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. On the other hand, unlike trip generation models to estimate vehicle trips, literature documents limited research to model and measure activity pertaining to pedestrian counts. This paper presents the development and an assessment of models to measure pedestrian activity at signalized intersections. Data collected at 176 signalized intersections in the City of Charlotte, located in the State of North Carolina, are used to develop models to measure pedestrian activity by the time of the 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), socio-economic 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 using features available in a commercial Geographic Information Systems (GIS) 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.
Samenvatting