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A U-turn at a mid-block median opening (MBMO) is a complex maneuver. The U-turning vehicle has to find a suitable gap between two fast-moving vehicles in the approaching through traffic (ATT) stream and decide whether to accept or reject the available gap. Incorrect judgment of an available gap may lead to congestion or a collision between the U-turning vehicle and ATT. Frequently, U-turning vehicles are in a state of dilemma while deciding whether to reject or accept the available gap. Under these scenarios, the decision-making process is a challenging task for U-turning vehicles. This article thus aims to analyze the dilemma zone of U-turning vehicles at MBMO by collecting field data from 14 locations. The dilemma zone has been estimated using three methods: the cumulative distribution method; the binary logit method; and the support vector machine (SVM) method. The length and location of the dilemma zone have been observed to be influenced by different types of vehicle. The dilemma zone has been observed to shift away from the nose of the MBMO as the size of the vehicle increases. Furthermore, a practical yet straightforward equation has been also suggested for estimating the dilemma zone based on the composition of the ATT stream. The outcome of the present study will be beneficial in understanding the dilemma associated with a U-turning driver at an MBMO. The estimated dilemma zone boundary can be used further to develop a warning system in association with the intelligent transportation system for helping U-turning vehicles complete the U-turn movement safely.

Critical gap is a crucial factor for capacity estimation and safety evaluation at uncontrolled mid-block median openings (MBMOs). The U-turning vehicle makes a U-turn when a sufficient gap between two fast-moving vehicles is available in the approaching through traffic (ATT) stream. Even though, worldwide, temporal gaps are extensively used, the spatial gap is an important parameter that significantly affects minor street vehicles’ safety (U-turning vehicles in this study). The present research, undertaken in India, focuses on estimating the temporal and spatial critical gap of U-turning vehicles at uncontrolled MBMOs. The collected data were analyzed for six different types of U-turning vehicles at varying approaching through traffic volume (ATTV). For critical gap estimation, four different critical gap estimation techniques, namely, modified Raff method (MRM), Ashworth method, binary logit model (BLM) method, and occupancy time (OT) method were employed, separately. From the analysis, temporal and spatial critical gaps were observed to vary between different types of vehicle, and it was also observed to vary with ATTV. The critical gap values of this study were found to be smaller than the critical values reported in developed countries, signifying the aggressive driving nature of drivers in developing countries. A detailed appraisal of the different critical gap estimation methods has been carried out. From this analysis, the OT method was found to provide the closest critical gap values with the published literature compared with other methods. Lastly, the findings from the present study will be useful for capacity estimation and safety evaluation at MBMO.

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