Quality Assurance Methods for Hourly Nonmotorized Traffic Counts

Abstract

Growing numbers of public transportation and recreation agencies have implemented automated bicycle and pedestrian traffic monitoring programs. To support these initiatives, researchers and agency analysts have developed programs, methods, and measures to ensure data quality. These methods include statistical tests for identifying and flagging outliers and other invalid counts and procedures for imputing or managing missing and censored counts. Because statistics such as annual average daily bicyclists are used frequently in planning and engineering, analysts have focused on validation of daily counts using data from permanent monitors. Procedures for ensuring the validity of hourly counts have not been standardized. This paper presents quality assurance (QA) methods for hourly nonmotorized traffic counts at 115 short-duration and nine permanent monitoring sites on multiuse trails monitored by the Minnesota Department of Natural Resources (MnDNR) and the Minnesota Department of Transportation (MnDOT) between 2016 and 2021. These methods include statistical tests for flagging and censoring invalid hourly counts and procedures for imputing estimates for censored or missing counts. Differences in traffic flow estimates with and without QA are documented, and hourly patterns and factors are presented. Use of quality assurance methods for hourly counts can increase the validity of estimates of nonmotorized traffic.