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In the last two decades the efficient traffic-flow prediction of vehicles has been significant in curbing traffic congestions at freeways and road intersections and it is among the many advantages of applying intelligent transportation systems in road intersections. However, transportation researchers have not focused on prediction of vehicular traffic flow at road intersections using hybrid algorithms such as adaptive neuro-fuzzy inference systems optimized by genetic algorithms. In this research, we propose two models, namely the adaptive neuro-fuzzy inference system (ANFIS) and the adaptive neuro-fuzzy inference system optimized by genetic algorithm (ANFIS-GA), to model and predict vehicles at signalized road intersections using the South African public road transportation system. The traffic data used for this research were obtained via up-to-date traffic data equipment. Eight hundred fifty traffic datasets were used for the ANFIS and ANFIS-GA modelling. The traffic data comprised ....