Use of Reduction-Effectiveness Ratios to Evaluate Reduced Traffic Data Collection Plans

Abstract

Because of budget shortfalls in recent years, state departments of transportation (DOTs) must adjust their traffic data collection plans by reducing data collection locations or extending data collection cycles; however, few studies have been performed to evaluate the cost-effectiveness of various efforts to reduce data collection. This study developed a quantitative method for evaluating the impact of various reduced plans for traffic data collection on the overall accuracy of the annual average daily traffic (AADT) estimation. The mean absolute percentage error is calculated to compare the accuracy of 10 reduced data collection plans with a base plan. In addition, a reduction-effectiveness ratio (i.e., the percentage of reduced data collection cost to the percentage of increased AADT estimation error) is proposed. Results from this study show that the current practice, which randomly selects data collection sites on the basis of different cycles, performs well in maintaining AADT estimation accuracy but may not be the most cost-effective approach. Results also show that certain types of sites, such as rural sites, lower-AADT sites, and sites with higher AADT variation, tend to produce larger errors if they are not counted. The results imply that the proposed method both provides a quantitative means with which to evaluate plans for reduced data collection and suggests ways to enhance current data collection and traffic estimation practices. The method also enriches the information provided to state departments of transportation for effective and informed decision making with limited resources.