Exploiting Correlations between Link Flows to Improve Estimation of Average Annual Daily Traffic on Coverage Count Segments

Abstract

A method is developed for exploiting correlations among segment flows that result from common origin–destination (O-D) path flows when average annual daily traffic (AADT) is being estimated on highway segments sampled with coverage counts. The method, which can be used with only two daily traffic volumes on the coverage count segment, is based on generalized least squares estimation of AADT, rather than on ordinary least squares estimation, which is traditionally used. The focus is on the correlation between the volumes on a single coverage count segment and a single segment equipped with a continuous automatic traffic recorder (ATR). The performance of this correlation-based method is compared with that of the traditional method through use of thousands of simulated O-D flow replications that are assigned on a small network to determine segment flows. The correlation-based method markedly outperforms the traditional method when the volume on the coverage count segment is highly correlated with that on the ATR segment. When the correlation between the volumes on the coverage count and ATR segments is low, the performance of the two methods is similar. It is expected that future developments for exploiting correlations between volumes on coverage count segments and multiple ATR segments will improve performance further.