AIMC Topic: Accidents, Traffic

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Analyzing relationships between latent topics in autonomous vehicle crash narratives and crash severity using natural language processing techniques and explainable XGBoost.

Accident; analysis and prevention May 13, 2024
Safety is one of the most essential considerations when evaluating the performance of autonomous vehicles (AVs). Real-world AV data, including trajectory, detection, and crash data, are becoming increasingly popular as they provide possibilities for ...
Humans Automobiles Narration Natural Language Processing Accidents, Traffic
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Cognitive workload classification of law enforcement officers using physiological responses.

Applied ergonomics May 10, 2024
Motor vehicle crashes (MVCs) are a leading cause of death for law enforcement officers (LEOs) in the U.S. LEOs and more specifically novice LEOs (nLEOs) are susceptible to high cognitive workload while driving which can lead to fatal MVCs. The object...
Machine Learning Data Analysis Female Galvanic Skin Response Monitoring, Physiologic Police Random Forest Heart Rate Automobiles Adult Eye Movements Workload Area Under Curve Automobile Driving Time Factors Male Accidents, Traffic Cognition
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A novel perspective on the selection of an effective approach to reduce road traffic accidents under Fermatean fuzzy settings.

PloS one May 10, 2024
Road traffic accidents (RTAs) pose a significant hazard to the security of the general public, especially in developing nations. A daily average of more than three thousand fatalities is recorded worldwide, rating it as the second most prevalent caus...
Accidents, Traffic Humans Fuzzy Logic
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Child face detection on front passenger seat through deep learning.

Traffic injury prevention May 8, 2024
OBJECTIVE: One of the main causes of death worldwide among young people are car crashes, and most of these fatalities occur to children who are seated in the front passenger seat and who, at the time of an accident, receive a direct impact from the a...
Deep Learning Adolescent Child, Preschool Middle Aged Infant Infant, Newborn Young Adult Humans Child Aged Adult Female Accidents, Traffic Male Automated Facial Recognition Face Child Restraint Systems
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Comparing fatal crash risk factors by age and crash type by using machine learning techniques.

PloS one May 6, 2024
This study aims to use machine learning methods to examine the causative factors of significant crashes, focusing on accident type and driver's age. In this study, a wide-ranging data set from Jeddah city is employed to look into various factors, suc...
Young Adult Adult Male Middle Aged Adolescent Humans Female Accidents, Traffic Age Factors Risk Factors Machine Learning Aged Algorithms
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Analyzing the transition from two-vehicle collisions to chain reaction crashes: A hybrid approach using random parameters logit model, interpretable machine learning, and clustering.

Accident; analysis and prevention May 2, 2024
Chain reaction crashes (CRC) begin with a two-vehicle collision and rapidly intensify as more vehicles get directly involved. CRCs result in more extensive damage compared to two-vehicle crashes and understanding the progression of a two-vehicle coll...
Humans Cluster Analysis Accidents, Traffic Iran Machine Learning Risk Factors Logistic Models
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Supporting equitable and responsible highway safety improvement funding allocation strategies - Why AI prediction biases matter.

Accident; analysis and prevention Apr 17, 2024
The existing methodologies for allocating highway safety improvement funding closely rely on the utilization of crash prediction models. Specifically, these models produce predictions that estimate future crash hazard levels in different geographical...
Resource Allocation Bias Accidents, Traffic Safety Socioeconomic Factors Models, Statistical Humans Artificial Intelligence
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Comprehensive Assessment of Artificial Intelligence Tools for Driver Monitoring and Analyzing Safety Critical Events in Vehicles.

Sensors (Basel, Switzerland) Apr 12, 2024
Human factors are a primary cause of vehicle accidents. Driver monitoring systems, utilizing a range of sensors and techniques, offer an effective method to monitor and alert drivers to minimize driver error and reduce risky driving behaviors, thus h...
Artificial Intelligence Humans Automobile Driving Accidents, Traffic Safety
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Improving traffic accident severity prediction using MobileNet transfer learning model and SHAP XAI technique.

PloS one Apr 9, 2024
Traffic accidents remain a leading cause of fatalities, injuries, and significant disruptions on highways. Comprehending the contributing factors to these occurrences is paramount in enhancing safety on road networks. Recent studies have demonstrated...
Machine Learning Accidents, Traffic Neural Networks, Computer
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Real-time crash prediction on express managed lanes of Interstate highway with anomaly detection learning.

Accident; analysis and prevention Apr 5, 2024
To facilitate efficient transportation, I-4 Express is constructed separately from general use lanes in metropolitan area to improve mobility and reduce congestion. As this new infrastructure would undoubtedly change the traffic network, there is a n...
Automobile Driving Area Under Curve Accidents, Traffic Humans Neural Networks, Computer Machine Learning Environment Design
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