AIMC Topic: Automobile Driving
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An explainable machine learning framework for predicting driving states using electroencephalogram.
Medical engineering & physics
Jun 1, 2025
OBJECTIVES: Understanding drivers' cognitive load is essential for enhancing road safety, as cognitive demands fluctuate across different driving scenarios, potentially impacting performance, and safety, particularly for drivers with neurological dis...
Deep-ATM DL-LSTM: A novel adaptive thresholding model with dual-layer LSTM architecture for real-time driver drowsiness detection using skin conductance signals.
Computers in biology and medicine
Jun 1, 2025
Driver drowsiness detection systems are crucial for road safety. However, existing machine learning models struggle to adjust thresholds for Skin Conductance (SC) adaptively signals due to insufficient feature extraction of tonic and phasic responses...
Driver Steering Intention Prediction for Human-Machine Shared Systems of Intelligent Vehicles Based on CNN-GRU Network.
Sensors (Basel, Switzerland)
May 20, 2025
In order to mitigate human-machine conflicts and optimize shared control strategy in advance, it is essential for the shared control system to understand and predict driver behavior. This paper proposes a method for predicting driver steering intenti...
Real-time driver drowsiness detection using transformer architectures: a novel deep learning approach.
Scientific reports
May 20, 2025
Driver drowsiness is a leading cause of road accidents, resulting in significant societal, economic, and emotional losses. This paper introduces a novel and robust deep learning-based framework for real-time driver drowsiness detection, leveraging st...
Evaluation of data collection and annotation approaches of driver gaze dataset.
Behavior research methods
May 14, 2025
Driver gaze estimation is important for various driver gaze applications such as building advanced driving assistance systems and understanding driver gaze behavior. Gaze estimation in terms of gaze zone classification requires large-scale labeled da...
Artificial intelligence voice gender, gender role congruity, and trust in automated vehicles.
Scientific reports
May 11, 2025
Existing research on human-automated vehicle (AV) interactions has largely focused on auditory explanations, with less attention to how voice characteristics shape user trust. This paper explores the influence of gender similarity between users and A...
Assessment of Driver Inattention State Using Multimodal Wearable Signals and Cross-Attention-Driven Hierarchical Fusion.
Studies in health technology and informatics
Apr 8, 2025
Identifying driver inattention is crucial for road safety, driver well-being and can be enhanced using multimodal physiological signals. However, effective fusion of multimodal data is highly challenging, particularly with intermediate fusion, where ...
Modeling of injury severity of distracted driving accident using statistical and machine learning models.
PloS one
Jan 1, 2025
Distracted Driving (DD) is one of the global causes of high mortality and fatality in road traffic accidents. The increase in the number of distracted driving accidents (DDAs) is one of the concerns among transportation communities. The present study...
Research on autonomous obstacle avoidance of mountainous tractors based on semantic neural network and laser SLAM.
PloS one
Jan 1, 2025
The accuracy and consistency of obstacle avoidance map construction are poor in complex and changeable dynamic environment. In order to improve the driving safety of mountain tractors in complex mountain environment, an autonomous obstacle avoidance ...
Research on target detection based on improved YOLOv7 in complex traffic scenarios.
PloS one
Jan 1, 2025
Target detection is an essential direction in artificial intelligence development, and it is a crucial step in realizing environmental awareness for intelligent vehicles and advanced driver assistance systems. However, the current target detection al...
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