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The objective of this study was to develop crash modification factors for four treatment types: rectangular rapid-flashing beacon (RRFB), pedestrian hybrid beacon (PHB), pedestrian refuge island (RI), and advance yield or stop markings and signs (AS). From 14 cities throughout the United States, 975 treatment and comparison sites were selected. Most of the treatment sites were selected at intersections on urban, multilane streets, because these locations present a high risk for pedestrian crashes and are where countermeasures typically are needed most. For each treatment site, relevant data were collected on the treatment characteristics, traffic, geometric, and roadway variables, and the pedestrian crashes and other crash types that occurred at each site. Cross-sectional regression models and before–after empirical Bayesian analysis techniques were used to determine the crash effects of each treatment type. All four of the treatment types were found to be associated with reductions in pedestrian crash risk, compared with the reductions at untreated sites. PHBs were associated with the greatest reduction of pedestrian crash risk (55% reduction), followed by RRFBs (47% reduction), RIs (32% reduction), and AS (25% reduction). The results for RRFBs had their basis in a limited sample and must be used with caution.

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This project implemented a comprehensive pedestrian safety program to reduce deaths and injuries among pedestrians in a large urban environment (Miami-Dade County, Florida). High-crash locations were targeted for countermeasure implementation and analysis. Using pedestrian crash data (1996–2001), four zones within the county were identified as having abnormally high pedestrian crash experiences. Based on crash characteristics and pedestrian factors (age, ethnicity), 16 education, enforcement and engineering treatments were implemented to reduce pedestrian crashes in the four zones and countywide. A before-after study design was used with three control groups to evaluate the effects of the program on pedestrian crashes. A 3-year after period was used (2002–2004). Multivariate intervention Auto-Regressive Integrated Moving Average time series analysis was used, along with non-parametric U-tests, to test for statistically significant differences in pedestrian crash experiences. Results showed that at the peak of the program effects in 2003 and 2004, the pedestrian safety program reduced countywide pedestrian crash rates by anywhere from 8.5% to 13.3%, depending on which control group was used. This effect translates to approximately 180 fewer crashes annually in the county, or 360 pedestrian crashes reduced for 2003 and 2004 combined, based on the more conservative 8.5% crash reduction. Countywide, the greatest crash reductions were found among children and adults; however, the program measures showed no effects in reducing crashes among older pedestrians. A number of lessons learnt were identified for future program implementation.