Pilot Model for Estimating Pedestrian Intersection Crossing Volumes

Abstract

Better data on pedestrian volumes are needed to improve the safety, comfort, and convenience of pedestrian movement. This requires more carefully-developed methodologies for counting pedestrians as well as improved methods of modeling pedestrian volumes. This paper describes the methodology used to create a simple, pilot model of pedestrian intersection crossing volumes in Alameda County, CA. The model is based on weekly pedestrian volumes at a sample of 50 intersections with a wide variety of surrounding land uses, transportation system attributes, and neighborhood socioeconomic characteristics. Three alternative model structures were considered, and the final recommended model has a good overall fit (adjusted-R 2 =0.897). Statistically-significant factors in the model include the total population within a 0.5-mile radius, employment within a 0.25-mile radius, number of commercial retail properties within a 0.25-mile radius, and the presence of a regional transit station within a 0.1-mile radius of an intersection. The model has a simple structure, and it can be implemented by practitioners using geographic information systems and a basic spreadsheet program. Since the study is based on a relatively small number of intersections in one urban area, additional research is needed to refine the model and determine its applicability in other areas.

Association between Roadway Intersection Characteristics and Pedestrian Crash Risk in Alameda County, California

“…This would include accounting for 5 weekday and weekend pedestrian activity, seasonal changes in pedestrian volumes, and differences in 6 pedestrian activity patterns near certain land uses (e.g., schools, neighborhood commercial areas). The intersection selection process was designed to capture a range of intersection site characteristics and 23 surrounding neighborhood characteristics (35). The 81 study intersections were spread throughout the 24 county.…”

Spatial modeling of bicycle activity at signalized intersections

“…One of the few studies using average daily volumes is that done by Schneider et al (2009); however, counts were not corrected for weather conditions. Moreover, most studies have employed simple statistical methods that do not correct for spatial autocorrelation.…”

Guidebook on Pedestrian and Bicycle Volume Data Collection

“…This process, called stratified random sampling, can be used to ensure that there are at least a few count locations with each key characteristic of interest. This strategy has been used to select count locations when developing predictive pedestrian and bicycle volume models and safety performance functions (Schneider, Arnold, and Ragland 2009a;Schneider et al 2010;Griswold, Medury, and Schneider 2011;Strauss, Miranda-Moreno, and Morency 2014). See the San Diego County case study for an example of stratified sampling.…”