Determining vehicle pre-crash speed in frontal barrier crashes using artificial neural network for intermediate car class. (March 2020) - Mrowicki, Adam; Krukowski, Mateusz; Turoboś, Filip; Kubiak, Przemysław
Highlights: Authors use artificial neural network to find the precrash velocity in intermediate car class. This approach is showing improvement over linear method-9% vs up to 18%. The perceptron can be gradually improved and fine tuned producing even more accurate estimations. Abstract: This paper introduces a new, innovative approach to pre-crash velocity determination, namely the artificial neural networks. A perceptron based on a database obtained from NHTSA (National Highway Traffic Safety Administration) with numerous data concerning frontal vehicle crash tests: i.e. vehicle mass, deformation zone and deformation coefficients C1 -C6 . Part of the database entries were used to train the network to develop consistent accuracy and the remainder was used as validation and training sets.