San Francisco Pedestrian Intersection Volume Model
The San Francisco Pedestrian Intersection Volume Model was developed in 2010 to estimate intersection pedestrian crash rates (reported crashes per million pedestrian crossings) and predict how pedestrian volumes are likely to change as development occurs near intersections in different neighborhoods. The San Francisco Municipal Transportation Authority (SFMTA) collected two-hour manual counts from 50 intersections that provided the foundation for the model. These 50 intersections had a variety of surrounding land uses, transportation system attributes, topographic features, and neighborhood socioeconomic characteristics. SFMTA also collected continuous pedestrian volume data using automated sensors on sidewalks close to 25 of these intersections. Time of week and land use adjustment factors were developed and used to extrapolate two-hour manual pedestrian crossing counts to annual volume estimates.
Loglinear regression modeling identified variables that had statistically-significant relationships with annual pedestrian intersection crossing volumes. Six alternative model structures were considered, and the final recommended model had a good overall fit (adjusted R-squared = 0.804). Pedestrian volumes were positively associated with the number of households within 1/4 mile of an intersection, number of jobs within 1/4 mile of an intersection, the intersection being in a zone with metered on-street parking, fewer hills near the intersection, the intersection being within 1/4 mile of a university campus, and the intersection being controlled by a traffic signal. The model was based on a relatively small sample of intersections, so the number of significant factors was limited to six. Other factors that may also be associated with pedestrian volumes in San Francisco include proximity to retail shopping areas and frequent transit service.
The model has a simple structure, and it can be applied using a basic spreadsheet program. Fehr & Peers Transportation Consultants applied the model to rank and map intersection pedestrian crash rates for more than 8,100 intersections throughout San Francisco.
Location: San Francisco, California
Funders: San Francisco Municipal Transportation Agency; Fehr & Peers Transportation Consultants. Work was performed at the UC Berkeley Safe Transportation Research and Education Center.
Project Period: June 2010 to May 2011
Additional Information: http://www.sfmta.com/cms/wproj/indxpdproj.htm
Loglinear regression modeling identified variables that had statistically-significant relationships with annual pedestrian intersection crossing volumes. Six alternative model structures were considered, and the final recommended model had a good overall fit (adjusted R-squared = 0.804). Pedestrian volumes were positively associated with the number of households within 1/4 mile of an intersection, number of jobs within 1/4 mile of an intersection, the intersection being in a zone with metered on-street parking, fewer hills near the intersection, the intersection being within 1/4 mile of a university campus, and the intersection being controlled by a traffic signal. The model was based on a relatively small sample of intersections, so the number of significant factors was limited to six. Other factors that may also be associated with pedestrian volumes in San Francisco include proximity to retail shopping areas and frequent transit service.
The model has a simple structure, and it can be applied using a basic spreadsheet program. Fehr & Peers Transportation Consultants applied the model to rank and map intersection pedestrian crash rates for more than 8,100 intersections throughout San Francisco.
Location: San Francisco, California
Funders: San Francisco Municipal Transportation Agency; Fehr & Peers Transportation Consultants. Work was performed at the UC Berkeley Safe Transportation Research and Education Center.
Project Period: June 2010 to May 2011
Additional Information: http://www.sfmta.com/cms/wproj/indxpdproj.htm
