Deformable Pyramid Sparse Transformer for Semi-Supervised Driver Distraction Detection [PDF]
SensorsEnsuring sustained driver attention is critical for intelligent transportation safety systems; however, the performance of data-driven driver distraction detection models is often limited by the high cost of large-scale manual annotation. To address this
Qiang Zhao +6 more
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E2DR: A Deep Learning Ensemble-Based Driver Distraction Detection with Recommendations Model [PDF]
Sensors, 2022 The increasing number of car accidents is a significant issue in current transportation systems. According to the World Health Organization (WHO), road accidents are the eighth highest top cause of death around the world.
Mustafa Aljasim, Rasha Kashef
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NeuroSafeDrive: An Intelligent System Using fNIRS for Driver Distraction Recognition [PDF]
SensorsDriver distraction remains a critical factor in road accidents, necessitating intelligent systems for real-time detection. This study introduces a novel fNIRS-based method to to classify varying levels of driver distraction across diverse simulated ...
Ghazal Bargshady +6 more
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Integrated deep learning framework for driver distraction detection and real-time road object recognition in advanced driver assistance systems [PDF]
Scientific ReportsMost accidents are a result of distractions while driving and road user’s safety is a global concern. The proposed approach integrates advanced deep learning for driver distraction detection with real-time road object recognition to jointly address this ...
Rakesh Salakapuri +5 more
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Situational perception in distracted driving: an agentic multi-modal LLM framework [PDF]
Frontiers in Artificial IntelligenceIntroductionDistracted driving is a significant public safety concern, causing thousands of accidents annually. While most driver assistance systems emphasize distraction detection, they fail to deliver real-time environmental perception and context ...
Ahmad M. Nazar +3 more
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An intelligent network framework for driver distraction monitoring based on RES-SE-CNN [PDF]
Scientific ReportsAs the quantity of motor vehicles and drivers experiences a continuous upsurge, the road driving environment has grown progressively more complex. This complexity has led to a concomitant increase in the probability of traffic accidents.
Jichong Lei +8 more
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Driver distraction detection via multi‐scale domain adaptation network
IET Intelligent Transport Systems, 2023 Distracted driving is the leading cause of road traffic accidents. It is essential to monitor the driver's status to avoid traffic accidents caused by distracted driving.
Jing Wang, ZhongCheng Wu
doaj +1 more source
IEEE Access, 2022 Driver distraction behavior causes a large number of traffic accidents every year, resulting in economic losses and injuries. Currently, the driver still plays an important role in the driving and control of the vehicle due to the low level of vehicle ...
Taiguo Li +3 more
doaj +1 more source
A Study on road accidents and detection of driver’s distraction [PDF]
International Journal of Trend in Scientific Research and Development, 2018 The number and quantity of vehicles on roads have enlarged due to technological and cost effective progress in recent years. As a result of this increase, Avoiding the traffic and accidents have become one of the most important parts of our daily lives as people spend more time in traffic thereby forcing drivers and other road users to face a higher ...
Mrs Deepalakshmi. G +4 more
openaire +2 more sources
Driver Distraction Detection Based on Multi-scale Feature Fusion Network [PDF]
Jisuanji kexue, 2022 The occurrence of road traffic accidents has increased year by year.Driver inattention during driving is one of the major causes of traffic accidents.In this paper,we utilize multi-source data to detect driver distraction.However,the correlations derived
ZHANG Yu-xin, CHEN Yi-qiang
doaj +1 more source