Impact investigation of road characteristics on the accident rate based on the neural network modelling

Abstract

The use of neural networks promotes flexible non-linear modelling. Also, it is the perspective direction. The article investigates the influence of the main road characteristics on the accident rate. Twelve variables are selected as the main road characteristics. The result of modelling is the two-layer feed-forward neural network with hidden sigmoid nodes and linear output nodes. The operability of the model is estimated by calculating the index of regression by training, validation and testing. The results are acceptable for the intended purpose. The resulting model can be used for assessing and forecasting the safety rate on the two-lane roads with the intensity of 120 to 340 cars/hour. These include a significant part of the streets of CIS countries and other states. Besides, the neural network model can become the basis for the development of software products for assessing the accident rate based on road characteristics or can be implemented in existing software.