Access points play a critical role in traffic safety along arterial roadways. Among the various elements of access management, the segment between minor road connections and U-turn openings presents unique safety challenges due to frequent weaving maneuvers. A widely applied design in such contexts is the Right Turn Followed by U-Turn (RTUT) configuration, an access management strategy that replaces direct left turns with a right turn followed by a downstream U-turn. In these situations, drivers entering from minor roads and intending to make U-turns often need to quickly shift lanes from slower outer lanes to faster inner ones. When the separation distance (SD) between the minor road and the U-turn is short, drivers have limited time and space to accelerate and merge safely, increasing the likelihood of conflicts with through traffic. This study aims to determine the optimal SD and other contributing factors affecting road user safety in RTUT segments. Unlike most previous research that has focused on isolated variables or relied primarily on simulation based analysis, this study integrates multiple geometric and operational factors into a unified regression framework using high resolution UAV trajectory data. By combining field based trajectories with the Time to Collision (TTC) conflict measure, a proactive surrogate safety indicator, the analysis provides a more detailed and reliable assessment of conflict risk compared with traditional crash based approaches. To achieve this, UAV technology was used to monitor 10 arterial segments with SD ranging from about 200 to 500 m (186–488 m). The collected trajectories were compiled into a comprehensive database for regression analysis. Results indicate that SD has the most significant impact on safety, with TTC increasing by up to approximately 1 s for every 100 m increase in SD under maximum entry speeds, highlighting the critical role of SD in mitigating conflicts. Other variables, such as vehicle entry speed, number of lanes, acceleration lane length, and hourly traffic volume also showed statistically significant effects. By integrating UAV based trajectory data with a multivariate regression framework, this study provides a novel and generalizable method for evaluating RTUT safety under real traffic conditions. The findings deliver practical insights for designing safer arterial facilities by optimizing separation distance and other critical geometric and operational factors.
Amani et al. (Sat,) studied this question.