Evaluation Methods for Estimating Vehicle Miles Traveled with GPS Travel Survey Data

Abstract

This research investigated the degree to which traditional routing algorithms, including those that took congestion levels into consideration, could be used to accurately predict GPS-recorded vehicle miles traveled (VMT) if only activity locations were known. Given recent policy interest in distance-based charges, the ability to predict household VMT accurately is an important research area because it can improve the quality of distributional assessments of distance-based proposals. This analysis found that shortest-time travel paths that incorporated congestion levels performed best across all income groups, urban locations, and trip lengths when compared with shortest-travel time paths with no congestion or shortest-distance paths. The average margin of error from this analysis was considerably smaller than those found in other studies. Failure to incorporate congestion effects into distance estimates consistently resulted in underestimation of household travel distance, sometimes rather significantly.