In the present research, the influence of road geometric properties and traffic characteristics on the right lane capacity value is explored for horizontal curves. The non-traditional procedure (artificial neural networks - ANNs), is adopted for modelling. The research utilizes 78 horizontal curves that provide the traffic and road geometry data, of which55 curves are classified as four-lane and the rest as six-lane ones. Two types of models are introduced to explore the right lane capacity as capacity at curves, and the capacity loss between curves and tangents. The results show that, for horizontal curves, the most effective variables affecting both road types are the percentage of heavy vehicles in traffic composition (HV) followed by radius of curve (R), and the lane width (LW). Furthermore, the capacity loss is also highly affected by R followed by HV. The derived outcomes present a remarkable move towards the beginning of an Egyptian highway design guide.
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