Performance Evaluation and Correction Functions for Automated Pedestrian and Bicycle Counting Technologies

Abstract

Automated counting technologies are one of the fastest growing sources of data in the non-motorized transportation field. Although automated counts make it possible to collect data for longer time periods and to document temporal variations in volumes more effectively than manual counts, all of the technologies being used are subject to systematic miscount rates that must be accounted for to generate accurate volume estimates. In this paper, accuracy and precision rates are tested for six automated pedestrian and bicycle counting technologies: passive infrared, active infrared, radio beam, pneumatic tubes, inductive loops, and piezoelectric strips. For some technologies, multiple products are tested. Counting devices were installed at 13 sites in seven cities to introduce variation in environmental (weather) conditions and volume levels, and manual validation counts were conducted based on video footage taken at each of the test sites. Correction functions are developed for each technology to increase accuracy of volume estimates. Various environmental conditions including temperature, rain, and lighting are tested in the development of the correction functions. For most technologies, a net undercount effect was observed that appears to worsen at higher volumes. Average error rates (average percentage deviation) for the tested technologies range from 0.55% for inductive loops to −17.38% for pneumatic tubes. However, after applying correction functions accuracy improves for nearly all technologies.