AIMC Topic: Accidents, Traffic
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AMFormer-based framework for accident responsibility attribution: Interpretable analysis with traffic accident features.
PloS one
Jul 28, 2025
Accurately determining responsibility in traffic accidents is crucial for ensuring fairness in law enforcement and optimizing responsibility standards. Traditional methods predominantly rely on subjective judgments, such as eyewitness testimonies and...
Exploiting heart rate variability for driver drowsiness detection using wearable sensors and machine learning.
Scientific reports
Jul 10, 2025
Driver drowsiness is a critical issue in transportation systems and a leading cause of traffic accidents. Common factors contributing to accidents include intoxicated driving, fatigue, and sleep deprivation. Drowsiness significantly impairs a driver'...
An interpretable dynamic ensemble selection multiclass imbalance approach with ensemble imbalance learning for predicting road crash injury severity.
Scientific reports
Jul 9, 2025
Accurate prediction of crash injury severity and understanding the seriousness of multi-classification injuries is vital for informing authorities and the public. This Knowledge is crucial for enhancing road safety and reducing congestion, as differe...
Predicting errors in accident hotspots and investigating satiotemporal, weather, and behavioral factors using interpretable machine learning: An analysis of telematics big data.
PloS one
Jul 8, 2025
BACKGROUND: Road traffic accidents (RTAs) are a major public health concern with significant health and economic burdens. Identifying high-risk areas and key contributing factors is essential for developing targeted interventions. While machine learn...
Predicting car accident severity in Northwest Ethiopia: a machine learning approach leveraging driver, environmental, and road conditions.
Scientific reports
Jul 1, 2025
Road traffic accidents (RTAs) in Northwest Ethiopia, a region with a fatality rate of 32.2 per 100,000 residents, pose a critical public health challenge exacerbated by infrastructural deficits and environmental hazards. This study leverages machine ...
Advanced traffic conflict analysis for safety evaluation at roundabouts under mixed traffic using extreme value theory.
Accident; analysis and prevention
May 16, 2025
Roundabout safety evaluation in non-lane-based, heterogeneous traffic conditions in low-middle-income countries brings challenges due to unavailable/unreliable crash data, thereby switching to the utilization of safety surrogates. This study employed...
Pattern recognition in crash clusters involving vehicles with advanced driving technologies.
Accident; analysis and prevention
May 6, 2025
Autonomous Vehicle (AV) technologies, including Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS), have significant potential to reduce crashes caused by driver errors. However, as AVs become more prevalent on roadways, th...
Dynamic cross-domain transfer learning for driver fatigue monitoring: multi-modal sensor fusion with adaptive real-time personalizations.
Scientific reports
May 6, 2025
Driver fatigue is one of the most common causes of road accidents, which means that there is a great need for robust and adaptive monitoring systems. Current models of fatigue detection suffer from domain-specific limitations in generalizing across d...
Cyclist crash severity modeling: A hybrid approach of XGBoost-SHAP and random parameters logit with heterogeneity in means and variances.
Journal of safety research
May 5, 2025
INTRODUCTION: Across the globe, policymakers are focusing on boosting sustainable transport options, notably cycling, to foster eco-friendly urban environments. However, the persistent safety challenges cyclists face continues to hinder these efforts...
A dense multi-pooling convolutional network for driving fatigue detection.
Scientific reports
May 3, 2025
Driver fatigue is one of the major causes of traffic accidents, particularly for drivers of large vehicles, who are more susceptible to fatigue due to prolonged driving hours and monotonous conditions during their journeys. Existing vision-based driv...
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