The measurement of traffic volumes on an extensive nationwide network is a very large task. It is not feasible to count all traffic on all roads all of the time.
Considerable reduction or effort in the counting process can be achieved by identifying key factors that may allow for grouping of roads into similar groups.
This project has derived nine major groups of roads based on the two-way hourly traffic pattern over the latest available two calendar years for continuous count/classification sites on state highways and local roads. This was achieved using hierarchical cluster analysis in the same manner as the similar, ground-breaking project undertook in the mid 1990's using older data, and prior to the introduction of the four term school year.
Statistical analysis of the estimation of AADT for vehicle counts of 2-3 hours, 24 hours, and 168 hours duration was undertaken, as well as estimation of the heavy vehicle AADT for classified counts of one-week duration. Various summary tables and graphs are provided.
Keywords: traffic counts, electronic traffic data, annual average daily traffic, hierarchical cluster analysis, New Zealand