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The article offers information on the smart right-turn designs at traffic intersections in the U.S. and their impact on traffic safety, discussing the consideration of traffic crashes while building the design; and the use of Empirical Bayes method to assess the effectiveness of smart right-turns.

Introduction Understanding driver behavior is important for traffic safety and operation, especially at intersections where different traffic movements conflict. While most driver-behavior studies are based on simulation, this paper documents the analysis of driver-behavior at signalized intersections with the SHRP 2 Naturalistic Driving Study (NDS) data. This study analyzes the different influencing factors on the operation (speed control) and observation of right-turn drivers. Method A total of 300 NDS trips at six signalized intersections were used, including the NDS time-series sensor data, the forward videos and driver face videos. Different factors of drivers, vehicles, roads and environments were studied for their influence on driver behavior. An influencing index function was developed and the index was calculated for each influencing factor to quantitatively describe its influencing level. The influencing index was applied to prioritize the factors, which facilitates development and selection of safety countermeasures to improve intersection safety. Drivers' speed control was analyzed under different conditions with consideration of the prioritized influencing factors. Results Vehicle type, traffic signal status, conflicting traffic, conflicting pedestrian and driver age group were identified as the five major influencing factors on driver observation. Conclusions This research revealed that drivers have high acceleration and low observation frequency under Right-Turn-On-Red (RTOR), which constituted potential danger for other roadway users, especially for pedestrians. Practical applications As speed has a direct influence on crash rates and severities, the revealed speed patterns of the different situations also benefit selection of safety countermeasures at signalized intersections. [ABSTRACT FROM AUTHOR]

Objective: This article aimed to identify the main features of older driver casualty crashes, including detailed descriptions of injury outcomes. Methods: Data were obtained from the Transport Accident Commission insurance claims database for 2 groups of drivers: aged 41 to 55 years (middle-aged drivers) and aged 65 years and older (older drivers). Results: In terms of crash circumstances, the majority of crashes involved a collision with another vehicle (70.0% of middle-aged drivers and 68.7% of older drivers). The 2 main maneuvers at the time of crash were driving straight ahead (44.6% of middle-aged drivers and 42.8% of older drivers) and turning right (equivalent of left turn in North America; 15.2% of middle-aged drivers and 17.6% of older drivers). In terms of injury outcomes, older drivers sustained a significantly higher proportion of injuries to the thorax (30.9% compared to 18.5% of middle-aged drivers). Conversely, a significantly higher proportion of middle-aged drivers sustained some form of injury to the neck (30.6% compared to 12.1% of older drivers). Conclusion: These findings highlight the situations that are particularly risky for older drivers and provide important insights for developing solutions to reduce older driver crash and injury risk. [ABSTRACT FROM AUTHOR]

Sight distance at the intersection of a minor road (controlled by a stop sign) and a major road is an important element of road safety. Several models have been recently developed for the analysis of sight distance at intersections involving horizontal curves on the major road. All these models assume that the intersection lies within the horizontal curve. There are situations, however, when the intersection lies within one of the tangents of the horizontal curve. This case would adversely affect sight distance, especially when the horizontal curve is sharp and the minor road is close to the horizontal curve. This paper develops a new mathematical model for sight distance analysis that explicitly addresses the case where the intersection lies within the tangents of the horizontal curve. The obstruction may be located within the tangent or within the horizontal curve, or located inside or outside of the horizontal curve. Using the model, graphical aids for the required obstruction distances from the major and minor roads, to satisfy sight distance requirements, are developed. The developed model can be used to evaluate sight distance for existing or new intersections. [ABSTRACT FROM AUTHOR]

Traditional pedestrian level of service measures at signalized intersections are based on pedestrian space and pedestrian delay. However, these measures may not adequately reflect the negative impact of right-turning traffic on pedestrians. This paper presents a statistical analysis using a binary logit model that provides new insights into the factors that affect the likelihood that a pedestrian is compromised (delayed, altered their travel path, or altered their travel speed) in response to traffic turning right (on green) during concurrent vehicle/pedestrian signal timing. The statistical analysis indicates that a number of factors affect the likelihood of a pedestrian being compromised including pedestrian direction of travel, right-turn traffic volume, number of pedestrians crossing, whether the pedestrian arrived late and began crossing after the end of the walk interval, and the crosswalk characteristics including location (downtown versus suburban) and one-way/two-way streets. [ABSTRACT FROM AUTHOR]