The integration of cycling into urban traffic systems has increased significantly. Which drives the expansion of dedicated bicycle lanes at intersections to accommodate the growing cyclist volumes while ensuring traffic efficiency and safety. Addressing cyclists’ priority at signalized intersections presents a complex challenge, necessitating tailored traffic signals and control methods. This research proposes a cycling priority strategy for isolated intersections, using fuzzy logic to make high-quality decisions regarding cyclist priority while minimizing delays for all road users. The methodology involves developing a fuzzy logicbased cyclist priority strategy, using input variables such as vehicle queue and cyclist queue to determine cyclist priority. The evaluation, conducted using VISSIM microscopic traffic simulation, demonstrates that the proposed fuzzy logic-based control system effectively reduces delays and stops for cyclists, with an optimal preference threshold (P*) value of 0.7 balancing the needs of both cyclists and motor vehicles. Sensitivity analysis against traditional control methods further emphasises the potential of the fuzzy logic approach to enhance overall traffic efficiency and promote sustainable urban mobility.
«The integration of cycling into urban traffic systems has increased significantly. Which drives the expansion of dedicated bicycle lanes at intersections to accommodate the growing cyclist volumes while ensuring traffic efficiency and safety. Addressing cyclists’ priority at signalized intersections presents a complex challenge, necessitating tailored traffic signals and control methods. This research proposes a cycling priority strategy for isolated intersections, using fuzzy logic to make high...
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