Median U-Turn intersection traffic control in field-like traffic signal controllers: fuzzy logic Type 2 approach

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Purpose This article introduces an innovative approach to applying a Type 2 fuzzy logic system for Median U-Turn (MUT) traffic control, particularly for implementation by field controllers like Advanced System Controller 3 (ASC/3). A MUT is an alternative intersection which implies a shift of left-turn conflicts by at least 250 feet from the main intersection to the new downstream U-turn intersections. The study addresses the need for adaptable traffic control methods that can effectively manage the unique characteristics of MUT intersections, especially during periods of fluctuating traffic demand. Design/methodology/approach Simulation techniques are utilized (in Vissim–microsimulation software) to evaluate the performance of the proposed, Type 2 fuzzy logic-based control strategy under various traffic demand scenarios. In this article, the oversaturated traffic conditions at MUT were not addressed. Findings While fixed-time control is generally suitable for controlling traffic demand at alternative intersections, it lacks flexibility to address significant fluctuations. This article presents new, semi-actuated Type 2 fuzzy logic system for MUT intersections. Simulation results demonstrate that this control strategy surpasses conventional traffic control methods. Considering conducted tests, Type 2 fuzzy logic outperforms fixed-time control by 11.84% and actuated-time control by 48.58%. Research limitations/implications This study contributes to the field of traffic engineering by introducing a novel approach to traffic control at MUT intersections using Type 2 fuzzy logic. By demonstrating the effectiveness of this approach through simulation experiments, we provide valuable insights into the potential of fuzzy logic systems for optimizing traffic management in urban environments. Practical implications This study contributes to the field of traffic engineering with a novel, Type 2 fuzzy logic-based approach to traffic control at MUT intersections. By demonstrating the effectiveness of this approach through simulation experiments, we provide valuable insights into the potential of Type 2 fuzzy logic systems for optimizing traffic management in urban environments. Social implications Five experimental scenarios were created to examine the effectiveness of the suggested fuzzy control logic, focusing on control delay, number of stops per vehicle, fuel consumption and CO2 and NOx emissions. Obtained results showed that proposed fuzzy control logic can decrease CO2 and NOx emissions. Originality/value We confirm that this work is original and has not been published elsewhere, nor is it currently under consideration for publication in any other journal or conference proceedings.

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