AIMC Topic: Automobile Driving
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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...
CCCNet: Criss-cross attention enhanced cross layer refinement network for lane detection in complex scenarios.
PloS one
Jan 1, 2025
Lane detection plays a crucial role in autonomous driving systems by enabling vehicles to comprehend road structure and ensure safe navigation. However, the current performance of lane line detection models, such as CCNet, exhibits limitations in han...
Enhanced Driver Stress Prediction from Multiple Biosignals via CNN Encoder-Decoder Model.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
In this work, we present PhysioFuseNet, a novel framework designed to enhance driver stress state classification. PhysioFuseNet integrates a CNN-based encoder-decoder model with multimodal biosignal fusion. Using a driving simulator, different multim...
Stiffness Adaptation of a Hybrid Soft Surgical Robot for Improved Safety in Interventional Surgery.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
Minimally invasive instruments are inserted per-cutaneously and are steered toward the desired anatomy. The low stiffness of instruments is an advantage; however, once the target is reached, the instrument usually is required to transmit force to the...
Partial directed coherence based graph convolutional neural networks for driving fatigue detection.
The Review of scientific instruments
Jul 1, 2020
The mental state of a driver can be accurately and reliably evaluated by detecting the driver's electroencephalogram (EEG) signals. However, traditional machine learning and deep learning methods focus on the single electrode feature analysis and ign...
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