Estimating confidence intervals for transport Mode share.

One of the common statistics used to monitor transport activity is the total travel by a particular method or mode and, for each mode, this share is routinely expressed as a percentage of total personal travel. This article describes a simple model to estimate a confidence interval around this percentage using Monte Carlo simulation. The model takes into account the impact of both measurement errors in counting traffic and daily variations in traffic levels. These confidence intervals can then be used to test reliably for significant changes in mode share. The model can also be used in sensitivity analysis to investigate how sensitive the width of this interval is to changes in the size of the measurement errors and daily fluctuations. A bootstrap technique is then used to validate the Monte Carlo estimated confidence interval.