AIMC Topic: Accidents, Traffic

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Exploring driving behavioral characteristics in pre-, in-, and post-conflict stages based on car-following trajectory data.

Ergonomics Aug 7, 2024
This study investigates driving behaviour in different stages of rear-end conflicts using vehicle trajectory data. Three conflict stages (pre-, in-, and post-conflict) are defined based on time-to-collision (TTC) indicator. Four indexes are selected ...
Female Young Adult Adult Humans Reaction Time Accidents, Traffic Automobile Driving Male Time Factors Automobiles
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Analyzing speed-difference impact on freeway joint injury severities of Leading-Following vehicles using statistical and data-driven models.

Accident; analysis and prevention Jul 6, 2024
Rear-end (RE) crashes are notably prevalent and pose a substantial risk on freeways. This paper explores the correlation between speed difference among the following and leading vehicles (Δν) and RE crash risk. Three joint models, comprising both unc...
Neural Networks, Computer Accidents, Traffic Support Vector Machine Models, Statistical Wounds and Injuries Humans Trauma Severity Indices
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An Identification Method for Road Hypnosis Based on Human EEG Data.

Sensors (Basel, Switzerland) Jul 6, 2024
The driver in road hypnosis has not only some external characteristics, but also some internal characteristics. External features have obvious manifestations and can be directly observed. Internal features do not have obvious manifestations and canno...
Automobile Driving Electroencephalography Humans Hypnosis Accidents, Traffic Neural Networks, Computer
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Exploring spatial heterogeneity in factors associated with injury severity in speeding-related crashes: An integrated machine learning and spatial modeling approach.

Accident; analysis and prevention Jul 4, 2024
Speeding, a risky act of driving a vehicle at a speed exceeding the posted limit, has consistently emerged as a leading contributor to traffic fatalities. Identifying the risk factors associated with injury severity in speeding-related crashes is ess...
Spatial Analysis Wounds and Injuries Male Middle Aged Models, Statistical Accidents, Traffic Automobile Driving Female Risk Factors Adult Humans Machine Learning
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A hybrid Machine learning and statistical modeling approach for analyzing the crash severity of mobility scooter users considering temporal instability.

Accident; analysis and prevention Jul 3, 2024
One of the main objectives in improving the quality of life for individuals with disabilities, especially those experiencing mobility issues such as the elderly, is to enhance their day-to-day mobility. Enabling easy mobility contributes to their ind...
Humans Machine Learning COVID-19 Male Middle Aged Persons with Disabilities Female Aged Adult United Kingdom Models, Statistical Accidents, Traffic
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Investigating the influence of streetscape environmental characteristics on pedestrian crashes at intersections using street view images and explainable machine learning.

Accident; analysis and prevention Jul 1, 2024
Examining the relationship between streetscape features and road traffic accidents is pivotal for enhancing roadway safety. While previous studies have primarily focused on the influence of street design characteristics, sociodemographic features, an...
Built Environment Algorithms Deep Learning Environment Design Pedestrians Accidents, Traffic Safety Humans Machine Learning
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Estimating helmet wearing rates via a scalable, low-cost algorithm: a novel integration of deep learning and google street view.

BMC public health Jun 20, 2024
INTRODUCTION: Wearing a helmet reduces the risk of head injuries substantially in the event of a motorcycle crash. Countries around the world are committed to promoting helmet use, but the progress has been slow and uneven. There is an urgent need fo...
Craniocerebral Trauma Accidents, Traffic Head Protective Devices Humans Algorithms Deep Learning
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Enabling CMF estimation in data-constrained scenarios: A semantic-encoding knowledge mining model.

Accident; analysis and prevention Jun 18, 2024
Availability of more accurate Crash Modification Factors (CMFs) is crucial for evaluating the effectiveness of various road safety treatments and prioritizing infrastructure investment accordingly. While customized study for each countermeasure scena...
Accidents, Traffic Data Mining Semantics Humans Natural Language Processing
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Real-time driving risk prediction using a self-attention-based bidirectional long short-term memory network based on multi-source data.

Accident; analysis and prevention May 25, 2024
Early warning of driving risks can effectively prevent collisions. However, numerous studies that predicted driving risks have suffered from the use of single data sources, insufficiently advanced models, and lack of time window analysis. To address ...
Automobile Driving Computer Simulation Humans Female Risk Assessment Adult Neural Networks, Computer Accidents, Traffic Young Adult Male Attention
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The dynamic-static dual-branch deep neural network for urban speeding hotspot identification using street view image data.

Accident; analysis and prevention May 21, 2024
The visual information regarding the road environment can influence drivers' perception and judgment, often resulting in frequent speeding incidents. Identifying speeding hotspots in cities can prevent potential speeding incidents, thereby improving ...
Neural Networks, Computer Deep Learning Cities Humans Image Processing, Computer-Assisted Accidents, Traffic Automobile Driving
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