AIMC Topic: Accidents, Traffic

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An intelligent network framework for driver distraction monitoring based on RES-SE-CNN.

Scientific reports Feb 26, 2025
As the quantity of motor vehicles and drivers experiences a continuous upsurge, the road driving environment has grown progressively more complex. This complexity has led to a concomitant increase in the probability of traffic accidents. Ample resear...
Automobile Driving Distracted Driving Humans Neural Networks, Computer Accidents, Traffic
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Prediction and interpretation of crash severity using machine learning based on imbalanced traffic crash data.

Journal of safety research Feb 25, 2025
INTRODUCTION: Predicting and interpreting crash severity is essential for developing cost-effective safety measures. Machine learning (ML) models in crash severity studies have attracted much attention recently due to their promising predicted perfor...
Risk Factors Accidents, Traffic Washington Humans Machine Learning
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Simulation of human-vehicle interaction at right-turn unsignalized intersections: A game-theoretic deep maximum entropy inverse reinforcement learning method.

Accident; analysis and prevention Feb 19, 2025
The safety of pedestrians in urban transportation systems has emerged as a significant research topic. As a vulnerable group within this transportation framework, pedestrians encounter heightened safety risks in complex urban road environments. Prote...
Game Theory Accidents, Traffic Safety Entropy Reinforcement, Psychology Markov Chains Walking Pedestrians Deep Learning Environment Design Algorithms Computer Simulation Humans
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Comparing AI and human-generated health messages in an Arabic cultural context.

Global health action Feb 18, 2025
BACKGROUND: AI is rapidly transforming the design of communication messages across various sectors, including health and safety. However, little is known about its effectiveness for roughly 420 million native Arabic speakers worldwide.
Female Adult Male Humans Artificial Intelligence Accidents, Traffic United Arab Emirates Health Communication Health Promotion
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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...
Deep Learning Accidents, Traffic Automobile Driving Humans
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Spatial heterogeneity effect of built environment on traffic safety using geographically weighted atrous convolutions neural network.

Accident; analysis and prevention Feb 8, 2025
The built environment exerts a significant influence on the frequency and severity of traffic accidents. Spatially uniform assumptions on the impacts of built environment factors commonly employed in existing research may lead to inconsistent and con...
Spatial Analysis Humans Built Environment Cities Neural Networks, Computer China Accidents, Traffic Environment Design Population Density Safety
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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 Machine Learning Humans Face Accidents, Traffic Algorithms Neural Networks, Computer Automobile Driving Sleep Stages
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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...
Automobile Driving Humans Automation Accidents, Traffic Artificial Intelligence Safety Automobiles
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Spatiotemporal multi-feature fusion vehicle trajectory anomaly detection for intelligent transportation: An improved method combining autoencoders and dynamic Bayesian networks.

Accident; analysis and prevention Jan 3, 2025
With the continuous development of intelligent transportation systems, traffic safety has become a major societal concern, and vehicle trajectory anomaly detection technology has emerged as a crucial method to ensure safety. However, current technolo...
China Time Factors Bayes Theorem Accidents, Traffic Models, Statistical Autoencoder Autonomous Vehicles
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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...
Accidents, Traffic Deep Learning Humans Automobile Driving Fuzzy Logic Automation Algorithms
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