Estimating the Critical Gap for U-Turns at Uncontrolled Median Openings

Abstract

Critical gap is an essential traffic parameter for assessing the capacity of U-turning vehicles at uncontrolled median openings and plays a vital role in U-turn facility design. Inaccurate driver gap acceptance data in U-turn designs can lead to traffic congestion and increase the risk of severe accidents. This study aimed to estimate the critical gap for U-turns at uncontrolled median openings by analyzing real-world traffic behavior across three distinct U-turn patterns in Bangkok using various estimation methods. The results showed that the Raff method produced the lowest critical gap estimates during both peak and off-peak hours (3.24 to 5.39 seconds), followed by the Maximum Likelihood Estimation method (4.29 to 6.69 seconds), the Greenshield method (4.75 to 6.75 seconds), and the Acceptance Curve method, which yielded the highest estimates (6.75 to 9.30 seconds). The findings also revealed that as direct traffic volume increased, the estimated critical gap values from all methods tended to decrease, and differences in U-turn patterns influenced the critical gap values. Among the methods evaluated, the Maximum Likelihood Estimation method demonstrated the highest consistency in critical gap estimation under varying traffic conditions.