Application of information entropy algorithm in safety risk prediction of road traffic driving behaviors

In the safety risk prediction process of driving behaviors, the influence of correlation among evaluation indexes is ignored, resulting in low prediction accuracy. Therefore, a safety risk prediction method of road traffic driving behaviors based on the information entropy algorithm is proposed. Firstly, according to the types of driving behaviors, the evaluation indexes representing driving behaviors are selected, and an evaluation index system is constructed. Then, the internal correlation among indexes is determined by the information entropy algorithm, and the comprehensive weight of indexes is calculated based on the index membership matrix. Then the prediction model is established. Finally, the safety risk level is determined to realize the safety risk prediction of driving behaviors. The simulation results show that the safety entropy value of the designed prediction method is 0.18, and the actual entropy value is 0.17, with a difference of 0.01 between them. Additionally, the deigned prediction method has high prediction accuracy, with prediction accuracy up to 0.94.