Achieving Vision Zero: Data-Driven Investment Strategy to Eliminate Pedestrian Fatalities on a Citywide Level

Abstract

San Francisco, California, completed a robust, data-driven process to define and prioritize pedestrian safety improvement projects. The goal of this process was to identify the lowest cost and most effective strategy to meet a citywide goal to eliminate traffic fatalities. A team of planners, engineers, and epidemiologists examined longitudinal pedestrian collision data to identify the major factors that corresponded with pedestrian– vehicle crashes in San Francisco and focused on locations with the highest frequency and severity of pedestrian injuries. Collision profiles were developed to classify the most frequent types of vehicle–pedestrian collisions at each intersection. Corresponding pedestrian safety countermeasures, selected for their relatively high effectiveness and low cost, were matched with applicable collision profiles. A scenario planning process was used to formulate a final investment strategy: a prioritized pedestrian safety project list that targeted the specific needs at priority locations. The data-driven capital planning process helped to secure funding commitments to implement pedestrian safety projects at 195 intersections over the course of 5 years, which moved San Francisco closer to its policy objective to eliminate pedestrian fatalities. All cities face a challenge in the employment of rigorous analysis to select and prioritize improvement projects with limited funding. This study created a new, streamlined approach to capital-constrained project development and prioritization that is applicable to all types of safety improvements across any jurisdiction.