Assessment of Models to Measure Pedestrian Activity at Signalized Intersections

Document Type

Journal Article

Publication Date


Subject Area

operations - traffic, planning - signage/information, technology - geographic information systems, mode - pedestrian, mode - pedestrian


Traffic volume, Time of day, Speed limits, Socioeconomic factors, Socioeconomic aspects, Signalized intersections, Signalised intersections, Periods of the day, Pedestrian movement, Pedestrian crossings, Pedestrian counts, Multiple regression analysis, Mathematical models, Land use, GIS, Geographic information systems, Geocoding, Demographics, Data collection, Data acquisition, Crosswalks, Crossing The Road, Charlotte (North Carolina)


The allocation of resources to build facilities amicable to pedestrians is governed by pedestrian activity at the location of interest. Collecting real-world data such as pedestrian counts at each point of interest is an expensive and time-consuming process. However, unlike trip generation models to estimate vehicle trips, the literature documents limited research to model and measure activity pertaining to pedestrian counts. The development and an assessment of models to measure pedestrian activity at signalized intersections are presented. Data collected at 176 signalized intersections in the city of Charlotte, North Carolina, are used to develop models to measure pedestrian activity by the time of day at signalized intersections. Pedestrian counts collected at the 176 intersections are used as a dependent variable. Factors such as demographic characteristics (population, household units), socioeconomic characteristics (income level, employment), land use characteristics (residential, commercial, industrial, etc.), network characteristics (number of approaches, number of lanes, speed limits, traffic volume, presence of medians), and the number of transit stops are extracted and estimated by using features available in a commercial geographic information system software program. These factors are used as independent variables. Multiple regression analysis through backward elimination of independent variables is used to develop the models. The developed models could be used by practitioners to measure pedestrian activity at a location if data are available. The measured pedestrian activity could be used in transportation planning, safety, and operational analyses.