Road rage vehicle risk assessment and prevention and control method

Abstract

The invention discloses a road rage vehicle risk assessment and prevention and control method. The invention belongs to the technical field of automobile active safety. The method comprises the stepsof data collection, feature recognition, risk assessment and prevention and control, the collected data comprises video data, audio data, driver intrinsic attributes and an external factor set, emotion types and intensities are output through feature recognition, the emotional state of a driver is evaluated through a dangerous driving risk assessment model, and then prevention and control measuresare taken. According to the invention, real-time monitoring and discrimination of the road rage emotion of the driver can be realized, the emotion change of the driver can be predicted, prevention and control measures are taken in advance, and adverse effects of road rage on traffic safety can be effectively reduced.

Description

Technical field [0001] The invention belongs to the technical field of automobile active safety, and particularly relates to a road rage vehicle risk assessment and prevention and control method. Background technique [0002] Road rage is an excessive emotional reaction of the driver during driving. Emotional fluctuations in a short period of time are large, which makes it easier for drivers to adopt high-risk driving behaviors to deal with conflicts. At present, domestic and foreign research on "road anger" mainly includes the mechanism and influencing factors of the driver’s road anger emotion, the behavior of the driver when driving in anger, the impact of the driver’s angry driving on traffic safety, and the driver’s driving process. The recognition of road anger emotions. With the support of deep learning, information fusion, big data processing and other technologies, breakthroughs have been made in the recognition of road anger emotions, but the research on road anger em...

AI Technical Summary

Problems solved by technology

With the support of technologies such as deep learning, information fusion, and big data processing, breakthroughs have been made in the recognition of road rage emotions, but research on road rage emotion recognition is rarely combined with active safety, and road rage emotion recognition The subsequent control measures have a time lag, and cannot provide timely and effective assistance to the driver and early warning of bad behavior such as driving safety.

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