AIMC Topic: Accidents, Traffic

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A hybrid CNN-ViT based framework for automatic traffic actions detection in smart cities.

PloS one
It is crucial to automatically detect traffic accidents and hazardous situations in a timely and accurate manner. In this way, both individual security will be ensured and significant contributions will be made to economic efficiency and sustainable ...

Driving style diversity in highway weaving areas: A drone-based analysis of population distribution patterns and operational parameter relationships.

PloS one
Driving style heterogeneity significantly influences traffic safety and efficiency in highway weaving areas, yet how operational parameters systematically shape population-level behavioral patterns remains unclear. This study examines the relationshi...

Feigning spectrum behaviour on the Neck Disability Index and Impact of Events Scale in whiplash associated disorder after motor vehicle crashes: a systematic assessment of classification models.

BMC psychology
PURPOSE: The aim of this study was to develop indices of feigning spectrum behaviour (FSB) on the Visual Analogue Pain Scale (VAS) Neck Disability Index (NDI) and Impact of Events Scale (IES) in people with whiplash associated disorder (WAD) after mo...

Higher hospital level does not improve 30-day survival after road traffic accidents.

Scientific reports
Globally, road traffic accidents (RTAs) remain a major cause of death, particularly among individuals aged 15-30 years. While Sweden has been at the forefront of traffic safety through the Vision Zero initiative, in-hospital management remains crucia...

Road traffic injuries (RTIs) in children and adolescents in India: an overview of epidemiology, reported reasons and its implications.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
INTRODUCTION: Road traffic injuries (RTIs) rank among the top causes of mortality and disability in children and adolescents, resulting in substantial socioeconomic impacts.

FastKAN-DDD: A novel fast Kolmogorov-Arnold network-based approach for driver drowsiness detection optimized for TinyML deployment.

PloS one
Driver drowsiness is a leading cause of traffic accidents and fatalities, highlighting the urgent need for intelligent systems capable of real-time fatigue detection. Although recent advancements in machine learning (ML) and deep learning (DL) have s...

Automatic road damage recognition based on improved YOLOv11 with multi-scale feature extraction and fusion attention mechanism.

PloS one
Rapid urbanization and growing traffic volumes have increased the demand for efficient and accurate road damage detection to ensure traffic safety and optimize maintenance. Traditional manual and vehicle-mounted inspection methods are often inefficie...

Deep reinforcement learning-based multi-lane mixed traffic ramp merging strategy.

PloS one
Due to concentrated conflicts, on-ramp merging is an important scenario in the study of new hybrid traffic control. Current research mainly focuses on optimizing the vehicle passage sequence of ramp vehicles merging with mainline vehicles in single-l...

Comparative evaluation of deep learning and traditional models for predicting traffic accident severity in Saudi Arabia.

Scientific reports
Road traffic accidents are one of the leading death causes around the globe, claiming millions of lives every year. Predicting traffic accident severity is essential for road users' safety and accident prevention. Artificial neural network (ANN), Boo...

Investigating factors influencing fatalities and injuries in animal-vehicle crashes using a random parameters logit model and ensemble machine learning approaches.

PloS one
Animal-vehicle crashes (AVC) pose risks in rural areas, often leading to casualties and injuries. Despite their infrequent occurrence, AVC can have significant consequences, especially when larger animals are involved. This study investigates factors...