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Review of Distracted Driving Detection Methods
CUI Tongchuan, WANG Xiaoqing, LI Yong, LI Yulong, SUN Weicheng
2025, 50(7):
41-45,52.
DOI: 10.16638/j.cnki.1671-7988.2025.007.008
With the development of vehicle automation and infotainment systems, the proportion of
accidents associated with driving distraction has increased, therefore driving distraction has
become an important and increasingly serious safety issue. In order to explore the research progress
of driving distraction detection methods, this paper summarizes the driving distraction detection
methods into single-class parameter method and multi-class parameter fusion method, and further
subdivides them into invasive detection method, semi-invasive detection method, non-invasive
detection method. And reviews the research status of detection methods at home and abroad,
discusses the scope of application and advantages and disadvantages of driving distraction
detection methods, and predicts the future research trend of driving distraction detection. The results show that the invasive detection method of the single-class parameter method has high
recognition accuracy and is highly invasive to the driver, and is more suitable for simulated driving
environment. The semi-invasive detection method has a certain degree of intrusion on driving, with
little impact and high accuracy, but is ex-post. The invasive detection method of multi-parameter
fusion method is highly invasive to the driver. Semi-invasive detection has high recognition
accuracy and low invasiveness, but is ex-post. In the future, it is possible to focus on the use of
semi-invasive detection of multi-parameter fusion method to identify distractions, focus on the
research on compound distraction recognition, carry out research on accurate identification of
distraction types, establish recognition models with different degrees of distraction, determine the
importance of identification indicators, and improve the evaluation system of recognition models.
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