AIMC Topic: Automobile Driving

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A deep transfer learning approach for Real-Time traffic conflict prediction with trajectory data.

Accident; analysis and prevention Feb 17, 2025
Recently, real-time traffic conflict prediction has drawn increasing attention due to its significant potential in proactive traffic safety systems. While various statistical and machine learning models have been developed for conflict prediction, tr...
Humans Deep Learning Accidents, Traffic Automobile Driving
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Few-shot transfer learning for individualized braking intent detection on neuromorphic hardware.

Journal of neural engineering Feb 13, 2025
This work explores use of a few-shot transfer learning method to train and implement a convolutional spiking neural network (CSNN) on a BrainChip Akida AKD1000 neuromorphic system-on-chip for developing individual-level, instead of traditionally used...
Neural Networks, Computer Machine Learning Female Humans Intention Automobile Driving Transfer, Psychology Adult Male Electroencephalography
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Why do people resist AI-based autonomous cars?: Analyzing the impact of the risk perception paradigm and conditional value on public acceptance of autonomous vehicles.

PloS one Feb 6, 2025
This study examines the factors that lead to the acceptance of AI-based autonomous vehicles. Despite the considerable importance of AI-based autonomous vehicles there has been a lack of analysis based on theoretical models and analysis that considers...
Automobile Driving Perception Male Middle Aged Surveys and Questionnaires Adolescent Automobiles Aged Young Adult Adult Artificial Intelligence Female Humans
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EEG-based fatigue state evaluation by combining complex network and frequency-spatial features.

Journal of neuroscience methods Feb 3, 2025
BACKGROUND: The proportion of traffic accidents caused by fatigue driving is increasing year by year, which has aroused wide concerns for researchers. In order to rapidly and accurately detect drivers' fatigue, this paper proposed an electroencephalo...
Fatigue Adult Male Humans Electroencephalography Neural Networks, Computer Signal Processing, Computer-Assisted Brain Automobile Driving
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Real-Time Driver Drowsiness Detection Using Facial Analysis and Machine Learning Techniques.

Sensors (Basel, Switzerland) Jan 29, 2025
Drowsy driving poses a significant challenge to road safety worldwide, contributing to thousands of accidents and fatalities annually. Despite advancements in driver drowsiness detection (DDD) systems, many existing methods face limitations such as i...
Support Vector Machine Accidents, Traffic Neural Networks, Computer Automobile Driving Humans Face Machine Learning Sleep Stages Algorithms
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An integrative approach to generating explainable safety assessment scenarios for autonomous vehicles based on Vision Transformer and SHAP.

Accident; analysis and prevention Jan 13, 2025
Automated Vehicles (AVs) are on the cusp of commercialization, prompting global governments to organize the forthcoming mobility phase. However, the advancement of technology alone cannot guarantee the successful commercialization of AVs without insi...
Humans Artificial Intelligence Automobiles Automation Accidents, Traffic Safety Automobile Driving
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Automatic brake Driver Assistance System based on deep learning and fuzzy logic.

PloS one Dec 31, 2024
Advanced Driver Assistance Systems (ADAS) aim to automate transportation fully. A key part of this automation includes tasks such as traffic light detection and automatic braking. While indoor experiments are prevalent due to computational demands an...
Automobile Driving Automation Deep Learning Fuzzy Logic Humans Accidents, Traffic Algorithms
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Assessing the impact of car-following driving style on traffic conflict risk using asymmetric behavior model and explainable machine learning.

Accident; analysis and prevention Dec 24, 2024
To deepen the understanding of the impact of car-following driving style (CFDS) on traffic conflict risk and address the lack of clear CFDS evaluation metrics, this study proposes an improved CFDS metric based on the Asymmetric Behavior (AB) theory. ...
Automobiles Aggression Humans Accidents, Traffic Risk-Taking Machine Learning Automobile Driving Risk Assessment
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Cooperative control of self-learning traffic signal and connected automated vehicles for safety and efficiency optimization at intersections.

Accident; analysis and prevention Dec 19, 2024
Cooperative control of intersection signals and connected automated vehicles (CAVs) possess the potential for safety enhancement and congestion alleviation, facilitating the integration of CAVs into urban intelligent transportation systems. This rese...
Environment Design Automation Humans Accidents, Traffic Automobiles Deep Learning Safety China Automobile Driving
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Semantically-Enhanced Feature Extraction with CLIP and Transformer Networks for Driver Fatigue Detection.

Sensors (Basel, Switzerland) Dec 12, 2024
Drowsy driving is a leading cause of commercial vehicle traffic crashes. The trend is to train fatigue detection models using deep neural networks on driver video data, but challenges remain in coarse and incomplete high-level feature extraction and ...
Video Recording Semantics Fatigue Accidents, Traffic Automobile Driving Humans Neural Networks, Computer Algorithms
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