Alternative innovative designs for intersections were defined to enhance traffic operation and safety. Median U-turn (MUT) and restricted crossing U-turn (RCUT) intersections are among the types of alternative intersections that enable drivers to make left-turn movements at median U-turn crossovers downstream of the main intersection. Recently, municipalities and transport agencies have tended to implement these types of intersections. However, their effectiveness in crash reduction has not been adequately determined in previous studies. This is because of the limited number of alternative intersections that were considered in these studies. In addition, there was no consideration for the unusual new geometric design of these intersections. In this study, a safety evaluation was conducted while considering the new intersection-related areas at MUT and RCUT intersections to clarify and quantify their effectiveness in crash reduction. This study considered 73 MUT and 12 RCUT intersections. Two types of MUT intersections were considered in this study. Crash modification factors for MUT and RCUT intersections were estimated by using before–after and cross-sectional methods. The results indicated that MUT and RCUT intersections are safer than conventional intersections. MUT intersections are effective in reducing total, property damage only (PDO), rear-end, and opposite-direction sideswipe crashes, although they significantly increase single-vehicle and non-motorized crashes. RCUT intersections are effective in reducing fatal-and-injury, injury, head-on, and angle crashes. Findings of this research provide clear evaluation for decision makers about the effectiveness of MUT and RCUT intersections in crash reduction.
In recent years, cycling has become an increasingly popular transportation mode around the world. In comparison with other popular modes of transportation, cycling is economical and energy efficient. While many studies have been conducted for the analysis of bicycle safety, most were limited in bicycle exposure data and on-street data. This study tries to improve the current safety performance functions for bicycle crashes at urban corridors by utilizing crowdsource data from STRAVA and on-street speed management strategies data. Speed management strategies are any roadway alterations that cause a change in motorists’ driving behavior. In Florida, these speed management strategies are defined by the Florida Department of Transportation design manual. Considering the disproportionate representation of cyclists from the STRAVA data, adjustments were made to represent more accurately the cyclists based on the video detection data by developing a Tobit model. The adjusted STRAVA data was used for bicyclist exposure to analyze bicycle crashes on urban arterials. A Bayesian joint model was developed to identify the relations between the bicycle crash frequency and factors relating to speed management strategies. Other factors, such as vehicle traffic data, roadway information, socio-demographic characteristics, and land use data, were also considered in the model. The results suggest that the adjusted STRAVA data could be used as the exposure for bicycle crash analysis. The results also highlight the significant effects of speed management strategies, such as parking lots and surface pavement. It is expected that these findings could help engineers develop effective strategies to enhance safety for bicyclists.
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