Abstract
Overtaking on two-lane undivided highways poses complex challenges, with attention traditionally focused on the overtaking vehicle. Yet, slow-moving vehicle (impeder) behaviour has been largely overlooked. This study investigates the yielding process whereby impeders actively support overtaking vehicles. This phenomenon can have implications for safety in autonomous environments and optimising Traffic control strategies. Empirical data, including drone-captured trajectories, were analyzed to develop predictive models for yielding behaviour. Prediction accuracies up to 82% and 85% for speed and space yielding were achieved, respectively. Integrating these models into microsimulation tools can supplement policy decisions, optimize Traffic flow, and mitigate accidents, yielding significant societal benefits.
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