Driver distraction distinguishing method based on transverse driving speed

Abstract

The invention discloses a driver distraction judgment method based on a transverse driving speed. The driver distraction judgment method based on the transverse driving speed comprises the following steps: 1, collecting transverse traveling speed data at fixed time intervals; 2, making a time domain diagram of the transverse driving speed; 3, removing invalid data segments; 4, performing frequencyspectrum analysis on effective data segments; and 5, judging whether the driver has a distraction phenomenon and a distraction degree in the time interval, wherein the distraction degree comprises three grades of mild distraction, moderate distraction and severe distraction. By the invention, whether the driver has a distraction phenomenon in a driving process can be rapidly and effectively judged, thereby reducing the probability of traffic accidents caused by distraction of the driver.

Description

technical field [0001] The invention belongs to the application field of safe driving, in particular to a method for discriminating driver distraction based on the lateral running speed of a vehicle. Background technique [0002] With the development of society and economy, the number of cars is increasing, and the road traffic pressure is increasing. Various bad driving behaviors lead to a high incidence of traffic accidents, among which the distracted driving behavior is particularly serious. Studies at home and abroad have shown that driver distraction has a certain impact on the driver's driving performance, visual behavior patterns and physiological indicators, so there are significant differences in driving performance between the driver's distracted driving state and the normal driving state. [0003] At present, the research on the characteristics of distraction mainly focuses on the phenomena such as large speed changes, lane departures, and increased following dist...

AI Technical Summary

Problems solved by technology

[0005] 1. The data required by the existing distraction recognition technology mostly relies on different systems and devices to obtain data during driving. The data acquisition is cumbersome and the amount of data is huge, making recognition difficult

[0006] 2. The existing distraction recognition technology is mainly based on driving performance indicators such as large vehicle speed changes, lane departure, and increased following distance. It cannot eliminate the influence of random factors very well, and the recognition accuracy is low.

[0007] 3. Distraction has a classification. Most of the existing distraction recognition technologies treat distraction as a driving phenomenon, and do not carry out a finer classification of distraction.

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