AIMC Topic: Accidents, Traffic

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A Real-Time Embedded System for Driver Drowsiness Detection Based on Visual Analysis of the Eyes and Mouth Using Convolutional Neural Network and Mouth Aspect Ratio.

Sensors (Basel, Switzerland) Sep 27, 2024
Currently, the number of vehicles in circulation continues to increase steadily, leading to a parallel increase in vehicular accidents. Among the many causes of these accidents, human factors such as driver drowsiness play a fundamental role. In this...
Sleepiness Eye Sleep Stages Mouth Automobile Driving Humans Neural Networks, Computer Artificial Intelligence Accidents, Traffic
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Investigation of a surrogate measure-based safety index for predicting injury crashes at signalized intersections.

Traffic injury prevention Sep 26, 2024
OBJECTIVES: The paper develops a machine learning-based safety index for classifying traffic conflicts that can be used to estimate the frequency of signalized intersection crashes, with a focus on the more severe ones that result in fatal and severe...
Environment Design Models, Statistical Regression Analysis Humans Neural Networks, Computer Machine Learning Video Recording Wounds and Injuries Accidents, Traffic Safety
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Evaluating the effectiveness of safety countermeasures at highway-railway grade crossing based on a machine learning framework.

Traffic injury prevention Sep 26, 2024
OBJECTIVE: This research aims to cluster similar highway-railway grade crossings (HRGCs) to examine the safety countermeasures at HRGCs.
Machine Learning Accidents, Traffic Safety Humans Environment Design Railroads Cluster Analysis
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Analysis of influencing factors of traffic accidents on urban ring road based on the SVM model optimized by Bayesian method.

PloS one Sep 24, 2024
Based on small scale sample of accident data from specific scenarios, fully exploring the potential influencing factors of the severity of traffic accidents has become a key and effective research method. In order to analyze the factors mentioned abo...
Cities Accidents, Traffic Humans Support Vector Machine China Bayes Theorem
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A hybrid approach for modeling bicycle crash frequencies: Integrating random forest based SHAP model with random parameter negative binomial regression model.

Accident; analysis and prevention Sep 16, 2024
To effectively capture and explain complex, nonlinear relationships within bicycle crash frequency data and account for unobserved heterogeneity simultaneously, this study proposes a new hybrid framework that combines the Random Forest-based SHapley ...
Risk Factors Support Vector Machine Models, Statistical Humans Machine Learning Algorithms Accidents, Traffic London Bicycling Regression Analysis Bayes Theorem Random Forest
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Optimizing vehicle Front-End structure for e-bike rider Safety: An advanced Multi-Objective approach using injury prediction models.

Accident; analysis and prevention Aug 29, 2024
A multi-objective optimization method based on an injury prediction model is proposed to address the increasingly prominent safety issues for e-bike riders in Chinese road traffic. This method aims to enhance the protective effect of vehicle front-en...
Humans Machine Learning Decision Support Techniques Bicycling Models, Theoretical Safety Biomechanical Phenomena Equipment Design Wounds and Injuries Accidents, Traffic Risk Assessment China
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Analyzing the heterogenous effects of factors on high-range speeding likelihood of taxi speeders: Does explainable deep learning provides more insights than random parameter approach?

Accident; analysis and prevention Aug 24, 2024
The random parameters Generalized Linear Model (GLM) is frequently used to model speeding characteristics and capture the heterogenous effects of factors. However, this statistical approach is seldom employed for prediction and generalization due to ...
Deep Learning Accidents, Traffic Automobile Driving Linear Models Risk-Taking Humans Neural Networks, Computer
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Gauging road safety advances using a hybrid EWM-PROMETHEE II-DBSCAN model with machine learning.

Frontiers in public health Aug 22, 2024
INTRODUCTION: Enhancing road safety conditions alleviates socioeconomic hazards from traffic accidents and promotes public health. Monitoring progress and recalibrating measures are indispensable in this effort. A systematic and scientific decision-m...
Humans Accidents, Traffic Machine Learning Safety Algorithms Reproducibility of Results Cluster Analysis
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Considering multi-scale built environment in modeling severity of traffic violations by elderly drivers: An interpretable machine learning framework.

Accident; analysis and prevention Aug 13, 2024
The causes of traffic violations by elderly drivers are different from those of other age groups. To reduce serious traffic violations that are more likely to cause serious traffic crashes, this study divided the severity of traffic violations into t...
Automobile Driving Built Environment Humans Machine Learning Aged, 80 and over Aged Bayes Theorem Accidents, Traffic
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Analysis of harsh braking and harsh acceleration occurrence via explainable imbalanced machine learning using high-resolution smartphone telematics and traffic data.

Accident; analysis and prevention Aug 8, 2024
Harsh driving events such as harsh brakings (HBs) and harsh accelerations (HAs) are promising Surrogate Safety Measures, already extensively utilised in road safety research. However, their occurrence relative to normal driving conditions has not bee...
Acceleration Greece Smartphone Accidents, Traffic Automobile Driving Adult Humans Machine Learning Algorithms Female Male
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