Driver road rage risk early warning method and system

Abstract

The invention discloses a driver road rage risk early warning method and system, and belongs to the technical field of intelligent driving assistance, and the method comprises the steps: obtaining the real-time driving state data of a to-be-detected driver, the state data comprising facial activity data, head posture data, limb movement data and heart rate data; fusing the state data in the minimum interval of the emotion change time length to obtain fused data; and taking the fusion data as the input of a pre-trained road rage level identification time sequence model to obtain the road rage risk level of the driver. The dangerous driving risk emotion of the driver can be continuously detected and early warned in the driving period, early warning can be carried out in advance before the driver is in the road rage state, and the driver is prompted to carry out self emotion adjustment.

Description

technical field [0001] The present 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 car intelligence is accelerating, the control system of the car is becoming more and more complex, and the contradiction between the driver and the car control system is becoming more and more prominent. At the same time, "road rage" and the driver's driving tendency have a crucial impact on driving safety. [0003] Currently, anger detection and early warning technology solutions mainly include the following two types: [0004] (1) Emotion recognition and detection method based on multi-modal fusion [0005] Emotion recognition based on multi-modal fusion refers to multimedia data in the form of video, text, voice, etc., based on a deep learning model, to extract data about facial expressions, text, voice, body, physiological and other modalities ...

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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