Predicting a Vehicle's Distance Traveled from Short-duration Data

Abstract

This article uses one year’s worth of daily travel distance data for 252 Seattle households’ vehicles to ascertain that one day’s distance (plus day of week and month of year information) accounts for 10.7% of the variability in that vehicle’s annual (total) distance traveled, while two and seven consecutive days’ distance values predict 16.7% and 33.6%, respectively. In analyzing Gini coefficients (which average 0.546 + / − 0.117 across these instrumented vehicles), one finds that full-time employed females have the most stable day-to-day driving patterns, allowing for shorter-duration surveys of such households.