Motorcycles, being a vehicle that offers its users, concomitantly, freedom, speed, and affordability, figure as one of the principal means of transportation in several emerging countries. However, in the scenario of benefits mentioned above, evident intrinsic harm to their use has been omitted: the exacerbated exposure of motorcyclists to accidents. Therefore, multiple efforts are being made to identify the road infrastructure components which are predominant in the increase of motorcyclists' accidents. Hence, this research proposal consists in the use of an Artificial Neural Network (ANN) model, a self-learning artificial intelligence that has an enormous potential in predicting and classifying phenomena, the Multilayer Perceptron (MLP), applied to an extensive and reliable database of accidents produced and supplied by the concessionaire responsible for the administration of stretches of Autopista Litoral Sul. This will be done to determine the aspects of road infrastructure that have major significance on motorcyclists' accidents, for the subsequent intensive search of previously applied solutions that have proven effectiveness, in conditions and scenarios close to this work, in increasing the efficiency of these components in terms of reducing the above-mentioned problem, thus offering support to road safety and public health in the country.
News published in Agência FAPESP Newsletter about the scholarship: