A Statistical Approach to Estimate Gap Acceptance Parameter at Three-Legged Uncontrolled Intersection

The estimation of the gap acceptance parameter for right-turning movements at uncontrolled T-intersections is the main focus of this paper. It takes a lot of effort to investigate an intersection that is unsignallised or is uncontrolled. In general, a driver's perception of the priority at an intersection is based on the volume of traffic, the design of the intersection, and the speed of the vehicle on main and minor approaches. Three uncontrolled T-intersections in the field were recorded as video in order to acquire the data. Accepted gaps, rejected gaps, vehicle types, and traffic composition are the data that were extracted from the video. The accepted and rejected gaps are fitted with various statistical distributions. The best-fitted model is recommended for the accepted and rejected gap based on goodness of fit tools, and the critical gap is estimated. Additionally, the critical gap value determined by best-fitted distributions (log-normal distribution) is compared to the values determined using Indo-HCM (Indo-HCM: Indian Highway Capacity Manual (Indo-HCM). CSIR-Central Road Res. Institute, New Delhi. (2017)). The value of the gap obtained using detailed traffic parameters can be further used for risk prediction to reduce the severity of crashes at uncontrolled intersections under mixed traffic conditions.