Road Classification Schemes – Good Indicators of Traffic Volume?

We compare three road classification systems to actual traffic counts in order to assess how well the classification systems perform as indicators of traffic volume, assuming that clear differentiation of traffic volumes among classes is desirable. Actual traffic counts were obtained for 215 locations in the Greater Vancouver Regional District(GVRD); the British Columbia provincial Digital Road Atlas (DRA) and DMTI CanMap road network provided road classification systems. Modelled traffic volumes for the GVRD, provided by TransLink, are also used to evaluate the classification systems. Based on the sample of actual traffic counts, we conclude that DRA road classes provide the best differentiation of traffic volume, although within class variation is substantial. Modelled traffic counts are not well differentiated by either the DRA road class or subclass, indicating either poor model performance or sample bias. A comparison of actual traffic count means for three regions in the study area with different total population and population densities showed no spatial pattern that would explain within class variation. Future research on within class variation is required, using a larger sample of actual traffic counts. Overall, the use of road classes to indicate level of exposure to traffic-related air pollution should be approached with caution, as significant exposure misclassification could occur.