AIMC Topic: Accidents, Traffic
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Interpretable machine learning for evaluating risk factors of freeway crash severity.
International journal of injury control and safety promotion
May 20, 2024
Machine learning (ML) models are widely employed for crash severity modelling, yet their interpretability remains underexplored. Interpretation is crucial for comprehending ML results and aiding informed decision-making. This study aims to implement ...
Brain Deformation Estimation With Transfer Learning for Head Impact Datasets Across Impact Types.
IEEE transactions on bio-medical engineering
May 20, 2024
OBJECTIVE: The machine-learning head model (MLHM) to accelerate the calculation of brain strain and strain rate, which are the predictors for traumatic brain injury (TBI), but the model accuracy was found to decrease sharply when the training/test da...
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 ...
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...
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...
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...
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...
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...
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...
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...
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