AIMC Topic: Accidents, Traffic

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A high-resolution trajectory data driven method for real-time evaluation of traffic safety.

Accident; analysis and prevention Dec 2, 2021
Real-time safety evaluation is essential for developing proactive safety management strategy and improving the overall traffic safety. This paper proposes a method for real-time evaluation of road safety, in which traffic states and conflicts are com...
Machine Learning Research Design Humans Accidents, Traffic Safety Logistic Models Support Vector Machine
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Vision-Based Driver's Cognitive Load Classification Considering Eye Movement Using Machine Learning and Deep Learning.

Sensors (Basel, Switzerland) Nov 30, 2021
Due to the advancement of science and technology, modern cars are highly technical, more activity occurs inside the car and driving is faster; however, statistics show that the number of road fatalities have increased in recent years because of drive...
Eye Movements Cognition Accidents, Traffic Automobile Driving Machine Learning Deep Learning Humans
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A Review of Deep Learning-Based Methods for Pedestrian Trajectory Prediction.

Sensors (Basel, Switzerland) Nov 13, 2021
Pedestrian trajectory prediction is one of the main concerns of computer vision problems in the automotive industry, especially in the field of advanced driver assistance systems. The ability to anticipate the next movements of pedestrians on the str...
Deep Learning Signal Processing, Computer-Assisted Humans Technology Automobile Driving Pedestrians Accidents, Traffic
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A Hybrid Deep Learning Model for Recognizing Actions of Distracted Drivers.

Sensors (Basel, Switzerland) Nov 8, 2021
With the rapid spreading of in-vehicle information systems such as smartphones, navigation systems, and radios, the number of traffic accidents caused by driver distractions shows an increasing trend. Timely identification and warning are deemed to b...
Humans Distracted Driving Accidents, Traffic Automobile Driving Neural Networks, Computer Deep Learning
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Deep-Learning-Based Approach for Iraqi and Malaysian Vehicle License Plate Recognition.

Computational intelligence and neuroscience Nov 6, 2021
Recognizing vehicle plate numbers is a key step towards implementing the legislation on traffic and reducing the number of daily traffic accidents. Although machine learning has advanced considerably, the recognition of license plates remains an obst...
Machine Learning Deep Learning Accidents, Traffic
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Crash Injury Severity Prediction Using an Ordinal Classification Machine Learning Approach.

International journal of environmental research and public health Nov 3, 2021
In many related works, nominal classification algorithms ignore the order between injury severity levels and make sub-optimal predictions. Existing ordinal classification methods suffer rank inconsistency and rank non-monotonicity. The aim of this pa...
Accidents, Traffic Neural Networks, Computer Machine Learning Algorithms
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Effect of pedestrian physique differences on head injury prediction in car-to-pedestrian accidents using deep learning.

Traffic injury prevention Oct 26, 2021
OBJECTIVE: The aim of this study is to identify the effects of pedestrian physique differences on head injury prediction in car-to-pedestrian accidents via deep learning.
Automobiles Humans Walking Finite Element Analysis Adult Deep Learning Craniocerebral Trauma Female Male Child Pedestrians Accidents, Traffic
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Accuracy of machine learning logistic regression in death prediction for patients of road traffic injury.

Asian journal of surgery Oct 15, 2021
Humans Machine Learning Logistic Models Accidents, Traffic Data Collection
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Mortality-Risk Prediction Model from Road-Traffic Injury in Drunk Drivers: Machine Learning Approach.

International journal of environmental research and public health Oct 8, 2021
BACKGROUND: Alcohol-related road-traffic injury is the leading cause of premature death in middle- and lower-income countries, including Thailand. Applying machine-learning algorithms can improve the effectiveness of driver-impairment screening strat...
Algorithms Cross-Sectional Studies Logistic Models Neural Networks, Computer Accidents, Traffic Machine Learning
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A deep learning approach for real-time crash prediction using vehicle-by-vehicle data.

Accident; analysis and prevention Sep 30, 2021
In road safety, real-time crash prediction may play a crucial role in preventing such traffic events. However, much of the research in this line generally uses data aggregated every five or ten minutes. This article proposes a new image-inspired data...
Accidents, Traffic Deep Learning Chile Humans Neural Networks, Computer
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