Bp Neural Network-based Smog Environment and the Risk Model of Mood Driving

In order to evaluate and study the influence of smog environment on driving safety, this paper utilizes the measurability of mood states, adopts back propagation (BP) artificial neural network instrument to establish a smog-risky mood network model. Six pictures in different smog levels were used as emotional stimuli to verify the BPM neural network-based smog-risky mood relation model. The result shows that the smog is a main factor affecting the driver's mood. The method of estimating moods based on the smog environment of BP network is able to predict 70% of the danger. It was proved to be an effective means for the safety management and self-detection of drivers, especially professional drivers.