Excel spreadsheet implementing the proposed methods is provided.

Keywords

• Critical gap
• Maximum likelihood
• Fisher information
• Bootstrap
• Confidence interval