Prioritizing Pedestrian and Bicyclist Count Locations for Volume Estimation

Abstract

As data collection programs grow, cities need a way to systematically deploy counting equipment in a way that ensures robust pedestrian and bicyclist volume data are collected across a spectrum of use patterns and infrastructure contexts. This paper presents the findings from a deep dive into pedestrian and bicyclist volumes and exposure, including statistical modeling, as well as translating the outputs into an algorithm for systematically growing Seattle Department of Transportation’s nonmotorized count data collection program. The data collection location prioritization algorithm described in this paper provides a roadmap for cities and other agencies as they build their nonmotorized data collection programs.