A driver's road rage risk warning method and system

Abstract

The invention discloses a driver road rage risk early warning method and system, belonging to the field of intelligent driving assistance technology, comprising: acquiring real-time driving state data of the driver to be tested, the state data including facial activity data, head posture data, limb Action data and heart rate data; the state data is fused within the minimum interval of emotional change time length to obtain fused data; the fused data is used as the input of the pre-trained road rage level recognition time series model to obtain the road rage risk of the driver grade. The present invention can continuously detect and warn the driver of dangerous driving risk emotions during the driving period, and can warn the driver in advance before road rage occurs, prompting the driver to adjust the self-emotion.

Description

technical field [0001] The invention relates to the technical field of intelligent driving assistance, in particular to a driver's road rage risk warning method and system. Background technique [0002] As the process of automobile intelligence is accelerating, the control system of the car is also increasingly complex, and the contradiction between the driver and the control system of the car is also increasingly prominent. At the same time, "road rage" and the driver's driving tendency have a crucial impact on driving safety. [0003] At present, technical solutions for detection and early warning of anger mainly include the following two types: [0004] (1) Emotion recognition and detection method based on multimodal fusion [0005] Emotion recognition based on multi-modal fusion refers to the extraction of data about facial expressions, text, voice, posture, physiology and other modalities in the multimedia data based on the deep learning model through multimedia data ...

AI Technical Summary

Problems solved by technology

[0008] The above-mentioned existing solutions cannot directly provide a direct early warning solution for the driver's road rage risk problem, and the specific defects are reflected in the following aspects:

[0009] (1) The original driver risk warning is mainly aimed at pre-job risk warning, but driving is a continuous activity, and it is completely impossible to measure and estimate the risk change process in the driving process simply by pre-job risk warning

[0010] (2) The original emotion recognition technology includes the emotional labels of "normal, angry, happy, and sad", as well as the emotional labels of "positive, neutral, and negative". The main defect is that the distinction level has not been considered Emotional characteristics, such as "level 1 anger", "level 2 anger", but the degree of emotional activation can greatly affect the driver's driving behavior in practice

[0011] (3) The original emotion recognition technology is mainly aimed at identifying and detecting the emotional state of "the moment", but it is still unable to predict the future emotional state, especially negative emotional states such as anger, sadness, and anxiety. In practice, it is necessary to Predict negative emotional states to solve the problem of risk prevention in advance

[0012] (4) The original emotion recognition device has not considered the problem of carrying in the vehicle environment, so it lacks data storage, data calling and corresponding design after considering the vehicle hardware and vehicle environmental conditions, which may cause difficulties in the method and device. Enter the problem of running in the car environment

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