AIMC Topic: Automobile Driving

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CBAM VGG16: An efficient driver distraction classification using CBAM embedded VGG16 architecture.

Computers in biology and medicine Aug 1, 2024
Driver monitoring systems (DMS) are crucial in autonomous driving systems (ADS) when users are concerned about driver/vehicle safety. In DMS, the significant influencing factor of driver/vehicle safety is the classification of driver distractions or ...
Attention Automobile Driving Distracted Driving Humans Neural Networks, Computer Deep Learning
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Deep learning approach for unified recognition of driver speed and lateral intentions using naturalistic driving data.

Neural networks : the official journal of the International Neural Network Society Jul 28, 2024
Driver intention recognition is a critical component of advanced driver assistance systems, with significant implications for improving vehicle safety, intelligence, and fuel economy. However, previous research on driver intention recognition has not...
Humans Neural Networks, Computer Female Intention Automobile Driving Adult Male Deep Learning
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Recognition of aggressive driving behavior under abnormal weather based on Convolutional Neural Network and transfer learning.

Traffic injury prevention Jul 24, 2024
OBJECTIVES: Aggressive driving behavior can lead to potential traffic collision risks, and abnormal weather conditions can exacerbate this behavior. This study aims to develop recognition models for aggressive driving under various climate conditions...
Male Weather Automobile Driving Aggression Machine Learning Computer Simulation Adult Humans Neural Networks, Computer
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An Identification Method for Road Hypnosis Based on Human EEG Data.

Sensors (Basel, Switzerland) Jul 6, 2024
The driver in road hypnosis has not only some external characteristics, but also some internal characteristics. External features have obvious manifestations and can be directly observed. Internal features do not have obvious manifestations and canno...
Humans Accidents, Traffic Automobile Driving Hypnosis Neural Networks, Computer Electroencephalography
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Exploring spatial heterogeneity in factors associated with injury severity in speeding-related crashes: An integrated machine learning and spatial modeling approach.

Accident; analysis and prevention Jul 4, 2024
Speeding, a risky act of driving a vehicle at a speed exceeding the posted limit, has consistently emerged as a leading contributor to traffic fatalities. Identifying the risk factors associated with injury severity in speeding-related crashes is ess...
Automobile Driving Spatial Analysis Wounds and Injuries Middle Aged Models, Statistical Accidents, Traffic Humans Machine Learning Female Risk Factors Adult Male
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Driver drowsiness is associated with altered facial thermal patterns: Machine learning insights from a thermal imaging approach.

Physiology & behavior Jun 23, 2024
Driver drowsiness is a significant factor in road accidents. Thermal imaging has emerged as an effective tool for detecting drowsiness by enabling the analysis of facial thermal patterns. However, it is not clear which facial areas are most affected ...
Body Temperature Thermography Sleep Stages Young Adult Adult Male Automobile Driving Sleepiness Face Machine Learning Computer Simulation Female Humans
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Driving Cognitive Alertness Detecting Using Evoked Multimodal Physiological Signals Based on Uncertain Self-Supervised Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jun 13, 2024
Multimodal physiological signals play a pivotal role in drivers' perception of work stress. However, the scarcity of labels and the multitude of modalities render the utilization of physiological signals for driving cognitive alertness detection chal...
Supervised Machine Learning Uncertainty Attention Humans Heart Rate Algorithms Automobile Driving Male Linear Models Cognition Entropy Electroencephalography
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Ultra-Wide Band Radar Empowered Driver Drowsiness Detection with Convolutional Spatial Feature Engineering and Artificial Intelligence.

Sensors (Basel, Switzerland) Jun 9, 2024
Driving while drowsy poses significant risks, including reduced cognitive function and the potential for accidents, which can lead to severe consequences such as trauma, economic losses, injuries, or death. The use of artificial intelligence can enab...
Radar Neural Networks, Computer Artificial Intelligence Humans Machine Learning Algorithms Support Vector Machine Automobile Driving
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Real-time driving risk prediction using a self-attention-based bidirectional long short-term memory network based on multi-source data.

Accident; analysis and prevention May 25, 2024
Early warning of driving risks can effectively prevent collisions. However, numerous studies that predicted driving risks have suffered from the use of single data sources, insufficiently advanced models, and lack of time window analysis. To address ...
Risk Assessment Accidents, Traffic Attention Automobile Driving Young Adult Adult Male Computer Simulation Female Humans Neural Networks, Computer
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The dynamic-static dual-branch deep neural network for urban speeding hotspot identification using street view image data.

Accident; analysis and prevention May 21, 2024
The visual information regarding the road environment can influence drivers' perception and judgment, often resulting in frequent speeding incidents. Identifying speeding hotspots in cities can prevent potential speeding incidents, thereby improving ...
Humans Neural Networks, Computer Accidents, Traffic Automobile Driving Deep Learning Cities Image Processing, Computer-Assisted
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