Monitoring method for cognitive distraction of driver on basis of multi-source information fusion

Abstract

The invention relates to a monitoring method for cognitive distraction of a driver on the basis of multi-source information fusion, and belongs to the technical field of automotive active safety.The method comprises the steps that the steering wheel angle, the vehicle speed and the head orientation and fixation point position coordinate information of the driver are collected in real time; data collected in real time is arranged into a data sequence according to the time order; according to a time-domain statistical indicator set (cognitive distraction characteristic set) of the steering wheel angle, the vehicle speed and the head orientation and fixation point position coordinate information of the driver is calculated within the computing time window length range, and real-time monitoring is conducted on the cognitive distraction state of the driver by adopting feature-level multi-source information fusion based on a support vector machine.Therefore, the purposes of improving the driving safety and reducing road traffic accidents are achieved.

Description

technical field [0001] The invention belongs to the technical field of automobile active safety, and in particular relates to a driver's cognitive distraction state monitoring technology based on driver's operation information and eye movement information. Background technique [0002] In the road traffic system composed of people, motor vehicles, and road environment, the motor vehicle driver is a weak link in the system. The driving process is complex, including multiple links such as situation awareness, decision-making, and execution. It is inevitable that distraction errors, Sudden abnormalities such as wrong judgments directly lead to driving risks. There are many reasons for driver error, and inattention is one of the most important. The driver attention monitoring system is an advanced automotive driving assistance system. It monitors the driver's attention status in real time. When the driver's attention is low, it will directly give an alarm prompt and provide dri...

AI Technical Summary

Problems solved by technology

[0003] Existing attention monitoring systems are mostly aimed at low attention caused by fatigue that changes slowly, and distraction is highly time-varying and requires high real-time monitoring. The existing driver's attention monitoring cannot cope with this feature of distraction; Existing attention monitoring systems mostly focus on visual distraction, while cognitive distraction has complex performance, poor consistency of conclusions, and it is difficult to find common characteristics in different driving scenarios, making monitoring difficult

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