Railway vehicle driver emotion recognition algorithm

Abstract

The invention discloses a railway vehicle driver emotion recognition algorithm. The algorithm comprises the following steps: S1, establishing a railway vehicle driver information database; s2, after a driver of the railway vehicle gets on duty, data information of the target object during the service providing period is obtained; s3, the collected data information is compared with the information database; s4, extracting Mel frequency domain features from the collected data information, and inputting the Mel frequency domain features into the trained convolutional neural network; s5, making an emotion fluctuation curve through a three-dimensional modeling system based on the trained convolutional neural network; and S6, intercepting fluctuation points of the emotion fluctuation curve in a future time period, and comparing the overlap ratios of t1 and t2. The emotion of the railway vehicle driver in the working period is obtained by monitoring the face information image, the limb action information image and the voice data of the railway vehicle driver in real time, different early warnings are made for different emotions, and the probability of occurrence of traffic accidents of the railway vehicle is reduced to the maximum extent.

Description

technical field [0001] The invention relates to the technical field of rail vehicle driver emotion recognition, in particular to a rail vehicle driver emotion recognition algorithm. Background technique [0002] There are many reasons for the occurrence of traffic accidents, generally speaking, human factors, vehicle factors, road and environmental factors, etc., among which human factors are the first. Among the human factors, the rail vehicle driver's factor is the most important, and the bad mood of rail vehicle drivers is an important cause of traffic accidents. [0003] When stimulated, most people express it through face, movement, eyes, etc. In the process of driving the vehicle, when the rail vehicle driver is happy and satisfied, he can feel comfortable and psychologically comfortable, and has a positive effect on the observation and judgment of things, often showing strong sensibility, diligent observation, and quick response. Accurate judgment and quick action a...

AI Technical Summary

Problems solved by technology

[0004] In the prior art, it is only possible to detect whether the current speed of the rail vehicle is overspeed, and to remind when it is overspeed, but it cannot solve the problem of increasing the probability of traffic accidents due to emotional instability of the rail vehicle driver

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