Exploring Monitoring Systems Data for Driver Distraction and Drowsiness Research [PDF]
Sensors, 2020 Driver inattention is a major contributor to road crashes. The emerging of new driver monitoring systems represents an opportunity for researchers to explore new data sources to understand driver inattention, even if the technology was not developed with
Sara Ferreira +2 more
exaly +4 more sources
Driver Distraction Detection Methods: A Literature Review and Framework
IEEE Access, 2021 Driver inattention and distraction are the main causes of road accidents, many of which result in fatalities. To reduce road accidents, the development of information systems to detect driver inattention and distraction is essential.
Alexey Kashevnik +2 more
exaly +3 more sources
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
doaj +2 more sources
Wearable Driver Distraction Identification On-The-Road via Continuous Decomposition of Galvanic Skin Responses [PDF]
Sensors, 2018 One of the main reasons for fatal accidents on the road is distracted driving. The continuous attention of an individual driver is a necessity for the task of driving. While driving, certain levels of distraction can cause drivers to lose their attention,
Omid Dehzangi +2 more
doaj +2 more sources
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
doaj +2 more sources
Selection of Measurement Method for Detection of Driver Visual Cognitive Distraction: A Review
IEEE Access, 2017 Driving distraction is a topic of great interest in the transport safety-research community, because it is now a primary cause of road accidents. A recent report has revealed that distraction is more alarming than previously thought, and a suitable ...
Rana Fayyaz Ahmad +2 more
exaly +3 more sources
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
doaj +2 more sources
Driver Distraction Using Visual-Based Sensors and Algorithms [PDF]
Sensors, 2016 Ruben Casado +2 more
exaly +2 more sources
Classification of Driver Distraction Risk Levels: Based on Driver’s Gaze and Secondary Driving Tasks
Mathematics, 2022 Driver distraction is one of the significant causes of traffic accidents. To improve the accuracy of accident occurrence prediction under driver distraction and to provide graded warnings, it is necessary to classify the level of driver distraction ...
Lili Zheng +5 more
doaj +1 more source
Detection of Driver Cognitive Distraction Using Machine Learning Methods
IEEE Access, 2023 Driver distraction is one of the primary causes of crashes. As a result, there is a great need to continuously observe driver state and provide appropriate interventions to distracted drivers. Cognitive distraction refers to the “look but not see&#
Apurva Misra +3 more
doaj +1 more source