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EN
With the growing integration of smart technologies in transportation, the study of roundabout operational efficiency and safety remains a pertinent research area. This paper presents a novel method for evaluating roundabout performance using simulation-based techniques. By analysing two roundabout case studies in Aimsun, the study explores the implications of increasing market penetration of cooperative, connected, and autonomous vehicles on traffic dynamics. The study involves processing geometric and traffic data, categorizing entry lane types, developing benchmark capacity functions, processing micro-simulator input data, and conducting sensitivity analysis for model calibration. The findings advance roundabout design and management in smart road systems and offer insights into the intersection of roundabout research and smart mobility solutions.
EN
Smart roads integrate advanced technology to enhance safety, effectiveness, and eco-friendliness, revolutionizing transportation systems. Within this framework, connectivity and automation work together to improve road mobility and energy efficiency. However, there are still uncertainties regarding their effect on road safety and traffic operations, as well as assessment methods, especially for intersections and roundabouts. Navigating roundabouts involves complex decision-making influenced by cooperative and competitive interactions between human-driven vehicles and connected and autonomous driving vehicles (CADVs), affecting gap-acceptance patterns. This research employs Aimsun Next software to simulate the rising market penetration percentages of CADVs by examining assumption-based behavior on single-lane roundabouts. It integrates CADV-based capacity modification factors from the Highway Capacity Manual 2022 and compares adapted capacity curves for CADVs, with simulated capacities for model calibration. Critical model parameters affecting CADVs' ability to enhance roundabout safety and throughput are identified, with a focus on the transition towards cooperative driving in the context of smart roads.
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