![]() The ANN model results show testing regression values of R 2 (0.99901). During the ANN modelling of the truck traffic flow, we used 956 traffic datasets divided into 70% for training and 15% each for testing and validation. ![]() The truck traffic data was collected using up-to-date equipment such as video cameras and inductive loop detectors from the South Africa transportation network. In this study, we focused on modelling the traffic flow of trucks at signalized road intersections using traffic flow variables such as speed, traffic volume, traffic density, and time as our inputs and outputs. Over the years, it has been deduced that trucks, irrespective of their sizes, significantly impact their surrounding traffic flow due to their body sizes and operational features. This research evaluates the effect of trucks on some specific traffic flow features. Far, little attention has been paid to the modelling of trucks traffic flow using an artificial neural network model and evaluating the stability analysis of trucks depending on the heterogenous optimal velocity. ![]() The evolution of traffic-related accidents caused by long, short, and medium trucks at signalized road intersections have been underemphasized in the last few years. ![]()
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